scientific journal | Q5633421 |
P6981 | ACNP journal ID | 44334 |
2112742 | ||
2112971 | ||
927934 | ||
P8375 | Crossref journal ID | 2911 |
3244 | ||
P1250 | Danish Bibliometric Research Indicator (BFI) SNO/CNO | 1091 |
P1058 | ERA Journal ID | 15245 |
P236 | ISSN | 0920-654X |
0928-2866 | ||
1573-4951 | ||
1573-9023 | ||
P1055 | NLM Unique ID | 8710425 |
9418303 | ||
P10283 | OpenAlex ID | V64621741 |
P3181 | OpenCitations bibliographic resource ID | 28716 |
245276 | ||
P8104 | Paperity journal ID | 255923 |
P1156 | Scopus source ID | 24619 |
55157 | ||
P5983 | Springer journal ID | 10822 |
P4616 | UniProt journal ID | 4057 |
P1240 | Danish Bibliometric Research Indicator level | 1 | |
P8875 | indexed in bibliographic review | Scopus | Q371467 |
Science Citation Index Expanded | Q104047209 | ||
P407 | language of work or name | English | Q1860 |
P123 | publisher | Springer Science+Business Media | Q176916 |
P1813 | short name | JCAMD | |
P1476 | title | Journal of Computer - Aided Molecular Design | |
Journal of Computer-Aided Molecular Design |
Q56979331 | Q56979331 |
Q56986646 | Q56986646 |
Q59188930 | Q59188930 |
Q60015703 | Q60015703 |
Q60488592 | Q60488592 |
Q63367548 | Q63367548 |
Q48230076 | "In silico" study of the binding of two novel antagonists to the nociceptin receptor |
Q52412458 | 'ValleyScan': a new two-bond drive technique for the calculation of potential energy surfaces with less computational effort |
Q35929548 | 1001 Ways to run AutoDock Vina for virtual screening |
Q44667597 | 2-Pyridone and 3-oxo-1,2,6-thiadiazine-1,1-dioxide derivatives: a new class of hydrogen bond equivalents of uracil |
Q62700164 | 2D and 3D QSAR studies of diarylpyrimidine HIV-1 reverse transcriptase inhibitors |
Q41549374 | 2D- and 3D-QSAR studies of a series of benzopyranes and benzopyrano[3,4b][1,4]-oxazines as inhibitors of the multidrug transporter P-glycoprotein |
Q44832225 | 3-D QSAR analysis of steroid/protein interactions: The use of difference maps |
Q40629130 | 3D QSAR (COMFA) of a series of potent and highly selective VLA-4 antagonists |
Q44667589 | 3D QSAR studies on binding affinities of coumarin natural products for glycosomal GAPDH of Trypanosoma cruzi |
Q74665324 | 3D hydrogen bond thermodynamics (HYBOT) potentials in molecular modelling |
Q43136203 | 3D-Pharmacophore mapping of thymidine-based inhibitors of TMPK as potential antituberculosis agents |
Q44711407 | 3D-QSAR and docking studies on 4-anilinoquinazoline and 4-anilinoquinoline epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors |
Q78325092 | 3D-QSAR and molecular modeling of HIV-1 integrase inhibitors |
Q81437679 | 3D-QSAR illusions |
Q56979316 | 3D-QSAR methods on the basis of ligand-receptor complexes. Application of COMBINE and GRID/GOLPE methodologies to a series of CYP1A2 ligands |
Q42853767 | 3D-QSAR studies and molecular docking on [5-(4-amino-1H-benzoimidazol-2-yl)-furan-2-yl]-phosphonic acid derivatives as fructose-1,6-biphophatase inhibitors |
Q28281913 | 3D-QSAR study of hallucinogenic phenylalkylamines by using CoMFA approach |
Q73013885 | 3D-QSAR using 'multiconformer' alignment: the use of HASL in the analysis of 5-HT1A thienopyrimidinone ligands |
Q33225366 | 3D-chiral atom, atom-type, and total non-stochastic and stochastic molecular linear indices and their applications to central chirality codification |
Q42664052 | 5,10-Methylene-5,6,7,8-tetrahydrofolate conformational transitions upon binding to thymidylate synthase: molecular mechanics and continuum solvent studies |
Q44968836 | 5-HT1A receptor pharmacophores to screen for off-target activity of α1-adrenoceptor antagonists. |
Q60546489 | A 3D QSAR CoMFA study of non-peptide angiotensin II receptor antagonists |
Q56978865 | A 3D QSAR approach to the search for geometrical similarity in a series of nonpeptide angiotensin II receptor antagonists |
Q33195977 | A Bayesian molecular interaction library. |
Q47415465 | A CADD-alog of strategies in pharma |
Q73652678 | A CoMFA analysis with conformational propensity: an attempt to analyze the SAR of a set of molecules with different conformational flexibility using a 3D-QSAR method |
Q39425242 | A D3R prospective evaluation of machine learning for protein-ligand scoring. |
Q30349714 | A Java applet for multiple linked visualization of protein structure and sequence. |
Q36877402 | A Monte Carlo method for finding important ligand fragments from receptor data |
Q72741855 | A Monte Carlo pharmacophore generation procedure: application to the human PAF receptor |
Q59188953 | A PLS QSAR analysis using 3D generated aromatic descriptors of principal property type: Application to some dopamine D2 benzamide antagonists |
Q30355593 | A Python tool to set up relative free energy calculations in GROMACS. |
Q54329542 | A QM/MM study of the associative mechanism for the phosphorylation reaction catalyzed by protein kinase A and its D166A mutant. |
Q62112721 | A QM/MM study of the binding of RAPTA ligands to cathepsin B |
Q89949713 | A Taxicab geometry quantification system to evaluate the performance of in silico methods: a case study on adenosine receptors ligands |
Q92260433 | A benchmark study of loop modeling methods applied to G protein-coupled receptors |
Q97427563 | A binding mode hypothesis for prothioconazole binding to CYP51 derived from first principles quantum chemistry |
Q92650830 | A blind SAMPL6 challenge: insight into the octanol-water partition coefficients of drug-like molecules via a DFT approach |
Q52234490 | A branch-and-bound method for optimal atom-type assignment in de novo ligand design. |
Q52435968 | A case for sharing. |
Q34220542 | A collaborative environment for developing and validating predictive tools for protein biophysical characteristics |
Q47217355 | A combined Fisher and Laplacian score for feature selection in QSAR based drug design using compounds with known and unknown activities. |
Q30357121 | A combined ligand-based and target-based drug design approach for G-protein coupled receptors: application to salvinorin A, a selective kappa opioid receptor agonist. |
Q48054359 | A combined treatment of hydration and dynamical effects for the modeling of host-guest binding thermodynamics: the SAMPL5 blinded challenge. |
Q77832767 | A comparative docking study and the design of potentially selective MMP inhibitors |
Q43566210 | A comparative molecular field analysis of cytochrome P450 2A5 and 2A6 inhibitors |
Q57021674 | A comparative molecular similarity index analysis (CoMSIA) study identifies an HLA-A2 binding supermotif |
Q43206017 | A comparative study of AutoDock and PMF scoring performances, and SAR of 2-substituted pyrazolotriazolopyrimidines and 4-substituted pyrazolopyrimidines as potent xanthine oxidase inhibitors |
Q42176495 | A comparative study of family-specific protein-ligand complex affinity prediction based on random forest approach |
Q33952708 | A comparative study of fragment screening methods on the p38α kinase: new methods, new insights |
Q77365342 | A comparative study of ligand-receptor complex binding affinity prediction methods based on glycogen phosphorylase inhibitors |
Q30391442 | A comparison of different functions for predicted protein model quality assessment |
Q52265017 | A comparison of heuristic search algorithms for molecular docking. |
Q92612919 | A comparison of molecular representations for lipophilicity quantitative structure-property relationships with results from the SAMPL6 logP Prediction Challenge |
Q28201523 | A comparison of progestin and androgen receptor binding using the CoMFA technique |
Q44325912 | A comparison of the pharmacophore identification programs: Catalyst, DISCO and GASP. |
Q80547849 | A comprehensive analysis of the thermodynamic events involved in ligand-receptor binding using CoRIA and its variants |
Q86826027 | A computational analysis of binding modes and conformation changes of MDM2 induced by p53 and inhibitor bindings |
Q43445035 | A computational analysis of the binding mode of closantel as inhibitor of the Onchocerca volvulus chitinase: insights on macrofilaricidal drug design |
Q34010186 | A computational analysis of the binding model of MDM2 with inhibitors |
Q36099514 | A computational docking study on the pH dependence of peptide binding to HLA-B27 sub-types differentially associated with ankylosing spondylitis |
Q74625543 | A computational model of the nicotinic acetylcholine binding site |
Q90952063 | A computational study of the molecular basis of antibiotic resistance in a DXR mutant |
Q71851464 | A computational study on the relative reactivity of reductively activated 1,4-benzoquinone and its isoelectronic analogs |
Q44912595 | A computational tool to optimize ligand selectivity between two similar biomacromolecular targets |
Q43122434 | A computational workflow for the design of irreversible inhibitors of protein kinases. |
Q73913505 | A computationally efficient alternative to the Buckingham potential for molecular mechanics calculations |
Q38973999 | A consistent S-Adenosylmethionine force field improved by dynamic Hirshfeld-I atomic charges for biomolecular simulation. |
Q28282247 | A consistent description of HYdrogen bond and DEhydration energies in protein-ligand complexes: methods behind the HYDE scoring function |
Q45059897 | A correlation study of quinoline derivatives and their pharmaceutical behavior by ab initio calculated NQR parameters |
Q47820357 | A critical assessment of finite element modeling approach for protein dynamics |
Q83298882 | A critical cross-validation of high throughput structural binding prediction methods for pMHC |
Q38610941 | A cross docking pipeline for improving pose prediction and virtual screening performance. |
Q28654731 | A crystallographic perspective on sharing data and knowledge |
Q89460089 | A deep learning approach for the blind logP prediction in SAMPL6 challenge |
Q44770779 | A density functional reactivity theory (DFRT) based approach to understand the interaction of cisplatin analogues with protecting agents |
Q35345510 | A desirability function-based scoring scheme for selecting fragment-like class A aminergic GPCR ligands. |
Q43476760 | A fast and efficient method for 2D and 3D molecular shape description |
Q34319994 | A fast and efficient method to generate biologically relevant conformations |
Q52373577 | A fast empirical method for the calculation of molecular polarizability. |
Q52402049 | A fast new approach to pharmacophore mapping and its application to dopaminergic and benzodiazepine agonists. |
Q52235674 | A flexible triangulation method to describe the solvent-accessible surface of biopolymers. |
Q57127520 | A fragment-based approach to the SAMPL3 Challenge |
Q87797011 | A functional feature analysis on diverse protein-protein interactions: application for the prediction of binding affinity |
Q52321852 | A genetic algorithm for flexible molecular overlay and pharmacophore elucidation. |
Q43936134 | A genetic algorithm for structure-based de novo design |
Q52346343 | A genetic algorithm for the automated generation of molecules within constraints. |
Q52076493 | A genetic algorithm for the automated generation of small organic molecules: drug design using an evolutionary algorithm. |
Q83845165 | A giant's shoulders: a perspective from Professor Norman L. Allinger |
Q48517142 | A grand vision for configurable science and minimizing the loss model. Interview by Wendy A. Warr. |
Q51708836 | A graph-theoretic approach to modeling metabolic pathways |
Q114689843 | A high quality, industrial data set for binding affinity prediction: performance comparison in different early drug discovery scenarios |
Q44268642 | A homology-based model of the human 5-HT2A receptor derived from an in silico activated G-protein coupled receptor |
Q38558151 | A hybrid approach for addressing ring flexibility in 3D database searching |
Q35918516 | A k-nearest neighbor classification of hERG K(+) channel blockers |
Q51899073 | A knowledge-based approach to generating diverse but energetically representative ensembles of ligand conformers. |
Q30367330 | A ligand's-eye view of protein binding. |
Q41151213 | A machine learning approach to computer-aided molecular design |
Q51932206 | A marriage made in torsional space: using GALAHAD models to drive pharmacophore multiplet searches. |
Q51297155 | A mechanism-based 3D-QSAR approach for classification and prediction of acetylcholinesterase inhibitory potency of organophosphate and carbamate analogs. |
Q44302800 | A method for fast energy estimation and visualization of protein-ligand interaction |
Q47252192 | A model for the binding of low molecular weight inhibitors to the active site of thrombin |
Q44490737 | A model of the human M2 muscarinic acetylcholine receptor |
Q52561640 | A modification to the COSMIC parameterisation using ab initio constrained potential functions. |
Q54111648 | A molecular dynamics investigation of CDK8/CycC and ligand binding: conformational flexibility and implication in drug discovery. |
Q40311614 | A molecular dynamics simulation study decodes the early stage of the disassembly process abolishing the human SAMHD1 function |
Q63916879 | A molecular graphics study exploring a putative ligand binding site of theβ-adrenoceptor |
Q41449034 | A molecular graphics study on structure-action relationships of calcium-antagonistic and agonistic 1,4-dihydropyridines |
Q46642481 | A molecular mechanism of P-loop pliability of Rho-kinase investigated by molecular dynamic simulation |
Q46159478 | A molecular model for the active site of S-adenosyl-L-homocysteine hydrolase |
Q72137023 | A molecular model of the folate binding site of Pneumocystis carinii dihydrofolate reductase |
Q47655100 | A molecular modeling study of inhibitors of nuclear factor kappa-B (p50)--DNA binding |
Q69373816 | A molecular modeling study on binding of drugs to calmodulin |
Q69360064 | A molecular modelling study of the interaction of noradrenaline with the beta 2-adrenergic receptor |
Q57012728 | A molecular-field-based similarity study of non-nucleoside HIV-1 reverse transcriptase inhibitors |
Q57012695 | A molecular-field-based similarity study of non-nucleoside HIV-1 reverse transcriptase inhibitors. 2. The relationship between alignment solutions obtained from conformationally rigid and flexible matching |
Q40814720 | A multivariate insight into the in vitro antitumour screen database of the National Cancer Institute: classification of compounds, similarities among cell lines and the influence of molecular targets. |
Q52244277 | A multiway 3D QSAR analysis of a series of (S)-N-[(1-ethyl-2-pyrrolidinyl)methyl]-6-methoxybenzamides. |
Q72741849 | A new approach to analysis and display of local lipophilicity/hydrophilicity mapped on molecular surfaces |
Q41812083 | A new fingerprint to predict nonribosomal peptides activity. |
Q48352338 | A new method for estimating the importance of hydrogen-bonding groups in the binding site of a protein. |
Q89928264 | A new method for estimating the relative binding free energy, derived from a free energy variational principle for the Pim-1-kinase-ligand and FKBP-ligand systems |
Q43181588 | A new method for ligand docking to flexible receptors by dual alanine scanning and refinement (SCARE). |
Q51890175 | A new paradigm for pattern recognition of drugs. |
Q51886827 | A new peptide docking strategy using a mean field technique with mutually orthogonal Latin square sampling. |
Q70984330 | A new procedure for improving the predictiveness of CoMFA models and its application to a set of dihydrofolate reductase inhibitors |
Q58225481 | A new scaling procedure to correct semiempirical MEP and MEP-derived properties |
Q52051313 | A new topological index to elucidate apolar hydrocarbons. |
Q91943045 | A noncanonical binding site of linezolid revealed via molecular dynamics simulations |
Q38724984 | A novel approach to molecular similarity |
Q52075976 | A novel method of aligning molecules by local surface shape similarity. |
Q59660974 | A novel scoring function for molecular docking |
Q44536459 | A novel view of modelling interactions between synthetic and biological polymers via docking |
Q79217779 | A novel workflow for the inverse QSPR problem using multiobjective optimization |
Q78429542 | A pharmacophore model for NK2 antagonist comprising compounds from several structurally diverse classes |
Q73331720 | A pharmacophore model for dopamine D4 receptor antagonists |
Q50616685 | A pose prediction approach based on ligand 3D shape similarity. |
Q44172742 | A practical procedure for the determination of electrostatic charges of large molecules |
Q68121886 | A prediction of the three-dimensional structure of maize NADP(+)-dependent malate dehydrogenase which explains aspects of light-dependent regulation unique to plant enzymes |
Q72933430 | A preliminary 3D model for cytochrome P450 2D6 constructed by homology model building |
Q41363342 | A probabilistic method to report predictions from a human liver microsomes stability QSAR model: a practical tool for drug discovery |
Q45059893 | A promising enantioselective Diels-Alder dienophile by computer-assisted rational design: 2,5-diphenyl-1-vinyl-borolane |
Q68280783 | A proposal for the molecular basis of ? and ? opiate receptor differentiation based on modeling of two types of cyclic enkephalins and a narcotic alkaloid |
Q57136306 | A proposed bioactive conformation of peptide T |
Q71699011 | A proposed common spatial pharmacophore and the corresponding active conformations of some peptide leukotriene receptor antagonists |
Q57138107 | A pseudoreceptor docking study of 4,5-?-epoxymorphinans with a range of dielectric constants |
Q45768558 | A pseudoreceptor modelling study of the varicella-zoster virus and human thymidine kinase binding sites. |
Q53118011 | A quantum mechanics/molecular mechanics study on the hydrolysis mechanism of New Delhi metallo-β-lactamase-1. |
Q58225433 | A quantum-mechanical study of the chain-length dependent stability of the extended and 310-helix conformations in dehydroalanine oligopeptides |
Q81581023 | A recursive-partitioning model for blood-brain barrier permeation |
Q91818380 | A remark on the efficiency of the double-system/single-box nonequilibrium approach in the SAMPL6 SAMPLing challenge |
Q34186750 | A reverse combination of structure-based and ligand-based strategies for virtual screening |
Q34937524 | A review of protein-small molecule docking methods |
Q32058635 | A search for sources of drug resistance by the 4D-QSAR analysis of a set of antimalarial dihydrofolate reductase inhibitors |
Q44002887 | A semiempirical SCF-MO study of the tautomeric forms of 3-acetyl tetronic- and tetramic acids |
Q77336352 | A semiempirical study on inhibition of catechol O-methyltransferase by substituted catechols |
Q43701176 | A sequence and structural study of transmembrane helices |
Q72816258 | A shape- and chemistry-based docking method and its use in the design of HIV-1 protease inhibitors |
Q30418333 | A shape-based machine learning tool for drug design |
Q86792219 | A simple, fast and convenient new method for predicting the stability of nitro compounds |
Q45768209 | A structural and energetics analysis of the binding of a series of N-acetylneuraminic-acid-based inhibitors to influenza virus sialidase |
Q44882009 | A structure-activity relationship study of catechol-O-methyltransferase inhibitors combining molecular docking and 3D QSAR methods |
Q44490685 | A structure-based design approach for the identification of novel inhibitors: application to an alanine racemase. |
Q30355430 | A structure-guided approach for protein pocket modeling and affinity prediction. |
Q46932252 | A successful virtual screening application: prediction of anticonvulsant activity in MES test of widely used pharmaceutical and food preservatives methylparaben and propylparaben |
Q52453040 | A supermolecule study of the effect of hydration on the conformational behaviour of leucine-enkephalin. |
Q47373331 | A support vector machine approach to classify human cytochrome P450 3A4 inhibitors |
Q43555845 | A theoretical approach to the influence of the macrocycle conformation on the molecular electronic structure in Mg-porphyrins |
Q40894842 | A theoretical model for the Gla-TSR-EGF-1 region of the anticoagulant cofactor protein S: from biostructural pathology to species-specific cofactor activity |
Q69601234 | A theoretical study of Zn++ interacting with models of ligands present at the thermolysin active site |
Q69843553 | A theoretical study of angiotensin-converting enzyme inhibitors |
Q46699174 | A theoretical study of cis-trans isomerisation in H-ZSM5: probing the impact of cluster size and zeolite framework on energetics and structure |
Q69601228 | A theoretical study of the Si-O bond in disiloxane and related molecules |
Q45423719 | A three-dimensional model of the human immunodeficiency virus type 1 integration complex |
Q44351042 | A uniform molecular model of delta opioid agonist and antagonist pharmacophore conformations |
Q43773521 | A unique geometry of the active site of angiotensin-converting enzyme consistent with structure-activity studies |
Q52025325 | A validation study on the practical use of automated de novo design. |
Q33220760 | A very large diversity space of synthetically accessible compounds for use with drug design programs |
Q48522021 | A very short history of structure-based design: how did we get here and where do we need to go? |
Q80082286 | A virtual active compound produced from the negative image of a ligand-binding pocket, and its application to in-silico drug screening |
Q30760210 | A virtual high throughput screen for high affinity cytochrome P450cam substrates. Implications for in silico prediction of drug metabolism |
Q30847753 | A virtual library of constrained cyclic tetrapeptides that mimics all four side-chain orientations for over half the reverse turns in the protein data bank. |
Q48311186 | A well deserved honor: Yvonne Martin, 2009 recipient of the Herman Skolnik Award. |
Q55059522 | A β-solenoid model of the Pmel17 repeat domain: insights to the formation of functional amyloid fibrils. |
Q91406530 | A3 adenosine receptor activation mechanisms: molecular dynamics analysis of inactive, active, and fully active states |
Q31052629 | ADAAPT: Amgen's data access, analysis, and prediction tools |
Q42131971 | AFAL: a web service for profiling amino acids surrounding ligands in proteins |
Q34465525 | ALADDIN: an integrated tool for computer-assisted molecular design and pharmacophore recognition from geometric, steric, and substructure searching of three-dimensional molecular structures |
Q51152903 | ALOHA: a novel probability fusion approach for scoring multi-parameter drug-likeness during the lead optimization stage of drug discovery. |
Q44501183 | AM1-SM2 and PM3-SM3 parameterized SCF solvation models for free energies in aqueous solution |
Q101210938 | AMOEBA binding free energies for the SAMPL7 TrimerTrip host-guest challenge |
Q73194550 | ANLIZE: a molecular mechanics force field visualization tool and its application to 18-crown-6 |
Q46704259 | ANVAS: artificial neural variables adaptation system for descriptor selection |
Q92763910 | ART-RRT: As-Rigid-As-Possible search for protein conformational transition paths |
Q91438193 | AZT acts as an anti-influenza nucleotide triphosphate targeting the catalytic site of A/PR/8/34/H1N1 RNA dependent RNA polymerase |
Q47742309 | Ab initio calculations on iron-porphyrin model systems for intermediates in the oxidative cycle of cytochrome P450s |
Q74633115 | Ab initio calculations on peptide-derived oxazoles and thiazoles: improved molecular mechanics parameters for the AMBER force field |
Q39214506 | Ab initio computational modeling of long loops in G-protein coupled receptors |
Q73652664 | Ab initio study on tautomerism of 2-thiouracil in the gas phase and in solution |
Q46531344 | Ab initio study on the noncovalent adsorption of camptothecin anticancer drug onto graphene, defect modified graphene and graphene oxide |
Q91056192 | Absolute and relative pKa predictions via a DFT approach applied to the SAMPL6 blind challenge |
Q47567527 | Absolute binding free energies for octa-acids and guests in SAMPL5 : Evaluating binding free energies for octa-acid and guest complexes in the SAMPL5 blind challenge. |
Q57463690 | Absolute binding free energies for the SAMPL6 cucurbit[8]uril host-guest challenge via the AMOEBA polarizable force field |
Q47567557 | Absolute binding free energy calculations of CBClip host-guest systems in the SAMPL5 blind challenge. |
Q35209226 | Academic librarians at play in the field of cheminformatics: building the case for chemistry research data management |
Q64119550 | Active learning strategies with COMBINE analysis: new tricks for an old dog |
Q83898270 | Active site acidic residues and structural analysis of modelled human aromatase: a potential drug target for breast cancer |
Q84567874 | Active site similarity between human and Plasmodium falciparum phosphodiesterases: considerations for antimalarial drug design |
Q72393570 | Active-site mobility inhibits reductive dehalogenation of 1,1,1-trichloroethane by cytochrome P450cam |
Q61833165 | Active-site-directed 3D database searching: Pharmacophore extraction and validation of hits |
Q48041442 | Activity cliffs in PubChem confirmatory bioassays taking inactive compounds into account |
Q61998568 | Activity prediction of substrates in NADH-dependent carbonyl reductase by docking requires catalytic constraints and charge parameterization of catalytic zinc environment |
Q28611248 | Activity, assay and target data curation and quality in the ChEMBL database |
Q43060708 | Adapting the semi-explicit assembly solvation model for estimating water-cyclohexane partitioning with the SAMPL5 molecules. |
Q98772845 | Addressing free fatty acid receptor 1 (FFAR1) activation using supervised molecular dynamics |
Q91624878 | Advanced Editorial to announce a JCAMD Special Issue on Artificial Intelligence and Machine Learning |
Q94523223 | Advances in exploring activity cliffs |
Q90797650 | Alchemical Grid Dock (AlGDock) calculations in the D3R Grand Challenge 3 : Binding free energies between flexible ligands and rigid receptors |
Q30419602 | Alchemical prediction of hydration free energies for SAMPL. |
Q74274403 | Alignment of flexible molecules at their receptor site using 3D descriptors and Hi-PCA |
Q36804259 | Alignment-independent technique for 3D QSAR analysis |
Q37549101 | All-atom/coarse-grained hybrid predictions of distribution coefficients in SAMPL5. |
Q51080699 | AllChem: generating and searching 10(20) synthetically accessible structures. |
Q34620088 | Allosteric antagonist binding sites in class B GPCRs: corticotropin receptor 1. |
Q38736870 | Allosteric modulation model of the mu opioid receptor by herkinorin, a potent not alkaloidal agonist |
Q30470433 | Alpha shock |
Q41264901 | An SH2 domain model of STAT5 in complex with phospho-peptides define "STAT5 Binding Signatures". |
Q43605227 | An ab initio theoretical study of the stereoisomers of tetrahydrocannabinols |
Q97427957 | An activity prediction model for steroidal and triterpenoidal inhibitors of Acetylcholinesterase enzyme |
Q68034483 | An approach to computer-aided inhibitor design: application to cathepsin L |
Q54451282 | An approximate but efficient method to calculate free energy trends by computer simulation: application to dihydrofolate reductase-inhibitor complexes. |
Q43463114 | An approximation of the Cioslowski–Mixon bond order indexes using the AlteQ approach |
Q58043817 | An atomistic model of passive membrane permeability: application to a series of FDA approved drugs |
Q51536809 | An automated PLS search for biologically relevant QSAR descriptors. |
Q73604181 | An automated method for predicting the positions of hydrogen-bonding atoms in binding sites |
Q31004695 | An effective simulation of aqueous micellar aggregates by computational models |
Q42973032 | An efficient synthesis of a rationally designed 1,5 disubstituted imidazole AT(1) angiotensin II receptor antagonist: reorientation of imidazole pharmacophore groups in losartan reserves high receptor affinity and confirms docking studies |
Q78057602 | An electron-conformational method of identification of pharmacophore and anti-pharmacophore shielding: application to rice blast activity |
Q46865357 | An eleven amino acid residue deletion expands the substrate specificity of acetyl xylan esterase II (AXE II) from Penicillium purpurogenum. |
Q52370106 | An evaluation of molecular models of the cytochrome P450 Streptomyces griseolus enzymes P450SU1 and P450SU2. |
Q57057113 | An explicit-solvent hybrid QM and MM approach for predicting pKa of small molecules in SAMPL6 challenge |
Q48643849 | An exploration of a novel strategy for superposing several flexible molecules. |
Q40965375 | An extensive ecdysteroid CoMFA. |
Q43611751 | An improved adaptive genetic algorithm for protein-ligand docking |
Q46378945 | An improved method to predict the entropy term with the MM/PBSA approach. |
Q28210723 | An improved nicotinic pharmacophore and a stereoselective CoMFA-model for nicotinic agonists acting at the central nicotinic acetylcholine receptors labelled by |
Q36838120 | An improved relaxed complex scheme for receptor flexibility in computer-aided drug design |
Q51867361 | An improved scoring function for suboptimal polar ligand complexes. |
Q44343144 | An improved theoretical approach to the empirical corrections of density functional theory |
Q51967889 | An in silico approach for screening flavonoids as P-glycoprotein inhibitors based on a Bayesian-regularized neural network. |
Q38559638 | An inequality for 3D database searching and its use in evaluating the treatment of conformational flexibility |
Q30616554 | An informatic pipeline for managing high-throughput screening experiments and analyzing data from stereochemically diverse libraries |
Q48110381 | An insight to the molecular interactions of the FDA approved HIV PR drugs against L38L↑N↑L PR mutant |
Q35201046 | An integrated approach to knowledge-driven structure-based virtual screening |
Q54275024 | An integrated suite of modeling tools that empower scientists in structure- and property-based drug design. |
Q48556761 | An interview with Jim Hopkins, CEO of Tripos Discovery Informatics. Interview by Wendy A. Warr. |
Q48425108 | An interview with Phil Bourne, associate director of the RCSB protein data bank. |
Q52561647 | An investigation into the construction of molecular models by the template joining method. |
Q99366569 | An online repository of solvation thermodynamic and structural maps of SARS-CoV-2 targets |
Q35029371 | An overview of the diversity represented in commercially-available databases |
Q33470339 | Analysis and use of fragment-occurrence data in similarity-based virtual screening |
Q30332646 | Analysis methods for identifying coordinated movements during ligand unbinding. |
Q78057597 | Analysis of Fas-ligand interactions using a molecular model of the receptor-ligand interface |
Q43078853 | Analysis of SM8 and Zap TK calculations and their geometric sensitivity |
Q51070510 | Analysis of stacking overlap in nucleic acid structures: algorithm and application. |
Q46947386 | Analysis of the activation mechanism of the guinea-pig Histamine H1-receptor |
Q45901560 | Annular tautomerism: experimental observations and quantum mechanics calculations. |
Q48113143 | Antagonist-perturbation mechanism for activation function-2 fixed motifs: active conformation and docking mode of retinoid X receptor antagonists |
Q91596914 | Anti-malarial, cytotoxicity and molecular docking studies of quinolinyl chalcones as potential anti-malarial agent |
Q72933435 | Antifungal triazole alcohols: a comparative analysis of structure-activity, structure-teratogenicity and structure-therapeutic index relationships using the Multiple Computer-Automated Structure Evaluation (Multi-CASE) methodology |
Q44087620 | Antimalarial activity of synthetic 1,2,4-trioxanes and cyclic peroxy ketals, a quantum similarity study |
Q44319409 | Antioxidant properties of phenolic Schiff bases: structure-activity relationship and mechanism of action. |
Q37368872 | Antitumor agents 252. Application of validated QSAR models to database mining: discovery of novel tylophorine derivatives as potential anticancer agents |
Q86310322 | App-etite for change |
Q91538152 | Applicability of a thermodynamic cycle approach for a force field parametrization targeting non-aqueous solvation free energies |
Q41515537 | Application of a simple quantum chemical approach to ligand fragment scoring for Trypanosoma brucei pteridine reductase 1 inhibition |
Q51939686 | Application of artificial neural networks and DFT-based parameters for prediction of reaction kinetics of ethylbenzene dehydrogenase. |
Q30585010 | Application of multivariate data analysis methods to comparative molecular field analysis (CoMFA) data: proton affinities and pKa prediction for nucleic acids components |
Q68049865 | Application of semi-empirical and ab initio quantum mechanical calculations |
Q54580789 | Application of shape-based and pharmacophore-based in silico screens for identification of Type II protein kinase inhibitors. |
Q100694740 | Application of target repositioning and in silico screening to exploit fatty acid binding proteins (FABPs) from Echinococcus multilocularis as possible drug targets |
Q90865437 | Application of the 3D-RISM-KH molecular solvation theory for DMSO as solvent |
Q70790876 | Applications of momentum-space similarity |
Q43883717 | Applications of rule-induction in the derivation of quantitative structure-activity relationships |
Q51023570 | Applying forces to elastic network models of large biomolecules using a haptic feedback device. |
Q44178393 | Approaching the 5-HT₃ receptor heterogeneity by computational studies of the transmembrane and intracellular domains |
Q83199715 | Are predefined decoy sets of ligand poses able to quantify scoring function accuracy? |
Q95938036 | Artificial intelligence in chemistry and drug design |
Q33519580 | Artificial neural network study on organ-targeting peptides |
Q47922804 | As-Rigid-As-Possible molecular interpolation paths |
Q46720946 | Asp746 to glycine change may have a greater influence than Cys751 to serine change in accounting for ligand selectivity between EGFR and HER-2 at the ATP site |
Q46321399 | Aspects of the mechanism of catalysis of glucose oxidase: a docking, molecular mechanics and quantum chemical study |
Q90442960 | Assessing and improving the performance of consensus docking strategies using the DockBox package |
Q48113134 | Assessing protein-ligand binding modes with computational tools: the case of PDE4B. |
Q89928274 | Assessing the accuracy of octanol-water partition coefficient predictions in the SAMPL6 Part II log P Challenge |
Q53423422 | Assessing the lipophilicity of fragments and early hits. |
Q91917408 | Assessing the performance of three resveratrol in binding with SIRT1 by molecular dynamics simulation and MM/GBSA methods: the weakest binding of resveratrol 3 to SIRT1 triggers a possibility of dissociation from its binding site |
Q55037679 | Assessing the stability of free-energy perturbation calculations by performing variations in the method. |
Q47696423 | Assessment of tautomer distribution using the condensed reaction graph approach. |
Q86295911 | Assessment of the tautomeric population of benzimidazole derivatives in solution: a simple and versatile theoretical-experimental approach |
Q47698531 | Assessment of uncertainty in chemical models by Bayesian probabilities: Why, when, how? |
Q46703807 | Association of cytochrome P450 enzymes is a determining factor in their catalytic activity |
Q31044283 | Association of transmembrane helices: what determines assembling of a dimer? |
Q31147673 | AstexViewer: a visualisation aid for structure-based drug design |
Q34338177 | AtlasCBS: a web server to map and explore chemico-biological space. |
Q89691238 | Atomistic computer simulations on multi-loaded PAMAM dendrimers: a comparison of amine- and hydroxyl-terminated dendrimers |
Q92720683 | Atomistic insight into sequence-directed DNA bending and minicircle formation propensity in the absence and presence of phased A-tracts |
Q38782136 | Atomistic lattice simulation of high Tc oxides |
Q39354173 | Autocorrelation descriptor improvements for QSAR: 2DA_Sign and 3DA_Sign |
Q82277218 | Automated QSPR through Competitive Workflow |
Q33797738 | Automated clustering of probe molecules from solvent mapping of protein surfaces: new algorithms applied to hot-spot mapping and structure-based drug design. |
Q47921236 | Automated computational screening of the thiol reactivity of substituted alkenes. |
Q52473270 | Automated conformational analysis: algorithms for the efficient construction of low-energy conformations. |
Q57966457 | Automated docking and molecular dynamics simulations of nimesulide in the cyclooxygenase active site of human prostaglandin-endoperoxide synthase-2 (COX-2) |
Q78057582 | Automated docking of 82 N-benzylpiperidine derivatives to mouse acetylcholinesterase and comparative molecular field analysis with 'natural' alignment |
Q57976077 | Automated docking of ligands to an artificial active site: augmenting crystallographic analysis with computer modeling |
Q52376640 | Automated molecular design: a new fragment-joining algorithm. |
Q44823868 | Automated molecule editing in molecular design |
Q67558783 | Automated site-directed drug design: an assessment of the transferability of atomic residual charges (CNDO) for molecular fragments |
Q52482964 | Automated site-directed drug design: approaches to the formation of 3D molecular graphs. |
Q67558781 | Automated site-directed drug design: searches of the Cambridge Structural Database for bond lengths in molecular fragments to be used for automated structure assembly |
Q67558780 | Automated site-directed drug design: the generation of a basic set of fragments to be used for automated structure assembly |
Q45964726 | Automatic QSAR modeling of ADME properties: blood-brain barrier penetration and aqueous solubility. |
Q52482973 | Automatic log P estimation based on combined additive modeling methods. |
Q68274966 | Automatic search for maximum similarity between molecular electrostatic potential distributions |
Q67976698 | Automatic superposition of drug molecules based on their common receptor site |
Q35803775 | Avalanche for shape and feature-based virtual screening with 3D alignment. |
Q36109714 | Azahar: a PyMOL plugin for construction, visualization and analysis of glycan molecules |
Q28296578 | BALLView: an object-oriented molecular visualization and modeling framework |
Q92899539 | BCL::Mol2D-a robust atom environment descriptor for QSAR modeling and lead optimization |
Q36801376 | BEDAM binding free energy predictions for the SAMPL4 octa-acid host challenge. |
Q51979864 | BODIL: a molecular modeling environment for structure-function analysis and drug design. |
Q90865429 | BRADSHAW: a system for automated molecular design |
Q33251138 | BRUTUS: optimization of a grid-based similarity function for rigid-body molecular superposition. II. Description and characterization |
Q46836531 | BUILDER v.2: improving the chemistry of a de novo design strategy |
Q47742352 | BUNDLE: a program for building the transmembrane domains of G-protein-coupled receptors |
Q33260987 | Balancing focused combinatorial libraries based on multiple GPCR ligands |
Q36303825 | Bayesian molecular design with a chemical language model. |
Q98184691 | Benchmarking GPCR homology model template selection in combination with de novo loop generation |
Q112570463 | Benchmarking ensemble docking methods in D3R Grand Challenge 4 |
Q98772844 | Benchmarking the performance of MM/PBSA in virtual screening enrichment using the GPCR-Bench dataset |
Q30620538 | Benefits of statistical molecular design, covariance analysis, and reference models in QSAR: a case study on acetylcholinesterase |
Q44711416 | Benzimidazole derivatives. 4. The recognition of the voluminous substituent attached to the basic amino group of 5-HT4 receptor antagonists |
Q114863710 | Best practices for repurposing studies |
Q42639520 | Bias, reporting, and sharing: computational evaluations of docking methods |
Q53076305 | Biased retrieval of chemical series in receptor-based virtual screening. |
Q28654673 | Bigger data, collaborative tools and the future of predictive drug discovery |
Q56975687 | Binding affinities in the SAMPL3 trypsin and host–guest blind tests estimated with the MM/PBSA and LIE methods |
Q48023567 | Binding affinities of the farnesoid X receptor in the D3R Grand Challenge 2 estimated by free-energy perturbation and docking. |
Q38302840 | Binding energy calculations for hevein-carbohydrate interactions using expanded ensemble molecular dynamics simulations. |
Q114226105 | Binding free energies for the SAMPL8 CB8 “Drugs of Abuse” challenge from umbrella sampling combined with Hamiltonian replica exchange |
Q37588656 | Binding free energies in the SAMPL5 octa-acid host-guest challenge calculated with DFT-D3 and CCSD(T). |
Q91376128 | Binding free energies in the SAMPL6 octa-acid host-guest challenge calculated with MM and QM methods |
Q59539663 | Binding free energy calculations to rationalize the interactions of huprines with acetylcholinesterase |
Q47827032 | Binding free energy predictions of farnesoid X receptor (FXR) agonists using a linear interaction energy (LIE) approach with reliability estimation: application to the D3R Grand Challenge 2. |
Q48057664 | Binding mode prediction and MD/MMPBSA-based free energy ranking for agonists of REV-ERBα/NCoR. |
Q50622600 | Binding mode similarity measures for ranking of docking poses: a case study on the adenosine A2A receptor. |
Q44490732 | Binding models of reversible inhibitors to type-B monoamine oxidase |
Q44667605 | Binding of alpha-hydroxy-beta-amino acid inhibitors to methionine aminopeptidase. The performance of two types of scoring functions |
Q41521138 | Binding of carboxylate and trimethylammonium salts to octa-acid and TEMOA deep-cavity cavitands |
Q33599960 | Binding of cyclic carboxylates to octa-acid deep-cavity cavitand |
Q85037178 | Binding of novel fullerene inhibitors to HIV-1 protease: insight through molecular dynamics and molecular mechanics Poisson-Boltzmann surface area calculations |
Q54413507 | Binding of the Zn2+ ion to ferric uptake regulation protein from E. coli and the competition with Fe2+ binding: a molecular modeling study of the effect on DNA binding and conformational changes of Fur. |
Q47659739 | Binding pose and affinity prediction in the 2016 D3R Grand Challenge 2 using the Wilma-SIE method |
Q37363075 | Binding-affinity predictions of HSP90 in the D3R Grand Challenge 2015 with docking, MM/GBSA, QM/MM, and free-energy simulations |
Q72069925 | Bioactive design: forward to new frontiers |
Q47391842 | Bioactive focus in conformational ensembles: a pluralistic approach |
Q48012449 | Biologically relevant conformational features of linear and cyclic proteolipid protein (PLP) peptide analogues obtained by high-resolution nuclear magnetic resonance and molecular dynamics. |
Q51277956 | Biomacromolecular quantitative structure-activity relationship (BioQSAR): a proof-of-concept study on the modeling, prediction and interpretation of protein-protein binding affinity. |
Q90101459 | Biomolecular force fields: where have we been, where are we now, where do we need to go and how do we get there? |
Q33601586 | Biophysical approaches to G protein-coupled receptors: structure, function and dynamics |
Q33928781 | Biosensor-based small molecule fragment screening with biolayer interferometry. |
Q26864619 | Blind prediction of HIV integrase binding from the SAMPL4 challenge |
Q40579705 | Blind prediction of SAMPL4 cucurbit[7]uril binding affinities with the mining minima method |
Q34541312 | Blind prediction of cyclohexane-water distribution coefficients from the SAMPL5 challenge |
Q48054550 | Blind prediction of distribution in the SAMPL5 challenge with QM based protomer and pK a corrections |
Q34257034 | Blind prediction of host-guest binding affinities: a new SAMPL3 challenge. |
Q34409381 | Blind prediction of solvation free energies from the SAMPL4 challenge. |
Q57829052 | Blind prediction test of free energies of hydration with COSMO-RS |
Q91396118 | Blinded evaluation of cathepsin S inhibitors from the D3RGC3 dataset using molecular docking and free energy calculations |
Q38597033 | Blinded evaluation of farnesoid X receptor (FXR) ligands binding using molecular docking and free energy calculations. |
Q90295745 | Blinded prediction of protein-ligand binding affinity using Amber thermodynamic integration for the 2018 D3R grand challenge 4 |
Q28818251 | Blinded predictions of distribution coefficients in the SAMPL5 challenge |
Q39509919 | Blinded predictions of host-guest standard free energies of binding in the SAMPL5 challenge |
Q91216246 | Blinded predictions of standard binding free energies: lessons learned from the SAMPL6 challenge |
Q31146521 | Blowing a breath of fresh share on data |
Q40775428 | Boltzmann's principle, knowledge-based mean fields and protein folding. An approach to the computational determination of protein structures |
Q56985169 | Bond-based 2D TOMOCOMD-CARDD approach for drug discovery: aiding decision-making in ‘in silico’ selection of new lead tyrosinase inhibitors |
Q56985185 | Bond-based global and local (bond, group and bond-type) quadratic indices and their applications to computer-aided molecular design. 1. QSPR studies of diverse sets of organic chemicals |
Q33335184 | Bond-based linear indices in QSAR: computational discovery of novel anti-trichomonal compounds. |
Q58114855 | Boosted feature selectors: a case study on prediction P-gp inhibitors and substrates |
Q47622421 | Boosted leave-many-out cross-validation: the effect of training and test set diversity on PLS statistics |
Q47577468 | Box size effects are negligible for solvation free energies of neutral solutes |
Q52427344 | Brownian dynamics simulation of protein association. |
Q30844883 | C-QSAR: a database of 18,000 QSARs and associated biological and physical data |
Q38772488 | CADD medicine: design is the potion that can cure my disease |
Q33350494 | CAL3JHH: a Java program to calculate the vicinal coupling constants (3J H,H) of organic molecules |
Q73604209 | CAMDAS: an automated conformational analysis system using molecular dynamics. Conformational Analyzer with Molecular Dynamics And Sampling |
Q46602190 | CAVEAT: a program to facilitate the design of organic molecules |
Q46022295 | CCDC well groomed: an interview with Colin Groom, Executive Director, Cambridge Crystallographic Data Centre, and Frank Allen, Emeritus Fellow. |
Q47694932 | CDOCKER and λ-dynamics for prospective prediction in D₃R Grand Challenge 2. |
Q68559277 | CGEMA and VGAP: a Colour Graphics Editor for Multiple Alignment using a variable GAP penalty. Application to the muscarinic acetylcholine receptor |
Q33350276 | CONFIRM: connecting fragments found in receptor molecules |
Q71851446 | CORCEMA evaluation of the potential role of intermolecular transferred NOESY in the characterization of ligand-receptor complexes |
Q67822568 | COSMIC(90): An improved molecular mechanics treatment of hydrocarbons and conjugated systems |
Q91480962 | COSMO-RS based predictions for the SAMPL6 logP challenge |
Q48882491 | COSMO-RS: a novel view to physiological solvation and partition questions. |
Q51924209 | Caco-2 cell permeability modelling: a neural network coupled genetic algorithm approach. |
Q91459326 | Calculate protein-ligand binding affinities with the extended linear interaction energy method: application on the Cathepsin S set in the D3R Grand Challenge 3 |
Q57397675 | Calculating distribution coefficients based on multi-scale free energy simulations: an evaluation of MM and QM/MM explicit solvent simulations of water-cyclohexane transfer in the SAMPL5 challenge |
Q51901592 | Calculating physical properties of organic compounds for environmental modeling from molecular structure. |
Q30668824 | Calculating the knowledge-based similarity of functional groups using crystallographic data |
Q36120306 | Calculation of distribution coefficients in the SAMPL5 challenge from atomic solvation parameters and surface areas |
Q70790866 | Calculation of hydrophobic parameters directly from three-dimensional structures using comparative molecular field analysis |
Q71483770 | Calculation of solvation and binding free energy differences between VX-478 and its analogs by free energy perturbation and AMSOL methods |
Q51914537 | Calculations of protein-ligand binding entropy of relative and overall molecular motions. |
Q41958908 | Calibrative approaches to protein solubility modeling of a mutant series using physicochemical descriptors |
Q51311642 | Call for Papers: GRC, CADD, and statistics, and all that. |
Q94466096 | Can free energy calculations be fast and accurate at the same time? Binding of low-affinity, non-peptide inhibitors to the SH2 domain of the src protein |
Q51309798 | Can topological indices transmit information on properties but not on structures? |
Q82908096 | Can we really do computer-aided drug design? |
Q52942162 | Can we separate active from inactive conformations? |
Q80467476 | Can we use docking and scoring for hit-to-lead optimization? |
Q57357387 | Cannabinoid CB1 receptor recognition of endocannabinoids via the lipid bilayer: molecular dynamics simulations of CB1 transmembrane helix 6 and anandamide in a phospholipid bilayer |
Q44064526 | Carboxylator: incorporating solvent-accessible surface area for identifying protein carboxylation sites |
Q45092503 | Cardio-vascular safety beyond hERG: in silico modelling of a guinea pig right atrium assay |
Q41872137 | Catalytic residues in hydrolases: analysis of methods designed for ligand-binding site prediction |
Q80865396 | Categorical QSAR models for skin sensitization based on local lymph node assay measures and both ground and excited state 4D-fingerprint descriptors |
Q52467410 | Cavity search: an algorithm for the isolation and display of cavity-like binding regions. |
Q33384498 | ChEMBL. An interview with John Overington, team leader, chemogenomics at the European Bioinformatics Institute Outstation of the European Molecular Biology Laboratory (EMBL-EBI). Interview by Wendy A. Warr |
Q78752864 | Chain melting temperature estimation for phosphatidyl cholines by quantum mechanically derived quantitative structure property relationships |
Q82324123 | Challenges in the determination of the binding modes of non-standard ligands in X-ray crystal complexes |
Q84143317 | Challenges of fragment screening |
Q46627471 | Challenging the gold standard for 3D-QSAR: template CoMFA versus X-ray alignment |
Q36794966 | Characterising the geometric diversity of functional groups in chemical databases |
Q90416615 | Characterization of PD-L1 binding sites by a combined FMO/GRID-DRY approach |
Q85028582 | Characterization of PDZ domain-peptide interactions using an integrated protocol of QM/MM, PB/SA, and CFEA analyses |
Q46630848 | Characterization of beta3-adrenergic receptor: determination of pharmacophore and 3D QSAR model for beta3 adrenergic receptor agonism. |
Q45902527 | Characterization of dipeptidylcarboxypeptidase of Leishmania donovani: a molecular model for structure based design of antileishmanials. |
Q57138096 | Characterization of low-energy conformational domains for Met-enkephalin |
Q69724842 | Charge calculations in molecular mechanics 7: application to polar pi systems incorporating nitro, cyano, amino, C=S and thio substituents |
Q68034485 | Charge calculations in molecular mechanics. IX. A general parameterisation of the scheme for saturated halogen, oxygen and nitrogen compounds |
Q70232998 | Charge calculations in molecular mechanics. Part 8. Partial atomic charges from classical calculations |
Q34019261 | Charge density distributions derived from smoothed electrostatic potential functions: design of protein reduced point charge models |
Q74505235 | Charge distribution from a simple molecular orbital type calculation and non-bonding interaction terms in the force field MAB |
Q44109237 | Charge-transfer interactions in the inhibition of MAO-A by phenylisopropylamines--a QSAR study. |
Q33392980 | ChemGPS-NP(Web): chemical space navigation online |
Q44202556 | ChemStable: a web server for rule-embedded naïve Bayesian learning approach to predict compound stability |
Q35453774 | Chemical and protein structural basis for biological crosstalk between PPARα and COX enzymes |
Q51079623 | Chemical space networks: a powerful new paradigm for the description of chemical space. |
Q51703673 | Chemical space sampling by different scoring functions and crystal structures. |
Q34380828 | Cheminformatics aspects of high throughput screening: from robots to models: symposium summary |
Q90433622 | Chemistry, information and Frank: a tribute to Frank Brown |
Q30875895 | Chemoinformatics methods for systematic comparison of molecules from natural and synthetic sources and design of hybrid libraries |
Q52373578 | Chemometric QSAR studies of antifungal azoxy compounds. |
Q53914324 | Chemometric rationalization of the structural and physicochemical basis for selective cyclooxygenase-2 inhibition: toward more specific ligands. |
Q70661457 | Chiral chromatography and multivariate quantitative structure-property relationships of benzimidazole sulphoxides |
Q57250693 | Class IV charge models: A new semiempirical approach in quantum chemistry |
Q73013892 | Classical QSAR and comparative molecular field analyses of the host-guest interaction of organic molecules with cyclodextrins |
Q47622495 | Classification of HIV protease inhibitors on the basis of their antiviral potency using radial basis function neural networks |
Q30983472 | Classification of a large anticancer data set by adaptive fuzzy partition |
Q74505239 | Classification of auxin plant hormones by interaction property similarity indices |
Q52061314 | Classification of protein disulphide-bridge topologies. |
Q30952694 | Classification scheme for the design of serine protease targeted compound libraries |
Q50181313 | ClogP(alk): a method for predicting alkane/water partition coefficient. |
Q44670603 | Close intramolecular sulfur-oxygen contacts: modified force field parameters for improved conformation generation |
Q33449492 | Closing the side-chain gap in protein loop modeling |
Q47717539 | Co-operative intra-protein structural response due to protein-protein complexation revealed through thermodynamic quantification: study of MDM2-p53 binding. |
Q31033965 | CoMFA and CoMSIA 3D-quantitative structure-activity relationship model on benzodiazepine derivatives, inhibitors of phosphodiesterase IV. |
Q44667595 | CoMFA and docking study of novel estrogen receptor subtype selective ligands |
Q52545360 | CoMFA validation of the superposition of six classes of compounds which block GABA receptors non-competitively. |
Q32058642 | CoMFA-based comparison of two models of binding site on adenosine A1 receptor. |
Q48006451 | Collaborating to improve the use of free-energy and other quantitative methods in drug discovery. |
Q48455544 | Collaboration, competition, validation and plans for the future : an interview with Gerard Kleywegt, Head of the Protein Data Bank in Europe. Interviewed by Wendy A Warr. |
Q31939358 | CombiDOCK: structure-based combinatorial docking and library design |
Q30628860 | Combinatorial docking and combinatorial chemistry: design of potent non-peptide thrombin inhibitors |
Q33481042 | Combinatorial library-based design with Basis Products |
Q33548819 | Combinatorial-computational-chemoinformatics (C3) approach to finding and analyzing low-energy tautomers. |
Q43724449 | Combined QSAR and molecule docking studies on predicting P-glycoprotein inhibitors |
Q100949808 | Combined experimental and quantum mechanical elucidation of the synthetically accessible stereoisomers of Hydroxyestradienone (HED), the starting material for vilaprisan synthesis |
Q39489949 | Combined use of pharmacophoric models together with drug metabolism and genotoxicity "in silico" studies in the hit finding process. |
Q38993439 | Combining MOSCED with molecular simulation free energy calculations or electronic structure calculations to develop an efficient tool for solvent formulation and selection |
Q30778906 | Combining NMR spectral and structural data to form models of polychlorinated dibenzodioxins, dibenzofurans, and biphenyls binding to the AhR. |
Q84615371 | Combining conformational sampling and selection to identify the binding mode of zinc-bound amyloid peptides with bifunctional molecules |
Q40959163 | Combining docking-based comparative intermolecular contacts analysis and k-nearest neighbor correlation for the discovery of new check point kinase 1 inhibitors |
Q100505466 | Combining fragment docking with graph theory to improve ligand docking for homology model structures |
Q47809580 | Combining fragment homology modeling with molecular dynamics aims at prediction of Ca²⁺ binding sites in CaBPs |
Q42242201 | Combining in silico and in cerebro approaches for virtual screening and pose prediction in SAMPL4. |
Q51410824 | Combining molecular dynamics simulation and ligand-receptor contacts analysis as a new approach for pharmacophore modeling: beta-secretase 1 and check point kinase 1 as case studies. |
Q38608749 | Combining self- and cross-docking as benchmark tools: the performance of DockBench in the D3R Grand Challenge 2. |
Q44225818 | Common prevalence of alanine and glycine in mobile reactive centre loops of serpins and viral fusion peptides: do prions possess a fusion peptide? |
Q28268675 | Community benchmarks for virtual screening |
Q79660689 | Comparative QSAR studies on PAMPA/modified PAMPA for high throughput profiling of drug absorption potential with respect to Caco-2 cells and human intestinal absorption |
Q79356133 | Comparative and pharmacophore model for deacetylase SIRT1 |
Q57966471 | Comparative binding energy analysis |
Q40547496 | Comparative binding energy analysis of haloalkane dehalogenase substrates: modelling of enzyme-substrate complexes by molecular docking and quantum mechanical calculations. |
Q67865141 | Comparative conformational analysis of [D-Pen2,D-Pen5]enkephalin (DPDPE): a molecular mechanics study |
Q71699017 | Comparative docking studies on ligand binding to the multispecific antibodies IgE-La2 and IgE-Lb4 |
Q45391940 | Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) of thiazolone derivatives as hepatitis C virus NS5B polymerase allosteric inhibitors |
Q52067622 | Comparative molecular field analysis (coMFA) study of epothilones-tubulin depolymerization inhibitors: pharmacophore development using 3D QSAR methods. |
Q77365335 | Comparative molecular field analysis and energy interaction studies of thrombin-inhibitor complexes |
Q73315113 | Comparative molecular field analysis and molecular modeling studies of 20-(S)-camptothecin analogs as inhibitors of DNA topoisomerase I and anticancer/antitumor agents |
Q45046460 | Comparative molecular field analysis of CCK-A antagonists using field-fit as an alignment technique. A convenient guide to design new CCK-A ligands |
Q77428769 | Comparative molecular field analysis of artemisinin derivatives: ab initio versus semiempirical optimized structures |
Q71483792 | Comparative molecular field analysis of non-steroidal aromatase inhibitors related to fadrozole |
Q56622993 | Comparative molecular modelling study of the calcium channel blockers nifedipine and black mamba toxin FS2 |
Q30656455 | Comparative molecular similarity index analysis (CoMSIA) to study hydrogen-bonding properties and to score combinatorial libraries |
Q74274396 | Comparative receptor mapping of serotoninergic 5-HT3 and 5-HT4 binding sites |
Q79158020 | Comparative residue interaction analysis (CoRIA): a 3D-QSAR approach to explore the binding contributions of active site residues with ligands |
Q39545851 | Comparative review of molecular modelling software for personal computers |
Q33201269 | Comparative study of several algorithms for flexible ligand docking |
Q79846741 | Comparative study of the prereactive protein kinase A Michaelis complex with kemptide substrate |
Q33515060 | Comparative virtual screening and novelty detection for NMDA-GlycineB antagonists |
Q47631131 | Comparing pharmacophore models derived from crystallography and NMR ensembles |
Q53075202 | Comparing the performance of meta-classifiers-a case study on selected imbalanced data sets relevant for prediction of liver toxicity. |
Q74835547 | Comparison of 3D quantitative structure-activity relationship methods: analysis of the in vitro antimalarial activity of 154 artemisinin analogues by hypothetical active-site lattice and comparative molecular field analysis |
Q52650065 | Comparison of a 3D-model of the classical alpha-scorpion toxin V from Leiurus quinquestriatus quinquestriatus with other scorpion toxins. |
Q79750135 | Comparison of a homology model and the crystallographic structure of human 11beta-hydroxysteroid dehydrogenase type 1 (11betaHSD1) in a structure-based identification of inhibitors |
Q91135908 | Comparison of affinity ranking using AutoDock-GPU and MM-GBSA scores for BACE-1 inhibitors in the D3R Grand Challenge 4 |
Q77365338 | Comparison of azacyclic urea A-98881 as HIV-1 protease inhibitor with cage dimeric N-benzyl 4-(4-methoxyphenyl)-1,4-dihydropyridine as representative of a novel class of HIV-1 protease inhibitors: a molecular modeling study |
Q85323813 | Comparison of bioactive chemical space networks generated using substructure- and fingerprint-based measures of molecular similarity |
Q81437638 | Comparison of commercially available genetic algorithms: gas as variable selection tool |
Q64112563 | Comparison of conformer distributions in the crystalline state with conformational energies calculated by ab initio techniques |
Q51999968 | Comparison of correlation vector methods for ligand-based similarity searching. |
Q44343648 | Comparison of cyclic delta-opioid peptides with non-peptide delta-agonist spiroindanyloxymorphone (SIOM) using the message-address concept: a molecular modeling study |
Q40867870 | Comparison of protein surfaces using a genetic algorithm |
Q39909719 | Comparison of structure fingerprint and molecular interaction field based methods in explaining biological similarity of small molecules in cell-based screens |
Q64111812 | Comparison of substructural epitopes in enzyme active sites using self-organizing maps |
Q70280723 | Comparison of the X-ray structure of baboon alpha-lactalbumin and the tertiary predicted computer models of human alpha-lactalbumin |
Q57463686 | Comparison of the umbrella sampling and the double decoupling method in binding free energy predictions for SAMPL6 octa-acid host-guest challenges |
Q35168275 | Comparison of three GPCR structural templates for modeling of the P2Y12 nucleotide receptor |
Q52220779 | Comparison of two implementations of the incremental construction algorithm in flexible docking of thrombin inhibitors. |
Q39248121 | Compilation and physicochemical classification analysis of a diverse hERG inhibition database |
Q64900233 | Complex macrocycle exploration: parallel, heuristic, and constraint-based conformer generation using ForceGen. |
Q43853536 | Composite multi-parameter ranking of real and virtual compounds for design of MC4R agonists: renaissance of the Free-Wilson methodology |
Q54494731 | Comprehensive model of wild-type and mutant HIV-1 reverse transciptases. |
Q51615421 | Computation of 3D queries for ROCS based virtual screens. |
Q47742338 | Computation of affinity and selectivity: binding of 2,4-diaminopteridine and 2,4-diaminoquinazoline inhibitors to dihydrofolate reductases |
Q39551290 | Computation of relative binding free energy for an inhibitor and its analogs binding with Erk kinase using thermodynamic integration MD simulation. |
Q51655176 | Computation space. |
Q51604799 | Computation, experiment and molecular design. |
Q39743323 | Computational analysis of EBNA1 "druggability" suggests novel insights for Epstein-Barr virus inhibitor design |
Q70984340 | Computational analysis of binding affinity and neural response at the L-alanine receptor |
Q30562222 | Computational analysis of local membrane properties |
Q35589799 | Computational and biophysical approaches to protein-protein interaction inhibition of Plasmodium falciparum AMA1/RON2 complex. |
Q36104862 | Computational and experimental studies of the interaction between phospho-peptides and the C-terminal domain of BRCA1. |
Q38829916 | Computational approaches for predicting mutant protein stability |
Q50973091 | Computational assessment of synthetic procedures. |
Q53608885 | Computational atomistic blueprinting of novel conducting copolymers using particle swarm optimization. |
Q39676642 | Computational chemistry and cheminformatics: an essay on the future |
Q89020557 | Computational chemistry at Janssen |
Q46294568 | Computational chemistry in 25 years |
Q39686921 | Computational chemistry in pharmaceutical research: at the crossroads |
Q30361816 | Computational chemogenomics: is it more than inductive transfer? |
Q52418847 | Computational combinatorial ligand design: application to human alpha-thrombin. |
Q52083095 | Computational design of D-peptide inhibitors of hepatitis delta antigen dimerization. |
Q43016539 | Computational design of a Diels-Alderase from a thermophilic esterase: the importance of dynamics. |
Q47778490 | Computational design of bio-inspired carnosine-based HOBr antioxidants |
Q91624909 | Computational design, synthesis and evaluation of new sulphonamide derivatives targeting HIV-1 gp120 |
Q47957502 | Computational discovery of putative quorum sensing inhibitors against LasR and RhlR receptor proteins of Pseudomonas aeruginosa |
Q38299764 | Computational docking simulations of a DNA-aptamer for argininamide and related ligands. |
Q96128888 | Computational exploration and experimental validation to identify a dual inhibitor of cholinesterase and amyloid-beta for the treatment of Alzheimer's disease |
Q33469692 | Computational fragment-based drug design to explore the hydrophobic sub-pocket of the mitotic kinesin Eg5 allosteric binding site |
Q34127928 | Computational fragment-based screening using RosettaLigand: the SAMPL3 challenge |
Q33408994 | Computational identification of epitopes in the glycoproteins of novel bunyavirus (SFTS virus) recognized by a human monoclonal antibody (MAb 4-5). |
Q40212184 | Computational insights into the interaction mechanism of triazolyl substituted tetrahydrobenzofuran derivatives with H(+),K(+)-ATPase at different pH. |
Q90474289 | Computational insights into the molecular mechanisms of differentiated allosteric modulation at the mu opioid receptor by structurally similar bitopic modulators |
Q39506214 | Computational insights into the selectivity mechanism of APP-IP over matrix metalloproteinases |
Q84711500 | Computational investigation of the binding mode of bis(hydroxylphenyl)arenes in 17β-HSD1: molecular dynamics simulations, MM-PBSA free energy calculations, and molecular electrostatic potential maps |
Q90814692 | Computational methods and tools for binding site recognition between proteins and small molecules: from classical geometrical approaches to modern machine learning strategies |
Q33886274 | Computational methods for the structural alignment of molecules |
Q34126654 | Computational model of the complex between GR113808 and the 5-HT4 receptor guided by site-directed mutagenesis and the crystal structure of rhodopsin |
Q47442677 | Computational modeling and in-vitro/in-silico correlation of phospholipid-based prodrugs for targeted drug delivery in inflammatory bowel disease. |
Q79883949 | Computational models to predict blood-brain barrier permeation and CNS activity |
Q36624603 | Computational photochemistry of retinal proteins |
Q42107457 | Computational prediction of ion permeation characteristics in the glycine receptor modified by photo-sensitive compounds |
Q44245923 | Computational prediction of kink properties of helices in membrane proteins. |
Q36297180 | Computational simulations of the conformational behaviour of the adhesive proteins RGDS fragment |
Q46703802 | Computational studies and drug design for HIV-1 reverse transcriptase inhibitors of 3',4'-di-O-(S)-camphanoyl-(+)-cis-khellactone (DCK) analogs |
Q47972915 | Computational studies of new potential antimalarial compounds--stereoelectronic complementarity with the receptor |
Q33560786 | Computational studies on the interaction of ABO-active saccharides with the norovirus VA387 capsid protein can explain experimental binding data |
Q43734813 | Computational study of elements of stability of a four-helix bundle protein biosurfactant. |
Q31080420 | Computational study of pH-dependent oligomerization and ligand binding in Alt a 1, a highly allergenic protein with a unique fold |
Q44167541 | Computational study of the catalytic domain of human neutrophil collagenase. specific role of the S3 and S'3 subsites in the interaction with a phosphonate inhibitor. |
Q85651591 | Computational study of the effects of protein tyrosine nitrations on the catalytic activity of human thymidylate synthase |
Q51823568 | Computational study of the heterodimerization between mu and delta receptors. |
Q37503295 | Computational study of the inhibitory mechanism of the kinase CDK5 hyperactivity by peptide p5 and derivation of a pharmacophore |
Q38296034 | Computational study on mechanism of G-quartet oligonucleotide T40214 selectively targeting Stat3. |
Q45250354 | Computational study on the molecular inclusion of andrographolide by cyclodextrin. |
Q52482980 | Computer Automated Structure Evaluation (CASE) of the teratogenicity of retinoids with the aid of a novel geometry index. |
Q43704069 | Computer based screening of compound databases: 1. Preselection of benzamidine-based thrombin inhibitors |
Q68846659 | Computer graphic study on models of the molybdenum cofactor of xanthine oxidase |
Q41212308 | Computer modelling: future directions |
Q30360045 | Computer simulation of biological interactions and reactivity. |
Q38782190 | Computer simulation of liquid crystals |
Q38359548 | Computer simulation of the binding of amonafide and azonafide to DNA. |
Q42210671 | Computer simulation of the binding of quinocarcin to DNA. Prediction of mode of action and absolute configuration |
Q69601244 | Computer simulation of the conformational behavior of cholecystokinin fragments: conformational families of sulfated CCK8 |
Q68121898 | Computer simulation of the conformational behaviour of angiotensinogen (6-13) renin substrate |
Q43490687 | Computer simulation study of the binding of an antiviral agent to a sensitive and a resistant human rhinovirus |
Q69844592 | Computer simulations in zeolite chemistry |
Q45105290 | Computer-aided active-site-directed modeling of the herpes simplex virus 1 and human thymidine kinase |
Q74097068 | Computer-aided design and activity prediction of leucine aminopeptidase inhibitors |
Q51393402 | Computer-aided design of novel antibacterial 3-hydroxypyridine-4-ones: application of QSAR methods based on the MOLMAP approach. |
Q48344517 | Computer-aided drug design at Boehringer Ingelheim. |
Q82324131 | Computer-aided drug design platform using PyMOL |
Q72741860 | Computer-aided drug design: a free energy perturbation study on the binding of methyl-substituted pterins and N5-deazapterins to dihydrofolate reductase |
Q28256647 | Computer-aided drug design: the next 20 years |
Q57074609 | Computer-aided drug discovery and design |
Q36179855 | Computer-aided drug discovery research at a global contract research organization |
Q50506096 | Computer-aided molecular design under the SWOTlight. |
Q68121893 | Computer-aided molecular modeling and design of DNA-inserting molecules |
Q41448933 | Computer-aided molecular modeling of a D2-agonist dopamine pharmacophore. |
Q41265612 | Computer-aided molecular modelling: research study or research tool? |
Q34348773 | Computer-aided structure-affinity relationships in a set of piperazine and 3,8-diazabicyclo[3.2.1]octane derivatives binding to the mu-opioid receptor |
Q33748641 | Computer-assisted combinatorial design of bicyclic thymidine analogs as inhibitors of Mycobacterium tuberculosis thymidine monophosphate kinase. |
Q84562022 | Computer-assisted study on the reaction between pyruvate and ylide in the pathway leading to lactyl-ThDP |
Q24289469 | Confidence limits, error bars and method comparison in molecular modeling. Part 1: the calculation of confidence intervals |
Q39116494 | Confidence limits, error bars and method comparison in molecular modeling. Part 2: comparing methods |
Q67941473 | Conformation of receptor-associated PGI2: an investigation by molecular modeling |
Q34560835 | Conformation-activity relationships of opiate analgesics |
Q68171365 | Conformational analyses on histamine H2-receptor antagonists |
Q47742296 | Conformational analysis of [Met5]-enkephalin: solvation and ionization considerations |
Q57135526 | Conformational analysis of a farnesyltransferase peptide inhibitor, CVIM |
Q43805835 | Conformational analysis of kainate in aqueous solution in relation to its binding to AMPA and kainic acid receptors |
Q92829689 | Conformational analysis of macrocycles: comparing general and specialized methods |
Q46467177 | Conformational analysis of methylphenidate: comparison of molecular orbital and molecular mechanics methods |
Q43979142 | Conformational analysis of nevirapine, a non-nucleoside HIV-1 reverse transcriptase inhibitor, based on quantum mechanical calculations |
Q62648702 | Conformational analysis of six- and twelve-membered ring compounds by molecular dynamics |
Q84904047 | Conformational analysis of the ΜΒΡ83-99 (Phe91) and ΜΒΡ83-99 (Tyr91) peptide analogues and study of their interactions with the HLA-DR2 and human TCR receptors by using molecular dynamics |
Q38350507 | Conformational analysis of thioglycoside derivatives of histo-blood group ABH antigens using an ab initio-derived reparameterization of MM4: implications for design of non-hydrolysable mimetics |
Q68012967 | Conformational analysis. Part 16. Conformational free energies in substituted piperidines and piperidinium salts |
Q52549169 | Conformational and receptor-binding properties of the insect neuropeptide proctolin and its analogues. |
Q52417441 | Conformational behaviour and molecular similarity of some beta 1-adrenergic ligands |
Q70984336 | Conformational behaviour of the antineoplastic peptide dolastatin-10 and of two mutated derivatives |
Q52351880 | Conformational energy downward driver (CEDD): characterization and calibration of the method. |
Q57136198 | Conformational energy penalties of protein-bound ligands |
Q89484077 | Conformational ensemble comparison for small molecules in drug discovery |
Q40116297 | Conformational flexibility of DENV NS2B/NS3pro: from the inhibitor effect to the serotype influence. |
Q43120311 | Conformational landscape of platinum(II)-tetraamine complexes: DFT and NBO studies |
Q33893624 | Conformational preferences of the potent dopamine reuptake blocker BTCP and its analogs and their incorporation into a pharmacophore model |
Q60459611 | Conformational properties of amphotericin B amide derivatives--impact on selective toxicity |
Q52542613 | Conformational properties of pyrethroids. |
Q52422829 | Conformational search by potential energy annealing: algorithm and application to cyclosporin A. |
Q48083247 | Conformational specificity of non-canonical base pairs and higher order structures in nucleic acids: crystal structure database analysis |
Q57594206 | Conformational studies of immunodominant myelin basic protein 1–11 analogues using NMR and molecular modeling |
Q41116526 | Conformational studies on (+)-anatoxin-a and derivatives |
Q46924588 | Conformational studies on the four stereoisomers of the novel anticholinergic 4-(dimethylamino)-2-phenyl-2-(2-pyridyl)pentanamide |
Q43566216 | Conformational study of insect adipokinetic hormones using NMR constrained molecular dynamics |
Q61326962 | Conformational variety for the ansa chain of rifamycins: comparison of observed crystal structures and molecular dynamics simulations |
Q52401179 | Conformations of large cycloalkanes: cyclooctadecane, cyclononadecane and cycloicosane. |
Q47571750 | Congestion game scheduling for virtual drug screening optimization. |
Q34440071 | Consensus Induced Fit Docking (cIFD): methodology, validation, and application to the discovery of novel Crm1 inhibitors |
Q33530647 | Consensus model for identification of novel PI3K inhibitors in large chemical library |
Q46916180 | Conserved network properties of helical membrane protein structures and its implication for improving membrane protein homology modeling at the twilight zone |
Q37198661 | Considerations and recent advances in QSAR models for cytochrome P450-mediated drug metabolism prediction |
Q52398725 | Constitutional, configurational and conformational analysis of transition metal coordination complexes. |
Q69601237 | Constrained search of conformational hyperspace |
Q42609883 | Construction of 3D models of the CYP11B family as a tool to predict ligand binding characteristics |
Q46758096 | Construction of 4D-QSAR models for use in the design of novel p38-MAPK inhibitors |
Q73331705 | Construction of a full three-dimensional model of the transpeptidase domain of Streptococcus pneumoniae PBP2x starting from its Calpha-atom coordinates |
Q56982829 | Continuous indicator fields: a novel universal type of molecular fields |
Q30457582 | Converging free energies of binding in cucurbit[7]uril and octa-acid host-guest systems from SAMPL4 using expanded ensemble simulations |
Q45945644 | Convex-PL: a novel knowledge-based potential for protein-ligand interactions deduced from structural databases using convex optimization. |
Q89543575 | Convolutional neural network scoring and minimization in the D3R 2017 community challenge |
Q91135888 | Correction to: BRADSHAW: a system for automated molecular design |
Q58558877 | Could the presence of sodium ion influence the accuracy and precision of the ligand-posing in the human A adenosine receptor orthosteric binding site using a molecular docking approach? Insights from Dockbench |
Q45216911 | Count on kappa |
Q52382633 | Coupling constants again: experimental restraints in structure refinement. |
Q91264661 | Coupling enhanced sampling of the apo-receptor with template-based ligand conformers selection: performance in pose prediction in the D3R Grand Challenge 4 |
Q57794478 | Covalent docking of selected boron-based serine beta-lactamase inhibitors |
Q100440524 | Covalent inhibitor reactivity prediction by the electrophilicity index-in and out of scope |
Q35230342 | Creating and virtually screening databases of fluorescently-labelled compounds for the discovery of target-specific molecular probes. |
Q114226104 | Crystal polymorphism and spectroscopical properties of sulfonamides in solid state by means of First Principles calculations |
Q35201628 | Crystal structure of an antiviral ankyrin targeting the HIV-1 capsid and molecular modeling of the ankyrin-capsid complex |
Q39621578 | Crystallographic modelling |
Q69500307 | Crystallographic studies and semi-empirical MNDO calculations on quisqualic acid and its analogues: systems containing unusual pyramidal heterocyclic ring nitrogens |
Q40565305 | Current methods for site-directed structure generation. |
Q57966454 | Current perspective of information technologies in drug discovery |
Q57017035 | Current trends in lead discovery: are we looking for the appropriate properties? |
Q42746608 | Customizing scoring functions for docking |
Q33593269 | Cyclodextrin KnowledgeBase a web-based service managing CD-ligand complexation data |
Q73803107 | Cyclophosphamides as hypoxia-activated diffusible cytotoxins: a theoretical study |
Q46050747 | D3R Grand Challenge 2: blind prediction of protein-ligand poses, affinity rankings, and relative binding free energies |
Q64118692 | D3R Grand Challenge 3: blind prediction of protein-ligand poses and affinity rankings |
Q91538145 | D3R Grand Challenge 4: ligand similarity and MM-GBSA-based pose prediction and affinity ranking for BACE-1 inhibitors |
Q91135912 | D3R Grand Challenge 4: prospective pose prediction of BACE1 ligands with AutoDock-GPU |
Q39328873 | D3R grand challenge 2015: Evaluation of protein-ligand pose and affinity predictions |
Q92892915 | D3R grand challenge 4: blind prediction of protein-ligand poses, affinity rankings, and relative binding free energies |
Q72240654 | DBMAKER: a set of programs to generate three-dimensional databases based upon user-specified criteria |
Q83012465 | DFT calculation of four new potential agents muscarinic of bispyridinium type: structure, synthesis, biological activity, hydration, and relations with the potents W84 and DUO-3O |
Q39869132 | DFT-based QSAR and QSPR models of several cis-platinum complexes: solvent effect |
Q33843997 | DFT-based prediction of reactivity of short-chain alcohol dehydrogenase. |
Q27231136 | DOCK 4.0: Search strategies for automated molecular docking of flexible molecule databases |
Q92260441 | DP-BINDER: machine learning model for prediction of DNA-binding proteins by fusing evolutionary and physicochemical information |
Q52567958 | DR2DI: a powerful computational tool for predicting novel drug-disease associations. |
Q30770159 | DREAM++: flexible docking program for virtual combinatorial libraries |
Q46937054 | Darwinian docking |
Q36852271 | Data modelling with neural networks: advantages and limitations. |
Q30970805 | Data quality in drug discovery: the role of analytical performance in ligand binding assays |
Q42684716 | Data sharing as an issue |
Q30735723 | Data sharing matters |
Q91624891 | Data structures for computational compound promiscuity analysis and exemplary applications to inhibitors of the human kinome |
Q30837195 | DataCite and DOI names for research data |
Q73913472 | Database diversity assessment: new ideas, concepts, and tools |
Q30194891 | De novo and inverse folding predictions of protein structure and dynamics |
Q80541220 | De novo design and synthetic accessibility |
Q51531786 | De novo design by pharmacophore-based searches in fragment spaces. |
Q30885899 | De novo design of molecular architectures by evolutionary assembly of drug-derived building blocks |
Q54452978 | De novo ligand design with explicit water molecules: an application to bacterial neuraminidase. |
Q38305525 | Deciphering common failures in molecular docking of ligand-protein complexes. |
Q91732591 | Deciphering structure, function and mechanism of Plasmodium IspD homologs from their evolutionary imprints |
Q92507759 | Deep neural network affinity model for BACE inhibitors in D3R Grand Challenge 4 |
Q100440522 | DeepCOMO: from structure-activity relationship diagnostics to generative molecular design using the compound optimization monitor methodology |
Q51658614 | Defining scaffold geometries for interacting with proteins: geometrical classification of secondary structure linking regions. |
Q79177476 | Defining the nucleotide binding sites of P2Y receptors using rhodopsin-based homology modeling |
Q34078930 | DemQSAR: predicting human volume of distribution and clearance of drugs |
Q83150153 | Democratization of computational chemistry and chem(o)informatics |
Q89450854 | Demystifying the pH dependent conformational changes of human heparanase pertaining to structure-function relationships: an in silico approach |
Q43606860 | Density functional and molecular docking studies towards investigating the role of single-wall carbon nanotubes as nanocarrier for loading and delivery of pyrazinamide antitubercular drug onto pncA protein. |
Q57905894 | Dependency of ligand free energy landscapes on charge parameters and solvent models |
Q72593895 | Derivation of a 3D pharmacophore model for the angiotensin-II site one receptor |
Q30576048 | Derivatives in discrete mathematics: a novel graph-theoretical invariant for generating new 2/3D molecular descriptors. I. Theory and QSPR application |
Q51311524 | Descriptor collision and confusion: toward the design of descriptors to mask chemical structures. |
Q31149833 | Descriptors you can count on? Normalized and filtered pharmacophore descriptors for virtual screening |
Q45407345 | Design and characterization of an engineered gp41 protein from human immunodeficiency virus-1 as a tool for drug discovery |
Q30873834 | Design and characterization of chemical space networks for different compound data sets |
Q54039496 | Design and synthesis of type-III mimetics of ShK toxin. |
Q74568399 | Design and synthesis of type-III mimetics of omega-conotoxin GVIA |
Q98652809 | Design and tests of prospective property predictions for novel antimalarial 2-aminopropylaminoquinolones |
Q78249929 | Design criteria for molecular mimics of fragments of the beta-turn. 1. C alpha atom analysis |
Q78249934 | Design criteria for molecular mimics of fragments of the beta-turn. 2. C alpha-C beta bond vector analysis |
Q33922101 | Design of a colicin E7 based chimeric zinc-finger nuclease |
Q33972623 | Design of a fragment library that maximally represents available chemical space |
Q33908733 | Design of a multi-purpose fragment screening library using molecular complexity and orthogonal diversity metrics. |
Q48230088 | Design of a tripartite network for the prediction of drug targets |
Q46939941 | Design of an activity landscape view taking compound-based feature probabilities into account |
Q35875854 | Design of chemical space networks on the basis of Tversky similarity |
Q86320243 | Design of chemical space networks using a Tanimoto similarity variant based upon maximum common substructures |
Q33417723 | Design of compound libraries for fragment screening |
Q73558603 | Design of dimerization inhibitors of HIV-1 aspartic proteinase: a computer-based combinatorial approach |
Q33225368 | Design of ligand binding to an engineered protein cavity using virtual screening and thermal up-shift evaluation. |
Q115732709 | Design of new imidazole derivatives with anti-HCMV activity: QSAR modeling, synthesis and biological testing |
Q43174214 | Design of new secreted phospholipase A2 inhibitors based on docking calculations by modifying the pharmacophore segments of the FPL67047XX inhibitor |
Q54334681 | Design of new selective inhibitors of cyclooxygenase-2 by dynamic assembly of molecular building blocks. |
Q57018486 | Design of potential angiogenin inhibitors |
Q40369005 | Design of recombinant stem cell factor-macrophage colony stimulating factor fusion proteins and their biological activity in vitro |
Q46614984 | Design of stapled DNA-minor-groove-binding molecules with a mutable atom simulated annealing method |
Q33543849 | Design, structure-based focusing and in silico screening of combinatorial library of peptidomimetic inhibitors of Dengue virus NS2B-NS3 protease |
Q35170923 | Design, synthesis and experimental validation of novel potential chemopreventive agents using random forest and support vector machine binary classifiers |
Q87139747 | Design, synthesis and in vitro kinetic study of tranexamic acid prodrugs for the treatment of bleeding conditions |
Q52587831 | Designing novel nicotinic agonists by searching a database of molecular shapes. |
Q77763158 | Designing sedative/hypnotic compounds from a novel substructural graph-theoretical approach |
Q39681302 | Designing the molecular future |
Q91134635 | Detailed potential of mean force studies on host-guest systems from the SAMPL6 challenge |
Q33466833 | Detection of ligand binding hot spots on protein surfaces via fragment-based methods: application to DJ-1 and glucocerebrosidase |
Q44291992 | Detection of tautomer proportions of dimedone in solution: a new approach based on theoretical and FT-IR viewpoint |
Q52531840 | Determination of clefts in receptor structures. |
Q71483788 | Determination of receptor-bound drug conformations by QSAR using flexible fitting to derive a molecular similarity index |
Q30664785 | Developing 13C NMR quantitative spectrometric data-activity relationship (QSDAR) models of steroid binding to the corticosteroid binding globulin |
Q35877995 | Developing a high-quality scoring function for membrane protein structures based on specific inter-residue interactions |
Q52118228 | Developing an in-house system to support combinatorial chemistry |
Q33440704 | Development and NMR validation of minimal pharmacophore hypotheses for the generation of fragment libraries enriched in heparanase inhibitors |
Q33260986 | Development and application of hybrid structure based method for efficient screening of ligands binding to G-protein coupled receptors |
Q33201132 | Development and testing of a de novo drug-design algorithm |
Q34588100 | Development and validation of a modular, extensible docking program: DOCK 5. |
Q42011227 | Development and validation of an improved algorithm for overlaying flexible molecules |
Q34647300 | Development of 7TM receptor-ligand complex models using ligand-biased, semi-empirical helix-bundle repacking in torsion space: application to the agonist interaction of the human dopamine D2 receptor |
Q30915859 | Development of QSAR models for microsomal stability: identification of good and bad structural features for rat, human and mouse microsomal stability |
Q47393221 | Development of SAAP3D force field and the application to replica-exchange Monte Carlo simulation for chignolin and C-peptide. |
Q44345689 | Development of a common 3D pharmacophore for delta-opioid recognition from peptides and non-peptides using a novel computer program |
Q44334810 | Development of a conformational search strategy for flexible ligands: a study of the potent mu-selective opioid analgesic fentanyl |
Q38967201 | Development of a pharmacophore for cruzain using oxadiazoles as virtual molecular probes: quantitative structure-activity relationship studies |
Q73331716 | Development of a unique 3D interaction model of endogenous and synthetic peripheral benzodiazepine receptor ligands |
Q52453050 | Development of an automatic estimation system for both the partition coefficient and aqueous solubility. |
Q44490741 | Development of biologically active compounds by combining 3D QSAR and structure-based design methods |
Q83178916 | Development of energetic pharmacophore for the designing of 1,2,3,4-tetrahydropyrimidine derivatives as selective cyclooxygenase-2 inhibitors |
Q80543755 | Development of in silico models for human liver microsomal stability |
Q30978307 | Development of predictive pharmacophore model for in silico screening, and 3D QSAR CoMFA and CoMSIA studies for lead optimization, for designing of potent tumor necrosis factor alpha converting enzyme inhibitors. |
Q46344744 | Development of purely structure-based pharmacophores for the topoisomerase I-DNA-ligand binding pocket |
Q83172122 | Development of small molecules designed to modulate protein-protein interactions |
Q31106855 | Development, interpretation and temporal evaluation of a global QSAR of hERG electrophysiology screening data |
Q49177279 | Different approaches toward an automatic structural alignment of drug molecules: applications to sterol mimics, thrombin and thermolysin inhibitors. |
Q33323614 | Differentiation of AmpC beta-lactamase binders vs. decoys using classification kNN QSAR modeling and application of the QSAR classifier to virtual screening |
Q44335475 | Differentiation of delta, mu, and kappa opioid receptor agonists based on pharmacophore development and computed physicochemical properties |
Q47624951 | Dihydrofolate reductase: a potential drug target in trypanosomes and leishmania. |
Q59576397 | Dimer asymmetry in superoxide dismutase studied by molecular dynamics simulation |
Q42274100 | Discover binding pathways using the sliding binding-box docking approach: application to binding pathways of oseltamivir to avian influenza H5N1 neuraminidase. |
Q58360607 | Discovering New Classes of Brugia malayi Asparaginyl-tRNA Synthetase Inhibitors and Relating Specificity to Conformational Change |
Q57271321 | Discovering high-affinity ligands from the computationally predicted structures and affinities of small molecules bound to a target: A virtual screening approach |
Q48299334 | Discovering new PI3Kα inhibitors with a strategy of combining ligand-based and structure-based virtual screening. |
Q91150165 | Discovery and evaluation of novel Mycobacterium tuberculosis ketol-acid reductoisomerase inhibitors as therapeutic drug leads |
Q36100810 | Discovery of DNA dyes Hoechst 34580 and 33342 as good candidates for inhibiting amyloid beta formation: in silico and in vitro study. |
Q90824891 | Discovery of a nanomolar inhibitor of the human glyoxalase-I enzyme using structure-based poly-pharmacophore modelling and molecular docking |
Q43701180 | Discovery of a novel serine protease inhibitor utilizing a structure-based and experimental selection of fragments technique |
Q91406534 | Discovery of a potential positive allosteric modulator of glucagon-like peptide 1 receptor through virtual screening and experimental study |
Q52328849 | Discovery of a small-molecule inhibitor of Dvl-CXXC5 interaction by computational approaches. |
Q93119102 | Discovery of new multifunctional selective acetylcholinesterase inhibitors: structure-based virtual screening and biological evaluation |
Q47797733 | Discovery of non-peptidic small molecule inhibitors of cyclophilin D as neuroprotective agents in Aβ-induced mitochondrial dysfunction |
Q85066830 | Discovery of novel human acrosin inhibitors by virtual screening |
Q50200993 | Discovery of novel inhibitors for Leishmania nucleoside diphosphatase kinase (NDK) based on its structural and functional characterization. |
Q91927626 | Discovery of novel inhibitors of human galactokinase by virtual screening |
Q40785976 | Discovery of novel polyamine analogs with anti-protozoal activity by computer guided drug repositioning |
Q91291275 | Discovery of novel wee1 inhibitors via structure-based virtual screening and biological evaluation |
Q33303858 | Discovery of small molecule inhibitors of ubiquitin-like poxvirus proteinase I7L using homology modeling and covalent docking approaches |
Q47380200 | Discovery of small molecules binding to the normal conformation of prion by combining virtual screening and multiple biological activity evaluation methods. |
Q78743159 | Discriminant and quantitative PLS analysis of competitive CYP2C9 inhibitors versus non-inhibitors using alignment independent GRIND descriptors |
Q48238825 | Disruptor of telomeric silencing 1-like (DOT1L): disclosing a new class of non-nucleoside inhibitors by means of ligand-based and structure-based approaches |
Q91903974 | Dissecting the molecular recognition of dual lapatinib derivatives for EGFR/HER2 |
Q41311286 | Distance geometry analysis of ligand binding to drug receptor sites |
Q47805558 | Distant collaboration in drug discovery: the LINK3D project |
Q30333075 | Distilling the essential features of a protein surface for improving protein-ligand docking, scoring, and virtual screening. |
Q96642516 | Distinct binding of cetirizine enantiomers to human serum albumin and the human histamine receptor H1 |
Q30406901 | Distinct functional and conformational states of the human lymphoid tyrosine phosphatase catalytic domain can be targeted by choice of the inhibitor chemotype |
Q57976081 | Distributed automated docking of flexible ligands to proteins: Parallel applications of AutoDock 2.4 |
Q73913479 | Diverse binding site structures revealed in homology models of polyreactive immunoglobulins |
Q92584649 | Diversifying chemical libraries with generative topographic mapping |
Q77763153 | Do active site conformations of small ligands correspond to low free-energy solution structures? |
Q34566045 | Do benzodiazepines mimic reverse-turn structures? |
Q52453044 | Do you believe in wavefunctions? |
Q48280219 | DockBench as docking selector tool: the lesson learned from D3R Grand Challenge 2015. |
Q80697148 | Docking and multivariate methods to explore HIV-1 drug-resistance: a comparative analysis |
Q83845170 | Docking and quantitative structure-activity relationship studies for 3-fluoro-4-(pyrrolo[2,1-f][1,2,4]triazin-4-yloxy)aniline, 3-fluoro-4-(1H-pyrrolo[2,3-b]pyridin-4-yloxy)aniline, and 4-(4-amino-2-fluorophenoxy)-2-pyridinylamine derivatives as c-Me |
Q45162110 | Docking and scoring of metallo-beta-lactamases inhibitors |
Q36098710 | Docking and scoring with ICM: the benchmarking results and strategies for improvement |
Q33527932 | Docking flexible ligands in proteins with a solvent exposure- and distance-dependent dielectric function |
Q38335016 | Docking glycosaminoglycans to proteins: analysis of solvent inclusion |
Q47797563 | Docking of small molecules to farnesoid X receptors using AutoDock Vina with the Convex-PL potential: lessons learned from D3R Grand Challenge 2. |
Q28266363 | Docking performance of the glide program as evaluated on the Astex and DUD datasets: a complete set of glide SP results and selected results for a new scoring function integrating WaterMap and glide |
Q39536628 | Docking pose selection by interaction pattern graph similarity: application to the D3R grand challenge 2015. |
Q91561359 | Docking rigid macrocycles using Convex-PL, AutoDock Vina, and RDKit in the D3R Grand Challenge 4 |
Q40525152 | Docking simulations suggest that all-trans retinoic acid could bind to retinoid X receptors. |
Q34415230 | Docking studies on NSAID/COX-2 isozyme complexes using contact statistics analysis |
Q44304349 | Docking study of the precursor peptide of mastoparan onto its putative processing enzyme, dipeptidyl peptidase IV: a revisit to molecular ticketing |
Q45184584 | Docking-based CoMFA and CoMSIA studies of non-nucleoside reverse transcriptase inhibitors of the pyridinone derivative type |
Q39317819 | Docking-undocking combination applied to the D3R Grand Challenge 2015. |
Q36243611 | DockingApp: a user friendly interface for facilitated docking simulations with AutoDock Vina |
Q43555843 | Does a diol cyclic urea inhibitor of HIV-1 protease bind tighter than its corresponding alcohol form? A study by free energy perturbation and continuum electrostatics calculations |
Q40985359 | Does your model weigh the same as a duck? |
Q38965242 | Drude polarizable force field for aliphatic ketones and aldehydes, and their associated acyclic carbohydrates |
Q89522959 | Drug Design Data Resource, Grand Challenge 4, second of two issues |
Q28732341 | Drug design for ever, from hype to hope |
Q33888145 | Drug discovery using very large numbers of patents: general strategy with extensive use of match and edit operations |
Q36082949 | Drug search for leishmaniasis: a virtual screening approach by grid computing. |
Q46121038 | Drug-resistant molecular mechanism of CRF01_AE HIV-1 protease due to V82F mutation |
Q34093054 | Druggability of methyl-lysine binding sites |
Q92566519 | Druggable exosites of the human kino-pocketome |
Q91135896 | Dual-targeted hit identification using pharmacophore screening |
Q41856129 | Dynamic clustering threshold reduces conformer ensemble size while maintaining a biologically relevant ensemble |
Q33825866 | Dynamic models of G-protein coupled receptor dimers: indications of asymmetry in the rhodopsin dimer from molecular dynamics simulations in a POPC bilayer. |
Q68049863 | Dynamic simulation as an essential tool in molecular modeling |
Q46720950 | Dynamical aspects of TEM-1 beta-lactamase probed by molecular dynamics |
Q86706640 | Dynamics and structural determinants of ligand recognition of the 5-HT6 receptor |
Q45102501 | E-state fields: applications to 3D QSAR. |
Q46788954 | ENPDA: an evolutionary structure-based de novo peptide design algorithm. |
Q73194557 | EVA: a new theoretically based molecular descriptor for use in QSAR/QSPR analysis |
Q51891050 | Editorial: special issue on "Evaluation of computational methods". |
Q44187754 | Effect of pH and ligand charge state on BACE-1 fragment docking performance |
Q33894051 | Effect of training data size and noise level on support vector machines virtual screening of genotoxic compounds from large compound libraries |
Q45944000 | Effective prediction of bacterial type IV secreted effectors by combined features of both C-termini and N-termini. |
Q46932255 | Effective virtual screening protocol for CYP2C9 ligands using a screening site constructed from flurbiprofen and S-warfarin pockets |
Q52033846 | Effectiveness of graph-based and fingerprint-based similarity measures for virtual screening of 2D chemical structure databases. |
Q36803981 | Effects of histidine protonation and rotameric states on virtual screening of M. tuberculosis RmlC. |
Q47730473 | Effects of inductive bias on computational evaluations of ligand-based modeling and on drug discovery |
Q50278953 | Effects of point mutations on the thermostability of B. subtilis lipase: investigating nonadditivity. |
Q43115469 | Effects of protein conformation in docking: improved pose prediction through protein pocket adaptation |
Q58855853 | Effects of variable selection on CoMFA coefficient contour maps in a set of triazines inhibiting DHFR |
Q37730016 | Efficient calculation of SAMPL4 hydration free energies using OMEGA, SZYBKI, QUACPAC, and Zap TK. |
Q30155477 | Efficient molecular mechanics simulations of the folding, orientation, and assembly of peptides in lipid bilayers using an implicit atomic solvation model |
Q34575180 | Efficient overlay of small organic molecules using 3D pharmacophores |
Q50744649 | Elaborate ligand-based modeling coupled with QSAR analysis and in silico screening reveal new potent acetylcholinesterase inhibitors. |
Q50985589 | Elaborate ligand-based modeling reveal new submicromolar Rho kinase inhibitors. |
Q57976070 | ElectroShape: fast molecular similarity calculations incorporating shape, chirality and electrostatics |
Q73798619 | Electron affinities of p-benzoquinone, p-benzoquinone imine and p-benzoquinone diimine, and spin densities of their p-benzosemiquinones computed by several quantum chemical models |
Q44871243 | Electron-density-dependent fused-sphere surfaces derived from pseudopotential calculations |
Q77447721 | Electrostatic and structural similarity of classical and non-classical lactam compounds |
Q57137396 | Electrostatic complementarity between proteins and ligands. 1. Charge disposition, dielectric and interface effects |
Q52370120 | Electrostatic complementarity between proteins and ligands. 2. Ligand moieties. |
Q52370117 | Electrostatic complementarity between proteins and ligands. 3. Structural basis. |
Q33250369 | Electrostatic evaluation of isosteric analogues |
Q90934690 | Electrostatic-field and surface-shape similarity for virtual screening and pose prediction |
Q70232995 | Electrostatics and computational modelling. Editorial overview |
Q92475363 | Elucidating the druggability of the human proteome with eFindSite |
Q77763145 | Elucidation of a common structure of selective fibrinogen receptor antagonists |
Q45991103 | Empirical estimation of the energetic contribution of individual interface residues in structures of protein-protein complexes. |
Q52230454 | Empirical scoring functions. II. The testing of an empirical scoring function for the prediction of ligand-receptor binding affinities and the use of Bayesian regression to improve the quality of the model. |
Q53678858 | Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes. |
Q31141737 | Empowering pharmacoinformatics by linked life science data |
Q114955379 | Enabling data-limited chemical bioactivity predictions through deep neural network transfer learning |
Q39233769 | Enabling drug discovery project decisions with integrated computational chemistry and informatics. |
Q48137563 | Enabling the hypothesis-driven prioritization of ligand candidates in big databases: Screenlamp and its application to GPCR inhibitor discovery for invasive species control. |
Q44554590 | Enantioselectivity of epoxide hydrolase catalysed oxirane ring opening: a 3D QSAR study. |
Q30834193 | Encouraging data citation and discovery with the Data Citation Index. |
Q33440708 | Energetic analysis of fragment docking and application to structure-based pharmacophore hypothesis generation |
Q83476926 | Energetic basis for drug resistance of HIV-1 protease mutants against amprenavir |
Q68844981 | Energy minimization and molecular dynamics studies of Asn-102 elastase |
Q44699698 | Engineering strategy to improve peptide analogs: from structure-based computational design to tumor homing |
Q53504228 | Engineering the Pseudomonas aeruginosa II lectin: designing mutants with changed affinity and specificity. |
Q33277028 | Enhancement of chemical rules for predicting compound reactivity towards protein thiol groups |
Q67976692 | Enhancement of the solubilities of polycyclic aromatic hydrocarbons by weak hydrogen bonds with water |
Q89949705 | Enhancing reaction-based de novo design using a multi-label reaction class recommender |
Q80988436 | Enhancing the accuracy of virtual screening: molecular dynamics with quantum-refined force fields |
Q36794962 | Enhancing the diversity of a corporate database using chemical database clustering and analysis |
Q99618258 | Enhancing water sampling of buried binding sites using nonequilibrium candidate Monte Carlo |
Q51070891 | Ensemble pharmacophore meets ensemble docking: a novel screening strategy for the identification of RIPK1 inhibitors. |
Q81360455 | Epik: a software program for pK( a ) prediction and protonation state generation for drug-like molecules |
Q48244185 | Erratum to: A combined treatment of hydration and dynamical effects for the modeling of host-guest binding thermodynamics: the SAMPL5 blinded challenge |
Q85959848 | Erratum to: A desirability function-based scoring scheme for selecting fragment-like class A aminergic GPCR ligands |
Q45064339 | Erratum to: Lessons learned from comparing molecular dynamics engines on the SAMPL5 dataset |
Q86650052 | Erratum to: design of chemical space networks using a Tanimoto similarity variant based upon maximum common substructures |
Q53863505 | Essential dynamics/factor analysis for the interpretation of molecular dynamics trajectories. |
Q62489974 | Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules |
Q45964937 | Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules. |
Q78249937 | Estimation of active conformations of drugs by a new molecular superposing procedure |
Q30680780 | Estimation of influential points in any data set from coefficient of determination and its leave-one-out cross-validated counterpart |
Q50919565 | Estimation of relative binding free energy based on a free energy variational principle for the FKBP-ligand system. |
Q30662631 | Estimation of the size of drug-like chemical space based on GDB-17 data. |
Q51281674 | EuLoc: a web-server for accurately predict protein subcellular localization in eukaryotes by incorporating various features of sequence segments into the general form of Chou's PseAAC. |
Q86188015 | Euclidean chemical spaces from molecular fingerprints: Hamming distance and Hempel's ravens |
Q46148600 | Evaluating docked complexes with the HINT exponential function and empirical atomic hydrophobicities. |
Q30367162 | Evaluating docking programs: keeping the playing field level. |
Q51482704 | Evaluating the applicability domain in the case of classification predictive models for carcinogenicity based on the counter propagation artificial neural network. |
Q93119111 | Evaluating the performance of MM/PBSA for binding affinity prediction using class A GPCR crystal structures |
Q33209809 | Evaluation and application of multiple scoring functions for a virtual screening experiment |
Q37518530 | Evaluation of DOCK 6 as a pose generation and database enrichment tool |
Q38558776 | Evaluation of a method for controlling molecular scaffold diversity in de novo ligand design |
Q73798633 | Evaluation of a novel infrared range vibration-based descriptor (EVA) for QSAR studies. 1. General application |
Q77365348 | Evaluation of a novel molecular vibration-based descriptor (EVA) for QSAR studies: 2. Model validation using a benchmark steroid dataset |
Q80543481 | Evaluation of descriptors and classification schemes to predict cytochrome substrates in terms of chemical information |
Q43786252 | Evaluation of designed ligands by a multiple screening method: application to glycogen phosphorylase inhibitors constructed with a variety of approaches |
Q92763898 | Evaluation of different virtual screening strategies on the basis of compound sets with characteristic core distributions and dissimilarity relationships |
Q34104969 | Evaluation of docking performance in a blinded virtual screening of fragment-like trypsin inhibitors |
Q52076496 | Evaluation of docking/scoring approaches: a comparative study based on MMP3 inhibitors. |
Q44667599 | Evaluation of extended parameter sets for the 3D-QSAR technique MaP: implications for interpretability and model quality exemplified by antimalarially active naphthylisoquinoline alkaloids |
Q36700190 | Evaluation of machine-learning methods for ligand-based virtual screening |
Q112614220 | Evaluation of multi-target deep neural network models for compound potency prediction under increasingly challenging test conditions |
Q36897804 | Evaluation of proposed modes of binding of (2S)-2-[4-[[(3S)-1-acetimidoyl-3-pyrrolidinyl]oxy]phenyl]-3-(7-am idino- 2- naphthyl)propanoic acid hydrochloride and some analogs to factor Xa using a comparative molecular field analysis |
Q56986653 | Evaluation of reactant-based and product-based approaches to the design of combinatorial libraries |
Q52081435 | Evaluation of the EVA descriptor for QSAR studies: 3. The use of a genetic algorithm to search for models with enhanced predictive properties (EVA_GA). |
Q37057393 | Evaluation of the performance of 3D virtual screening protocols: RMSD comparisons, enrichment assessments, and decoy selection--what can we learn from earlier mistakes? |
Q40931321 | Evolutionary algorithms in computer-aided molecular design |
Q38720771 | ExcelAutomat: a tool for systematic processing of files as applied to quantum chemical calculations |
Q30358437 | Exhaustive docking and solvated interaction energy scoring: lessons learned from the SAMPL4 challenge. |
Q83133195 | Exhaustive search and solvated interaction energy (SIE) for virtual screening and affinity prediction |
Q100512761 | Experimental characterization of the association of β-cyclodextrin and eight novel cyclodextrin derivatives with two guest compounds |
Q43687591 | Experimental design based 3-D QSAR analysis of steroid-protein interactions: application to human CBG complexes |
Q46568237 | Experimental versus predicted affinities for ligand binding to estrogen receptor: iterative selection and rescoring of docked poses systematically improves the correlation |
Q86018664 | Exploring conformational search protocols for ligand-based virtual screening and 3-D QSAR modeling |
Q60238413 | Exploring ensembles of bioactive or virtual analogs of X-ray ligands for shape similarity searching |
Q51911690 | Exploring fragment spaces under multiple physicochemical constraints. |
Q91292738 | Exploring fragment-based target-specific ranking protocol with machine learning on cathepsin S |
Q30875882 | Exploring privileged structures: the combinatorial synthesis of cyclic peptides |
Q48035411 | Exploring sets of molecules from patents and relationships to other active compounds in chemical space networks |
Q52652923 | Exploring the dynamics and interaction of a full ErbB2 receptor and Trastuzumab-Fab antibody in a lipid bilayer model using Martini coarse-grained force field. |
Q56989244 | Exploring the free-energy landscape of carbohydrate–protein complexes: development and validation of scoring functions considering the binding-site topology |
Q90374506 | Exploring the inhibitory activity of valproic acid against the HDAC family using an MMGBSA approach |
Q44554593 | Exploring the molecular basis of selectivity in A1 adenosine receptors agonists: a case study |
Q39027957 | Exploring the stability of ligand binding modes to proteins by molecular dynamics simulations |
Q49177145 | Extended electron distributions applied to the molecular mechanics of some intermolecular interactions. |
Q71851456 | Extended electron distributions applied to the molecular mechanics of some intermolecular interactions. II. Organic complexes |
Q43524484 | Extended solvent-contact model approach to SAMPL4 blind prediction challenge for hydration free energies |
Q39569522 | Extended solvent-contact model approach to blind SAMPL5 prediction challenge for the distribution coefficients of drug-like molecules |
Q72816270 | Extending the trend vector: the trend matrix and sample-based partial least squares |
Q48891681 | Extensive all-atom Monte Carlo sampling and QM/MM corrections in the SAMPL4 hydration free energy challenge. |
Q91596904 | Extensive benchmark of rDock as a peptide-protein docking tool |
Q30423742 | Extensive structural change of the envelope protein of dengue virus induced by a tuned ionic strength: conformational and energetic analyses. |
Q53395167 | Extracting ligands from receptors by reversed targeted molecular dynamics. |
Q34415675 | Extraction and validation of substructure profiles for enriching compound libraries |
Q39116173 | Extrapolative prediction using physically-based QSAR. |
Q51643618 | FILO (field interaction ligand optimization): a simplex strategy for searching the optimal ligand interaction field in drug design. |
Q43786250 | FLASHFLOOD: a 3D field-based similarity search and alignment method for flexible molecules |
Q30420637 | FLOG: a system to select 'quasi-flexible' ligands complementary to a receptor of known three-dimensional structure |
Q38565532 | FOUNDATION: a program to retrieve all possible structures containing a user-defined minimum number of matching query elements from three-dimensional databases |
Q51358561 | FRED and HYBRID docking performance on standardized datasets. |
Q43451646 | FTree query construction for virtual screening: a statistical analysis. |
Q30585007 | Facet diagrams for quantum similarity data |
Q58616267 | Factor Xa: simulation studies with an eye to inhibitor design |
Q91907393 | Families and clans of cysteine peptidases |
Q43594676 | Fast 3D molecular superposition and similarity search in databases of flexible molecules |
Q47845562 | Fast H-DROP: A thirty times accelerated version of H-DROP for interactive SVM-based prediction of helical domain linkers |
Q44247409 | Fast and accurate methods for predicting short-range constraints in protein models |
Q44325905 | Fast estimation of hydrogen-bonding donor and acceptor propensities: a GMIPp study. |
Q52078631 | Fast prediction and visualization of protein binding pockets with PASS. |
Q45906417 | Fast prediction of hydration free energies for SAMPL4 blind test from a classical density functional theory. |
Q51647018 | Feature trees: a new molecular similarity measure based on tree matching. |
Q45965607 | Feature-map vectors: a new class of informative descriptors for computational drug discovery. |
Q78683432 | Filtering databases and chemical libraries |
Q38302057 | Finding potential DNA-binding compounds by using molecular shape |
Q52528201 | Fine specificity of antigen binding to two class I major histocompatibility proteins (B*2705 and B*2703) differing in a single amino acid residue. |
Q90857873 | First virtual screening and experimental validation of inhibitors targeting GES-5 carbapenemase |
Q30834186 | Fitting and handling dose response data |
Q97533134 | Flexi-pharma: a molecule-ranking strategy for virtual screening using pharmacophores from ligand-free conformational ensembles |
Q34319987 | Flexibases: a way to enhance the use of molecular docking methods |
Q34054640 | Flexibility of a biotinylated ligand in artificial metalloenzymes based on streptavidin--an insight from molecular dynamics simulations with classical and ab initio force fields |
Q44109232 | Flexible docking under pharmacophore type constraints |
Q52346365 | Flexible ligand docking using a genetic algorithm. |
Q71749028 | Flexible matching of test ligands to a 3D pharmacophore using a molecular superposition force field: comparison of predicted and experimental conformations of inhibitors of three enzymes |
Q30952629 | Flexsim-R: a virtual affinity fingerprint descriptor to calculate similarities of functional groups |
Q91063627 | Focused Library Generator: case of Mdmx inhibitors |
Q90101463 | Force field development phase II: Relaxation of physics-based criteria… or inclusion of more rigorous physics into the representation of molecular energetics |
Q57057117 | Force matching as a stepping stone to QM/MM CB[8] host/guest binding free energies: a SAMPL6 cautionary tale |
Q46419532 | Force-field and quantum-mechanical binding study of selected SAMPL3 host-guest complexes |
Q44896308 | Force-field parametrization and molecular dynamics simulations of Congo red. |
Q58225273 | Force-field parametrization and molecular dynamics simulations of p-menthan-3,9-diols: a family of amphiphilic compounds derived from terpenoids |
Q58224827 | Force-field parametrization of retro-inverso modified residues: Development of torsional and electrostatic parameters |
Q38909972 | ForceGen 3D structure and conformer generation: from small lead-like molecules to macrocyclic drugs |
Q36438659 | Forces in molecular recognition: comparison of experimental data and molecular mechanics calculations |
Q41282224 | Forging the future |
Q74633111 | Fractional description of free energies of solvation |
Q35074986 | Fragment-based Shape Signatures: a new tool for virtual screening and drug discovery |
Q33474361 | Fragment-based drug discovery |
Q48438267 | Fragment-based drug discovery: what really works. An interview with Sandy Farmer of Boehringer Ingelheim. |
Q39731911 | Fragment-based lead discovery: challenges and opportunities |
Q33469688 | Fragment-based lead generation: identification of seed fragments by a highly efficient fragment screening technology |
Q46844812 | Fragment-based prediction of skin sensitization using recursive partitioning. |
Q35030073 | Fragment-based strategy for structural optimization in combination with 3D-QSAR. |
Q42956918 | Fragment-guided approach to incorporating structural information into a CoMFA study: BACE-1 as an example |
Q51550370 | Free energy calculations offer insights into the influence of receptor flexibility on ligand-receptor binding affinities. |
Q43844939 | Free energy force field (FEFF) 3D-QSAR analysis of a set of Plasmodium falciparum dihydrofolate reductase inhibitors |
Q46628590 | Free energy perturbation approach to the critical assessment of selective cyclooxygenase-2 inhibitors |
Q57235415 | Free enthalpies of replacing water molecules in protein binding pockets |
Q87611444 | Free-energy perturbation and quantum mechanical study of SAMPL4 octa-acid host-guest binding energies |
Q28655211 | FreeSolv: a database of experimental and calculated hydration free energies, with input files |
Q45945153 | From bird's eye views to molecular communities: two-layered visualization of structure-activity relationships in large compound data sets. |
Q30657218 | From data point timelines to a well curated data set, data mining of experimental data and chemical structure data from scientific articles, problems and possible solutions |
Q83133107 | Frozen out: molecular modeling in the age of cryocrystallography |
Q58859728 | Functional concerted motions in the bovine serum retinol-binding protein |
Q30165525 | Functional group placement in protein binding sites: a comparison of GRID and MCSS. |
Q71483760 | Functionality map analysis of the active site cleft of human thrombin |
Q41103702 | Furan-based benzene mono- and dicarboxylic acid derivatives as multiple inhibitors of the bacterial Mur ligases (MurC-MurF): experimental and computational characterization |
Q34526566 | Further development and validation of empirical scoring functions for structure-based binding affinity prediction |
Q41295404 | Future in biomolecular computation |
Q44348873 | Future structural genomics initiatives: an interview with Helen Berman, director of the Protein Data Bank. Interview by Wendy A Warr |
Q51930711 | GALAHAD: 1. pharmacophore identification by hypermolecular alignment of ligands in 3D. |
Q30925927 | GEOM: a new tool for molecular modelling based on distance geometry calculations with NMR data |
Q52373585 | GREEN: a program package for docking studies in rational drug design. |
Q58137119 | GRIND-derived pharmacophore model for a series of α-tropanyl derivative ligands of the sigma-2 receptor* |
Q47565870 | GalaxyDock BP2 score: a hybrid scoring function for accurate protein-ligand docking |
Q51992733 | Gaussian mapping of chemical fragments in ligand binding sites. |
Q34076146 | Gazing into the crystal ball; the future of computer-aided drug design |
Q52401172 | GenStar: a method for de novo drug design. |
Q90703523 | Generating conformational transition paths with low potential-energy barriers for proteins |
Q58860144 | Generation of a homology model of the human histamine H3 receptor for ligand docking and pharmacophore-based screening |
Q51899915 | Generation of in-silico cytochrome P450 1A2, 2C9, 2C19, 2D6, and 3A4 inhibition QSAR models. |
Q46467172 | Generation of multiple pharmacophore hypotheses using multiobjective optimisation techniques |
Q31132887 | Genetic algorithm for the design of molecules with desired properties |
Q51536807 | Genetic algorithms and self-organizing maps: a powerful combination for modeling complex QSAR and QSPR problems. |
Q51245948 | Genetic algorithms as a tool for helix design--computational and experimental studies on prion protein helix 1. |
Q46865680 | Genetic neural network modeling of the selective inhibition of the intermediate-conductance Ca2+ -activated K+ channel by some triarylmethanes using topological charge indexes descriptors. |
Q69601240 | Geometries of functional group interactions in enzyme-ligand complexes: guides for receptor modelling |
Q40036944 | Geometry optimization method versus predictive ability in QSPR modeling for ionic liquids |
Q73652694 | Global 3D-QSAR methods: MS-WHIM and autocorrelation |
Q46328629 | Glycogen synthase kinase-3 inhibition by 3-anilino-4-phenylmaleimides: insights from 3D-QSAR and docking |
Q33317309 | GridMol: a grid application for molecular modeling and visualization |
Q80164054 | Guest editorial for special issue on "ADME and Physical Properties" |
Q30359360 | Guidelines for the analysis of free energy calculations |
Q48449691 | Guiding effective decisions: an interview with Matthew Segall, CEO of Optibrium. Interview by Wendy A. Warr. |
Q51074171 | H-DROP: an SVM based helical domain linker predictor trained with features optimized by combining random forest and stepwise selection. |
Q44194556 | HEPT derivatives as non-nucleoside inhibitors of HIV-1 reverse transcriptase: QSAR studies agree with the crystal structures |
Q44935041 | HINT: a new method of empirical hydrophobic field calculation for CoMFA. |
Q56395272 | HTMoL: full-stack solution for remote access, visualization, and analysis of molecular dynamics trajectory data |
Q48311195 | Herman Skolnik award symposium honoring Yvonne Martin. |
Q41105119 | Heterofullerenes: structure and property predictions, possible uses and synthesis proposals |
Q73913499 | Heuristic lipophilicity potential for computer-aided rational drug design |
Q77622454 | Heuristic lipophilicity potential for computer-aided rational drug design: optimizations of screening functions and parameters |
Q80642889 | Hierarchical QSAR technology based on the Simplex representation of molecular structure |
Q51937056 | Hierarchical clustering analysis of flexible GBR 12909 dialkyl piperazine and piperidine analogs. |
Q91120392 | High accuracy quantum-chemistry-based calculation and blind prediction of macroscopic pKa values in the context of the SAMPL6 challenge |
Q43936132 | High-affinity interactions of ligands at recombinant guinea pig 5HT7 receptors |
Q33258784 | High-throughput structure-based pharmacophore modelling as a basis for successful parallel virtual screening |
Q69724839 | Highly conformationally constrained halogenated 6-spiroepoxypenicillins as probes for the bioactive side-chain conformation of benzylpenicillin |
Q46382445 | Homo-timeric structural model of human microsomal prostaglandin E synthase-1 and characterization of its substrate/inhibitor binding interactions |
Q73558607 | Homology model directed alignment selection for comparative molecular field analysis: application to photosystem II inhibitors |
Q51680712 | Homology modeling and metabolism prediction of human carboxylesterase-2 using docking analyses by GriDock: a parallelized tool based on AutoDock 4.0. |
Q45140752 | Homology modeling and molecular dynamics simulation of N-myristoyltransferase from protozoan parasites: active site characterization and insights into rational inhibitor design |
Q46630846 | Homology modeling and molecular interaction field studies of alpha-glucosidases as a guide to structure-based design of novel proposed anti-HIV inhibitors. |
Q42643877 | Homology modeling of 5-lipoxygenase and hints for better inhibitor design |
Q77622447 | Homology modeling of the receptor binding domain of human thrombopoietin |
Q84325850 | Homology modeling, docking and structure-based pharmacophore of inhibitors of DNA methyltransferase |
Q45232745 | Homology modeling, force field design, and free energy simulation studies to optimize the activities of histone deacetylase inhibitors |
Q43276048 | Homology modelling of the human adenosine A2B receptor based on X-ray structures of bovine rhodopsin, the beta2-adrenergic receptor and the human adenosine A2A receptor |
Q72137028 | HomologyPlot: searching for homology to a family of proteins using a database of unique conserved patterns |
Q58023183 | Host andPorphyromonas gingivalis proteinases in periodontitis: A biochemical model of infection and tissue destruction |
Q89690119 | How N-(pyridin-4-yl)pyridin-4-amine and its methyl and nitro derivatives are arranged in the interlayer space of zirconium sulfophenylphosphonate: a problem solved by experimental and calculation methods |
Q47793987 | How accurate are continuum solvation models for drug-like molecules? |
Q92763888 | How computational chemistry develops: a tribute to Peter Goodford |
Q90303607 | How medicinal chemists learned about log P |
Q84958923 | How the energy evaluation method used in the geometry optimization step affect the quality of the subsequent QSAR/QSPR models |
Q30952705 | How to acquire new biological activities in old compounds by computer prediction. |
Q37064087 | How to do an evaluation: pitfalls and traps |
Q94083406 | How to do an evaluation: pitfalls and traps |
Q87313284 | Human farnesyl pyrophosphate synthase inhibition by nitrogen bisphosphonates: a 3D-QSAR study |
Q46630855 | Human topoisomerase I poisoning: docking protoberberines into a structure-based binding site model |
Q90863654 | Hybrid receptor structure/ligand-based docking and activity prediction in ICM: development and evaluation in D3R Grand Challenge 3 |
Q71491557 | Hydration in drug design. 1. Multiple hydrogen-bonding features of water molecules in mediating protein-ligand interactions |
Q71491560 | Hydration in drug design. 2. Influence of local site surface shape on water binding |
Q53903013 | Hydration in drug design. 3. Conserved water molecules at the ligand-binding sites of homologous proteins. |
Q57752850 | Hydration of beta-cyclodextrin: a molecular dynamics simulation study |
Q73233704 | Hydrogen bonding and dimeric self-association of 2-pyrrolidinone: an ab initio study |
Q52376641 | Hydrophile-lipophile balance of alkyl ethoxylated surfactants as a function of intermolecular energies. |
Q46758100 | Hydrophobic molecular similarity from MST fractional contributions to the octanol/water partition coefficient. |
Q48593386 | IA, database of known ligands of aminoacyl-tRNA synthetases. |
Q56918926 | IADE: a system for intelligent automatic design of bioisosteric analogs |
Q44779922 | IS-Dom: a dataset of independent structural domains automatically delineated from protein structures |
Q52234494 | Identification and energetic ranking of possible docking sites for pterin on dihydrofolate reductase. |
Q89630929 | Identification and neuroprotective evaluation of a potential c-Jun N-terminal kinase 3 inhibitor through structure-based virtual screening and in-vitro assay |
Q38942084 | Identification of antipsychotic drug fluspirilene as a potential p53-MDM2 inhibitor: a combined computational and experimental study |
Q53365053 | Identification of common inhibitors of wild-type and T315I mutant of BCR-ABL through the parallel structure-based virtual screening. |
Q43631523 | Identification of cylin-dependent kinase 1 inhibitors of a new chemical type by structure-based design and database searching |
Q30378289 | Identification of family-specific residue packing motifs and their use for structure-based protein function prediction: I. Method development. |
Q33472769 | Identification of family-specific residue packing motifs and their use for structure-based protein function prediction: II. Case studies and applications |
Q54313399 | Identification of ligand efficient, fragment-like hits from an HTS library: structure-based virtual screening and docking investigations of 2H- and 3H-pyrazolo tautomers for Aurora kinase A selectivity. |
Q41751942 | Identification of ligands for RNA targets via structure-based virtual screening: HIV-1 TAR. |
Q42991468 | Identification of ligands that target the HCV-E2 binding site on CD81. |
Q36171916 | Identification of novel Trypanosoma cruzi prolyl oligopeptidase inhibitors by structure-based virtual screening. |
Q92533317 | Identification of novel and potent small-molecule inhibitors of tubulin with antitumor activities by virtual screening and biological evaluations |
Q41035643 | Identification of novel inhibitors for Pim-1 kinase using pharmacophore modeling based on a novel method for selecting pharmacophore generation subsets. |
Q35329233 | Identification of novel inhibitors of human Chk1 using pharmacophore-based virtual screening and their evaluation as potential anti-cancer agents. |
Q53425325 | Identification of novel inhibitors of mitogen-activated protein kinase phosphatase-1 with structure-based virtual screening. |
Q35234394 | Identification of novel peroxisome proliferator-activated receptor-gamma (PPARγ) agonists using molecular modeling method. |
Q34691787 | Identification of novel small molecule TGF-β antagonists using structure-based drug design |
Q40396412 | Identification of novel target sites and an inhibitor of the dengue virus E protein |
Q91255146 | Identification of protoberberine alkaloids as novel histone methyltransferase G9a inhibitors by structure-based virtual screening |
Q31068979 | Identification of target-specific bioisosteric fragments from ligand-protein crystallographic data |
Q41921115 | Identification of the quinolinedione inhibitor binding site in Cdc25 phosphatase B through docking and molecular dynamics simulations |
Q34458951 | Identification of tissue-specific targeting peptide |
Q33400428 | Identifying conformational changes of the beta(2) adrenoceptor that enable accurate prediction of ligand/receptor interactions and screening for GPCR modulators |
Q30409188 | Identifying ligand binding sites and poses using GPU-accelerated Hamiltonian replica exchange molecular dynamics |
Q44087623 | Identifying potential binding modes and explaining partitioning behavior using flexible alignments and multidimensional scaling |
Q47604123 | Identifying the binding mode of a molecular scaffold. |
Q35714235 | If we designed airplanes like we design drugs.... |
Q45991101 | Imidazole-containing farnesyltransferase inhibitors: 3D quantitative structure-activity relationships and molecular docking. |
Q45747848 | Impact of distance-based metric learning on classification and visualization model performance and structure-activity landscapes. |
Q47406205 | Impact of domain knowledge on blinded predictions of binding energies by alchemical free energy calculations |
Q49349893 | Impact of graphene-based nanomaterials (GBNMs) on the structural and functional conformations of hepcidin peptide. |
Q51963745 | Implementation of smooth continuous camera trajectories for viewing PDB and VRML objects. |
Q40675058 | Implicit solvation in the self-consistent mean field theory method: sidechain modelling and prediction of folding free energies of protein mutants. |
Q43805829 | Improved convergence of binding affinities with free energy perturbation: application to nonpeptide ligands with pp60src SH2 domain |
Q33573726 | Improved docking, screening and selectivity prediction for small molecule nuclear receptor modulators using conformational ensembles |
Q42739070 | Improved estimation of ligand-macromolecule binding affinities by linear response approach using a combination of multi-mode MD simulation and QM/MM methods |
Q30844880 | Improved mapping of protein binding sites |
Q31135416 | Improved pose and affinity predictions using different protocols tailored on the basis of data availability |
Q38698230 | Improving binding mode and binding affinity predictions of docking by ligand-based search of protein conformations: evaluation in D3R grand challenge 2015. |
Q80642884 | Improving database enrichment through ensemble docking |
Q30369696 | Improving homology modeling of G-protein coupled receptors through multiple-template derived conserved inter-residue interactions. |
Q92971717 | Improving ligand 3D shape similarity-based pose prediction with a continuum solvent model |
Q51500330 | Improving molecular docking through eHiTS' tunable scoring function. |
Q39187331 | Improving quantitative structure-activity relationship models using Artificial Neural Networks trained with dropout |
Q57976069 | Improving the accuracy of ultrafast ligand-based screening: incorporating lipophilicity into ElectroShape as an extra dimension |
Q90416653 | Improving the binding affinity estimations of protein-ligand complexes using machine-learning facilitated force field method |
Q115732708 | Imputation of sensory properties using deep learning |
Q34194604 | In memoriam professor Corwin Hansch: birth pangs of QSAR before 1961. |
Q30351707 | In search of new lead compounds for trypanosomiasis drug design: a protein structure-based linked-fragment approach. |
Q28820807 | In search of novel ligands using a structure-based approach: a case study on the adenosine A2A receptor |
Q35292182 | In silico ADME/Tox: why models fail |
Q42979856 | In silico analysis of the histaprodifen induced activation pathway of the guinea-pig histamine H(1)-receptor |
Q91343393 | In silico fragment-mapping method: a new tool for fragment-based/structure-based drug discovery |
Q42730804 | In silico identification of new ligands for GPR17: a promising therapeutic target for neurodegenerative diseases |
Q38302099 | In silico identification of novel ligands for G-quadruplex in the c-MYC promoter |
Q39428478 | In silico inspired design and synthesis of a novel tubulin-binding anti-cancer drug: folate conjugated noscapine (Targetin). |
Q46111336 | In silico model for P-glycoprotein substrate prediction: insights from molecular dynamics and in vitro studies |
Q33202593 | In silico models for the prediction of dose-dependent human hepatotoxicity |
Q43658463 | In silico molecular docking analysis of the human Argonaute 2 PAZ domain reveals insights into RNA interference. |
Q82283376 | In silico prediction of acyl glucuronide reactivity |
Q31165898 | In silico prediction of drug toxicity |
Q47844404 | In silico probing and biological evaluation of SETDB1/ESET-targeted novel compounds that reduce tri-methylated histone H3K9 (H3K9me3) level |
Q44554597 | In silico rationalization of the structural and physicochemical requirements for photobiological activity in angelicine derivatives and their heteroanalogues |
Q34785012 | In silico screening for Plasmodium falciparum enoyl-ACP reductase inhibitors |
Q61445645 | In silico strategies for the selection of chelating compounds with potential application in metal-promoted neurodegenerative diseases |
Q48439351 | In tribute to Corwin Hansch, father of QSAR. |
Q53076975 | In-silico guided discovery of novel CCR9 antagonists. |
Q52566240 | In-silico screening using flexible ligand binding pockets: a molecular dynamics-based approach. |
Q36606981 | Inactive and active states and supramolecular organization of GPCRs: insights from computational modeling |
Q42673544 | Inclusion of conserved buried water molecules in the model structure of rat submaxillary kallikrein. |
Q51925745 | Incorporating partial matches within multi-objective pharmacophore identification. |
Q47808756 | Incorporating significant amino acid pairs and protein domains to predict RNA splicing-related proteins with functional roles |
Q48044225 | Incorporating specificity into optimization: evaluation of SPA using CSAR 2014 and CASF 2013 benchmarks |
Q73013897 | Indices of differences of path lengths: novel topological descriptors derived from electronic interferences in graphs |
Q93383642 | Individually double minimum-distance definition of protein-RNA binding residues and application to structure-based prediction |
Q85888112 | Inflation of correlation in the pursuit of drug-likeness |
Q46808355 | Influence of conformation on the representation of small flexible molecules at low resolution: alignment of endothiapepsin ligands. |
Q92360805 | Influence of feature rankers in the construction of molecular activity prediction models |
Q89450851 | Influence of gauche effect on uncharged oxime reactivators for the reactivation of tabun-inhibited AChE: quantum chemical and steered molecular dynamics studies |
Q42922783 | Influence of metal cofactors and water on the catalytic mechanism of creatininase-creatinine in aqueous solution from molecular dynamics simulation and quantum study |
Q47276113 | Inhibition and substrate recognition--a computational approach applied to HIV protease |
Q90020262 | Inhibition of protein interactions: co-crystalized protein-protein interfaces are nearly as good as holo proteins in rigid-body ligand docking |
Q91624899 | Inhibitor discovery for the E. coli meningitis virulence factor IbeA from homology modeling and virtual screening |
Q72933425 | Inhibitors of prolyl endopeptidase: characterization of the pharmacophoric pattern using conformational analysis and 3D-QSAR |
Q57781255 | Insight into microtubule destabilization mechanism of 3,4,5-trimethoxyphenyl indanone derivatives using molecular dynamics simulation and conformational modes analysis |
Q42182937 | Insight into the modified Ibalizumab-human CD4 receptor interactions: using a computational binding free energy approach |
Q49722085 | Insight into the molecular mechanism of yeast acetyl-coenzyme A carboxylase mutants F510I, N485G, I69E, E477R, and K73R resistant to soraphen A. |
Q40911493 | Insights into resistance mechanism of the macrolide biosensor protein MphR(A) binding to macrolide antibiotic erythromycin by molecular dynamics simulation |
Q93173606 | Insights into the EGFR SAR of N-phenylquinazolin-4-amine-derivatives using quantum mechanical pairwise-interaction energies |
Q42906910 | Insights into the binding mode and mechanism of action of some atypical retinoids as ligands of the small heterodimer partner (SHP). |
Q37589537 | Insights into the binding of GABA to the insect RDL receptor from atomistic simulations: a comparison of models |
Q41629853 | Insights into the preferential order of strand exchange in the Cre/loxP recombinase system: impact of the DNA spacer flanking sequence and flexibility |
Q51330280 | Integrated in silico approaches for the prediction of Ames test mutagenicity. |
Q79804490 | Interaction force diagrams: new insight into ligand-receptor binding |
Q83025440 | Interaction of clozapine and its nitrenium ion with rat D2 dopamine receptors: in vitro binding and computational study |
Q39465346 | Interaction with specific HSP90 residues as a scoring function: validation in the D3R Grand Challenge 2015. |
Q43975038 | Interactions between anti-ErbB2 antibody A21 and the ErbB2 extracellular domain provide a basis for improving A21 affinity |
Q46155298 | Interactions between cycloguanil derivatives and wild type and resistance-associated mutant Plasmodium falciparum dihydrofolate reductases |
Q100428437 | Interactions of GF-17 derived from LL-37 antimicrobial peptide with bacterial membranes: a molecular dynamics simulation study |
Q46454089 | Interactions of peptide mimics of hyaluronic acid with the receptor for hyaluronan mediated motility (RHAMM). |
Q46159218 | Interactive essential dynamics |
Q85815370 | Intermediate states in the binding process of folic acid to folate receptor α: insights by molecular dynamics and metadynamics |
Q44109235 | Internally defined distances in 3D-quantitative structure-activity relationships |
Q94497353 | Interpretation of machine learning models using shapley values: application to compound potency and multi-target activity predictions |
Q30967921 | Interpreting physicochemical experimental data sets |
Q27681778 | Interrogating HIV integrase for compounds that bind- a SAMPL challenge |
Q41504204 | Introducing the 'active search' method for iterative virtual screening |
Q46157145 | Introduction to the special issue: Data Part 2: Experimental Data |
Q58108982 | Investigating cyclic peptides inhibiting CD2-CD58 interactions through molecular dynamics and molecular docking methods |
Q45994451 | Investigating the extension of pairwise distance pharmacophore measures to triplet-based descriptors. |
Q44895743 | Investigating the hydrogen-bond acceptor site of the nicotinic pharmacophore model: a computational and experimental study using epibatidine-related molecular probes |
Q30648918 | Investigation of classification methods for the prediction of activity in diverse chemical libraries |
Q47797187 | Investigation of structures and properties of cyclic peptide nanotubes by experiment and molecular dynamics. |
Q28246874 | Investigation of substituent effect of 1-(3,3-diphenylpropyl)-piperidinyl phenylacetamides on CCR5 binding affinity using QSAR and virtual screening techniques |
Q52643202 | Investigation of the binding mode of a novel cruzain inhibitor by docking, molecular dynamics, ab initio and MM/PBSA calculations. |
Q47581478 | Investigation of the intermolecular recognition mechanism between the E3 ubiquitin ligase Keap1 and substrate based on multiple substrates analysis. |
Q44167538 | Investigation of the metal binding site in methionine aminopeptidase by density functional theory. |
Q96957947 | Investigations on the E/Z-isomerism of neonicotinoids |
Q48263627 | Is scaffold hopping a reliable indicator for the ability of computational methods to identify structurally diverse active compounds? |
Q73604198 | Is the parallel or antiparallel beta-sheet more stable? A semiempirical study |
Q39684964 | Is there a future for computational chemistry in drug research? |
Q32103649 | IsoStar: a library of information about nonbonded interactions |
Q51062863 | JCAMD special series: statistics and molecular modeling. |
Q52013586 | Key issues in the computational simulation of GPCR function: representation of loop domains. |
Q28829862 | Kinetic barriers in the isomerization of substituted ureas: implications for computer-aided drug design |
Q37544381 | Knowing when to give up: early-rejection stratagems in ligand docking |
Q35621988 | Knowledge-guided docking: accurate prospective prediction of bound configurations of novel ligands using Surflex-Dock |
Q45964832 | LASSO-ligand activity by surface similarity order: a new tool for ligand based virtual screening. |
Q52346358 | LFER and CoMFA studies on optical resolution of alpha-alkyl alpha-aryloxy acetic acid methyl esters on DACH-DNB chiral stationary phase. |
Q44114180 | LUDI: rule-based automatic design of new substituents for enzyme inhibitor leads |
Q39453218 | Large scale free energy calculations for blind predictions of protein-ligand binding: the D3R Grand Challenge 2015. |
Q90716418 | Large-scale evaluation of cytochrome P450 2C9 mediated drug interaction potential with machine learning-based consensus modeling |
Q28266243 | Lead Finder docking and virtual screening evaluation with Astex and DUD test sets |
Q30410587 | Lead optimization mapper: automating free energy calculations for lead optimization |
Q33276455 | Lead-like, drug-like or "Pub-like": how different are they? |
Q45942993 | Learning epistatic interactions from sequence-activity data to predict enantioselectivity. |
Q49349899 | Leaving us with fond memories, smiles, SMILES and, alas, tears: a tribute to David Weininger, 1952-2016. |
Q30864260 | Lessons for fragment library design: analysis of output from multiple screening campaigns |
Q30275590 | Lessons learned from comparing molecular dynamics engines on the SAMPL5 dataset |
Q47359129 | Lessons learned from participating in D3R 2016 Grand Challenge 2: compounds targeting the farnesoid X receptor. |
Q38899445 | Lessons learned from the design of chemical space networks and opportunities for new applications |
Q47414331 | Lessons learned in induced fit docking and metadynamics in the Drug Design Data Resource Grand Challenge 2. |
Q51604998 | Let's get honest about sampling. |
Q33511462 | Let's not forget tautomers |
Q37464148 | Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands |
Q67508426 | Ligand atom partial charges assignment for complementary electrostatic potentials |
Q74505232 | Ligand binding affinity prediction by linear interaction energy methods |
Q47622535 | Ligand binding to domain-3 of human serum albumin: a chemometric analysis |
Q33291961 | Ligand design by a combinatorial approach based on modeling and experiment: application to HLA-DR4. |
Q40898209 | Ligand docking and binding site analysis with PyMOL and Autodock/Vina |
Q88019760 | Ligand efficiency metrics considered harmful |
Q44720168 | Ligand expansion in ligand-based virtual screening using relevance feedback |
Q80566722 | Ligand intramolecular motions in ligand-protein interaction: ALPHA, a novel dynamic descriptor and a QSAR study with extended steroid benchmark dataset |
Q50888328 | Ligand- and receptor-based docking with LiBELa. |
Q59489014 | Ligand-, structure- and pharmacophore-based molecular fingerprints: a case study on adenosine A1, A2A, A2B, and A3 receptor antagonists |
Q112693388 | Ligand-based and structure-based studies to develop predictive models for SARS-CoV-2 main protease inhibitors through the 3d-qsar.com portal |
Q38896131 | Ligand-based virtual screening under partial shape constraints |
Q45942240 | Ligand-biased ensemble receptor docking (LigBEnD): a hybrid ligand/receptor structure-based approach. |
Q44789723 | Ligand-guided optimization of CXCR4 homology models for virtual screening using a multiple chemotype approach. |
Q52066525 | Ligand-receptor docking with the Mining Minima optimizer. |
Q41283780 | Limiting assumptions in molecular modeling: electrostatics |
Q37972732 | Limiting assumptions in structure-based design: binding entropy |
Q80405218 | Linear and nonlinear functions on modeling of aqueous solubility of organic compounds by two structure representation methods |
Q28732338 | Lions and tigers and bears, oh my! Three barriers to progress in computer-aided molecular design |
Q34209458 | Lipophilicity in PK design: methyl, ethyl, futile |
Q34309917 | Local elevation: a method for improving the searching properties of molecular dynamics simulation. |
Q33819815 | Local neighborhood behavior in a combinatorial library context |
Q73013881 | Localization and quantification of hydrophobicity: the molecular free energy density (MolFESD) concept and its application to sweetness recognition |
Q52056851 | Locally linear embedding for dimensionality reduction in QSAR. |
Q92650826 | LogP prediction performance with the SMD solvation model and the M06 density functional family for SAMPL6 blind prediction challenge molecules |
Q48496292 | Looking forward into the next 25 years: the 25th anniversary issue of the Journal of Computer-Aided Molecular Design. |
Q52340891 | MAB, a generally applicable molecular force field for structure modelling in medicinal chemistry. |
Q44667593 | MCASE study of the multidrug resistance reversal activity of propafenone analogs |
Q78249919 | MCDOCK: a Monte Carlo simulation approach to the molecular docking problem |
Q36438656 | MENTHOR, a database system for the storage and retrieval of three-dimensional molecular structures and associated data searchable by substructural, biologic, physical, or geometric properties |
Q51652885 | MEPSIM: a computational package for analysis and comparison of molecular electrostatic potentials. |
Q35159035 | MLP Tools: a PyMOL plugin for using the molecular lipophilicity potential in computer-aided drug design |
Q82599858 | MM/GBSA and LIE estimates of host-guest affinities: dependence on charges and solvation model |
Q73315110 | MM3(96) parameterization for camptothecin analogs: an ab initio and molecular mechanics study |
Q87428553 | MOOCers and shakers and chemistry course takers |
Q37328051 | MOPAC: a semiempirical molecular orbital program |
Q73315115 | MS-WHIM, new 3D theoretical descriptors derived from molecular surface properties: a comparative 3D QSAR study in a series of steroids |
Q47742327 | MTD-ADJ: a multiconformational minimal topologic difference for determining bioactive conformers using adjusted biological activities |
Q45963769 | Machine learning of chemical reactivity from databases of organic reactions. |
Q45962041 | Machine learning study for the prediction of transdermal peptide. |
Q100505468 | Machine learning-accelerated quantum mechanics-based atomistic simulations for industrial applications |
Q90623080 | Macrocycle modeling in ICM: benchmarking and evaluation in D3R Grand Challenge 4 |
Q38326787 | Major versus minor groove DNA binding of a bisarginylporphyrin hybrid molecule: a molecular mechanics investigation |
Q39826842 | Making priors a priority |
Q53033714 | Managing bias in ROC curves. |
Q34667555 | Managing missing measurements in small-molecule screens. |
Q27943500 | Many InChIs and quite some feat |
Q40325980 | Mappability of drug-like space: towards a polypharmacologically competent map of drug-relevant compounds |
Q53332785 | Mapping of the interaction sites of galanthamine: a quantitative analysis through pairwise potentials and quantum chemistry. |
Q47604098 | Mapping protein pockets through their potential small-molecule binding volumes: QSCD applied to biological protein structures |
Q51007235 | Markov model-based polymer assembly from force field-parameterized building blocks. |
Q30791792 | Matching organic libraries with protein-substructures. |
Q91309178 | MathDL: mathematical deep learning for D3R Grand Challenge 4 |
Q63244985 | Mathematical deep learning for pose and binding affinity prediction and ranking in D3R Grand Challenges |
Q35037939 | Maximum common subgraph isomorphism algorithms for the matching of chemical structures |
Q50596276 | Maximum common substructure-based Tversky index: an asymmetric hybrid similarity measure. |
Q81437644 | Measuring CAMD technique performance: a virtual screening case study in the design of validation experiments |
Q38813544 | Measuring experimental cyclohexane-water distribution coefficients for the SAMPL5 challenge |
Q73010973 | Mechanism of action of aspartic proteinases: application of transition-state analogue theory |
Q54578344 | Mechanism of enhanced conversion of 1,2,3-trichloropropane by mutant haloalkane dehalogenase revealed by molecular modeling. |
Q50503846 | Mechanism of falcipain-2 inhibition by α,β-unsaturated benzo[1,4]diazepin-2-one methyl ester. |
Q80800641 | Mechanism of inhibition of human secretory phospholipase A2 by flavonoids: rationale for lead design |
Q42941894 | Mechanisms of amphipathic helical peptide denaturation by guanidinium chloride and urea: a molecular dynamics simulation study. |
Q85390872 | Mechanistic insights into protonation state as a critical factor in hFPPS enzyme inhibition |
Q30778898 | Megavariate analysis of hierarchical QSAR data |
Q96582928 | Meta-iPVP: a sequence-based meta-predictor for improving the prediction of phage virion proteins using effective feature representation |
Q44325908 | Metal complexes of chiral pentaazacrowns as conformational templates for beta-turn recognition |
Q30656461 | Methodological developments and strategies for a fast flexible superposition of drug-size molecules |
Q36373060 | Milestones in electron crystallography |
Q52078633 | Mixed QM/MM molecular electrostatic potentials. |
Q45372748 | Mixed learning algorithms and features ensemble in hepatotoxicity prediction. |
Q31112333 | Model based on GRID-derived descriptors for estimating CYP3A4 enzyme stability of potential drug candidates |
Q64910935 | Model of full-length HIV-1 integrase complexed with viral DNA as template for anti-HIV drug design. |
Q30395805 | Modeling & Informatics at Vertex Pharmaceuticals Incorporated: our philosophy for sustained impact. |
Q97675058 | Modeling Epac1 interactions with the allosteric inhibitor AM-001 by co-solvent molecular dynamics |
Q33647180 | Modeling activated states of GPCRs: the rhodopsin template |
Q60429767 | Modeling activated states of GPCRs: the rhodopsin template |
Q79280850 | Modeling and active site refinement for G protein-coupled receptors: application to the beta-2 adrenergic receptor |
Q52435960 | Modeling and conformation analysis of beta-cyclodextrin complexes. |
Q33270297 | Modeling chemical reactions for drug design |
Q51891051 | Modeling dimerizations of transmembrane proteins using Brownian dynamics simulations. |
Q30367791 | Modeling error in experimental assays using the bootstrap principle: understanding discrepancies between assays using different dispensing technologies. |
Q27316009 | Modeling ligand recognition at the P2Y12 receptor in light of X-ray structural information |
Q44866867 | Modeling lipophilicity from the distribution of electrostatic potential on a molecular surface |
Q34288765 | Modeling of enzyme-substrate complexes for the metalloproteases MMP-3, ADAM-9 and ADAM-10. |
Q51812818 | Modeling of peptides containing D-amino acids: implications on cyclization. |
Q68559274 | Modeling of protease I collagenolytic enzyme from the fiddler crab Uca pugilator |
Q83450537 | Modeling of the structure and interactions of the B. anthracis antitoxin, MoxX: deletion mutant studies highlight its modular structure and repressor function |
Q36503781 | Modeling the evolution of drug resistance in malaria |
Q33309679 | Modeling the inhibition of quadruple mutant Plasmodium falciparum dihydrofolate reductase by pyrimethamine derivatives |
Q40775373 | Modeling the interactions of a peptide-major histocompatibility class I ligand with its receptors. I. Recognition by two alpha beta T cell receptors |
Q42620546 | Modeling the interactions of a peptide-major histocompatibility class I ligand with its receptors. II. Cross-reaction between a monoclonal antibody and two alpha beta T cell receptors. |
Q34063351 | Modeling the pharmacodynamics of passive membrane permeability |
Q77428754 | Modelling a 3D structure for EgDf1 from Echinococcus granulosus: putative epitopes, phosphorylation motifs and ligand |
Q70790871 | Modelling and mutation studies on the histamine H1-receptor agonist binding site reveal different binding modes for H1-agonists: Asp116 (TM3) has a constitutive role in receptor stimulation |
Q74625546 | Modelling of adrenoceptor ligand targets based on novel medium- or macro-sized fused nitrogen heterocyclic systems |
Q68846654 | Modelling of alpha-lactalbumin from the known structure of hen egg white lysozyme using molecular dynamics |
Q58491302 | Modelling of carbohydrate–aromatic interactions: ab initio energetics and force field performance |
Q73798615 | Modelling of the binding site of the human m1 muscarinic receptor: experimental validation and refinement |
Q52289432 | Modelling steric effects in DNA-binding platinum(II)-am(m)ine complexes. |
Q71491544 | Modelling study of protein kinase inhibitors: binding mode of staurosporine and origin of the selectivity of CGP 52411 |
Q46758094 | Modelling the interaction of catecholamines with the alpha 1A adrenoceptor towards a ligand-induced receptor structure. |
Q68121890 | Models for the binding of amiodarone to the thyroid hormone receptor |
Q30371590 | Models of protein-ligand crystal structures: trust, but verify |
Q45943917 | Modern drug design: the implication of using artificial neuronal networks and multiple molecular dynamic simulations. |
Q44109231 | Modified AutoDock for accurate docking of protein kinase inhibitors |
Q47820341 | MolAlign: an algorithm for aligning multiple small molecules. |
Q42373393 | Molden 2.0: quantum chemistry meets proteins |
Q50694018 | Molden: a pre- and post-processing program for molecular and electronic structures. |
Q82663150 | Molecular and structural determinants of adamantyl susceptibility to HLA-DRs allelic variants: an in silico approach to understand the mechanism of MLEs |
Q48043854 | Molecular basis of P450 OleTJE: an investigation of substrate binding mechanism and major pathways. |
Q52217017 | Molecular basis of quantitative structure-properties relationships (QSPR): a quantum similarity approach. |
Q46628594 | Molecular design of two sterol 14alpha-demethylase homology models and their interactions with the azole antifungals ketoconazole and bifonazole |
Q68329869 | Molecular determinants in the bioactivation of the dopaminergic neurotoxin N-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) |
Q39725235 | Molecular docking and 3D-quantitative structure activity relationship analyses of peptidyl vinyl sulfones: Plasmodium Falciparum cysteine proteases inhibitors. |
Q43248352 | Molecular docking and QSAR of aplyronine A and analogues: potent inhibitors of actin |
Q39325646 | Molecular docking performance evaluated on the D3R Grand Challenge 2015 drug-like ligand datasets |
Q44115744 | Molecular docking studies of a group of hydroxamate inhibitors with gelatinase-A by molecular dynamics |
Q45247134 | Molecular docking studies on tetrahydroimidazo-[4,5,1-jk][1,4]-benzodiazepinone (TIBO) derivatives as HIV-1 NNRT inhibitors |
Q83943548 | Molecular dynamics and docking simulations as a proof of high flexibility in E. coli FabH and its relevance for accurate inhibitor modeling |
Q59576097 | Molecular dynamics characterization of the SAMHD1 Aicardi–Goutières Arg145Gln mutant: structural determinants for the impaired tetramerization |
Q38417439 | Molecular dynamics modeling the synthetic and biological polymers interactions pre-studied via docking: anchors modified polyanions interference with the HIV-1 fusion mediator |
Q43979135 | Molecular dynamics of 5-HT1A and 5-HT2A serotonin receptors with methylated buspirone analogues. |
Q60998748 | Molecular dynamics of Mycobacterium tuberculosis KasA: implications for inhibitor and substrate binding and consequences for drug design |
Q43703243 | Molecular dynamics simulation and linear interaction energy study of D-Glu-based inhibitors of the MurD ligase |
Q69464713 | Molecular dynamics simulation as a complement to diffraction in the study of disorder in crystals |
Q33481737 | Molecular dynamics simulation of S100B protein to explore ligand blockage of the interaction with p53 protein |
Q73041072 | Molecular dynamics simulation of cyclosophoroheptadecaose (Cys-A) |
Q30863658 | Molecular dynamics simulation of halogen bonding mimics experimental data for cathepsin L inhibition |
Q47655089 | Molecular dynamics simulation of matrix metalloproteinase 2: fluctuations and time evolution of recognition pockets |
Q55042750 | Molecular dynamics simulation of the human adenosine A3 receptor: agonist induced conformational changes of Trp243. |
Q53859885 | Molecular dynamics simulation of the ligand binding domain of mGluR1 in response to agonist and antagonist binding. |
Q57138268 | Molecular dynamics simulation of the renin inhibitor H142 in water |
Q46441558 | Molecular dynamics simulation study of PTP1B with allosteric inhibitor and its application in receptor based pharmacophore modeling |
Q51678306 | Molecular dynamics simulations and structure-based network analysis reveal structural and functional aspects of G-protein coupled receptor dimer interactions. |
Q36852484 | Molecular dynamics simulations give insight into D-glucose dioxidation at C2 and C3 by Agaricus meleagris pyranose dehydrogenase |
Q36461086 | Molecular dynamics simulations of cyclosporin A: the crystal structure and dynamic modelling of a structure in apolar solution based on NMR data |
Q38782160 | Molecular dynamics simulations of halide glasses |
Q46642485 | Molecular dynamics simulations of ligand-induced backbone conformational changes in the binding site of the periplasmic lysine-, arginine-, ornithine-binding protein. |
Q72816267 | Molecular dynamics simulations of oligonucleotides in solution: visualization of intrinsic curvature |
Q83978827 | Molecular dynamics simulations of pro-apoptotic BH3 peptide helices in aqueous medium: relationship between helix stability and their binding affinities to the anti-apoptotic protein Bcl-X(L) |
Q79280859 | Molecular dynamics simulations on the inhibition of cyclin-dependent kinases 2 and 5 in the presence of activators |
Q58327982 | Molecular dynamics studies of α-helix stability in fibril-forming peptides |
Q47604133 | Molecular dynamics study of peptide segments of the BH3 domain of the proapoptotic proteins Bak, Bax, Bid and Hrk bound to the Bcl-xL and Bcl-2 proteins. |
Q35623525 | Molecular dynamics to enhance structure-based virtual screening on cathepsin B. |
Q36819901 | Molecular dynamics: deciphering the data |
Q78043568 | Molecular electrostatic potentials as input for the alignment of HIV-1 integrase inhibitors in 3D QSAR |
Q38828100 | Molecular graph convolutions: moving beyond fingerprints. |
Q46698360 | Molecular insight into γ-γ tubulin lateral interactions within the γ-tubulin ring complex (γ-TuRC). |
Q88052698 | Molecular insight of isotypes specific β-tubulin interaction of tubulin heterodimer with noscapinoids |
Q62631468 | Molecular insight on the non-covalent interactions between carbapenems and l,d-transpeptidase 2 from Mycobacterium tuberculosis: ONIOM study |
Q68248935 | Molecular level model for the agonist/antagonist selectivity of the 1,4-dihydropyridine calcium channel receptor |
Q52379524 | Molecular lipophilicity potential, a tool in 3D QSAR: method and applications. |
Q52544096 | Molecular mechanics calculations on deaminooxytocin and on deamino-arginine-vasopressin and its analogues. |
Q51325445 | Molecular mechanism of R-bicalutamide switching from androgen receptor antagonist to agonist induced by amino acid mutations using molecular dynamics simulations and free energy calculation. |
Q44667602 | Molecular model of the neural dopamine transporter |
Q56784778 | Molecular modeling and bioinformatical analysis of the antibacterial target enzyme MurA from a drug design perspective |
Q58846797 | Molecular modeling and dynamics of neuropeptide Y |
Q63916872 | Molecular modeling of a putative antagonist binding site on helix III of the β-adrenoceptor |
Q43909373 | Molecular modeling of class I and II alleles of the major histocompatibility complex in Salmo salar |
Q73604191 | Molecular modeling of cytochrome P450 3A4 |
Q44087626 | Molecular modeling of interactions of the non-peptide antagonist YM087 with the human vasopressin V1a, V2 receptors and with oxytocin receptors. |
Q30403920 | Molecular modeling of protein structure and function: a bioinformatic approach |
Q77336349 | Molecular modeling of the human vasopressin V2 receptor/agonist complex |
Q41061215 | Molecular modeling of the intestinal bile acid carrier: a comparative molecular field analysis study |
Q48633791 | Molecular modeling of the neurophysin I/oxytocin complex. |
Q30363533 | Molecular modeling on pyruvate phosphate dikinase of Entamoeba histolytica and in silico virtual screening for novel inhibitors. |
Q45150390 | Molecular modeling studies on the urease active site and the enzyme-catalyzed urea hydrolysis |
Q44352483 | Molecular modeling study of the differential ligand-receptor interaction at the mu, delta and kappa opioid receptors |
Q39025426 | Molecular modeling study of the induced-fit effect on kinase inhibition: the case of fibroblast growth factor receptor 3 (FGFR3). |
Q77622443 | Molecular modeling study of tubulosine and other related ipecac alkaloids |
Q71483776 | Molecular modelling and conformational analysis of a GABAB antagonist |
Q33389197 | Molecular modelling evaluation of the cytotoxic activity of podophyllotoxin analogues |
Q39568002 | Molecular modelling in design of crop protection chemicals |
Q68665073 | Molecular modelling of poly(aryl ether ketones). I. Aryl..aryl interactions in crystal structures |
Q31131948 | Molecular modelling prediction of ligand binding site flexibility |
Q67865138 | Molecular modelling studies and the chromatographic behaviour of oxiracetam and some closely related molecules |
Q57948799 | Molecular modelling studies of substrate binding to the lipase from Rhizomucor miehei |
Q47796479 | Molecular modelling studies on the ORL1-receptor and ORL1-agonists |
Q77763142 | Molecular moment similarity between clozapine and substituted [(4-phenylpiperazinyl)-methyl] benzamides: selective dopamine D4 agonists |
Q37843834 | Molecular motions in drug design: the coming age of the metadynamics method |
Q52838984 | Molecular recognition of thiaclopride by Aplysia californica AChBP: new insights from a computational investigation. |
Q81575893 | Molecular shape and electrostatics in the encoding of relevant chemical information |
Q68665067 | Molecular similarity: the introduction of flexible fitting |
Q54508458 | Molecular simulation and docking studies of Gal1p and Gal3p proteins in the presence and absence of ligands ATP and galactose: implication for transcriptional activation of GAL genes. |
Q40415323 | Molecular simulation assisted identification of Ca(2+) binding residues in TMEM16A. |
Q39676629 | Molecular simulation methods in drug discovery: a prospective outlook |
Q43480285 | Molecular structure matching by simulated annealing. I. A comparison between different cooling schedules |
Q68665077 | Molecular structure matching by simulated annealing. II. An exploration of the evolution of configuration landscape problems |
Q52453058 | Molecular structure matching by simulated annealing. III. The incorporation of null correspondences into the matching problem. |
Q44087939 | Molecular structure matching by simulated annealing. IV. Classification of atom correspondences in sets of dissimilar molecules |
Q52321861 | Molecular surface-volume and property matching to superpose flexible dissimilar molecules. |
Q98565059 | Monomer structure fingerprints: an extension of the monomer composition version for peptide databases |
Q93023479 | Monte Carlo on the manifold and MD refinement for binding pose prediction of protein-ligand complexes: 2017 D3R Grand Challenge |
Q30847414 | Morphological similarity: a 3D molecular similarity method correlated with protein-ligand recognition |
Q89724286 | Multi-phase Boltzmann weighting: accounting for local inhomogeneity in molecular simulations of water-octanol partition coefficients in the SAMPL6 challenge |
Q115732710 | Multi-task convolutional neural networks for predicting in vitro clearance endpoints from molecular images |
Q91438187 | Multi-task generative topographic mapping in virtual screening |
Q44361690 | Multi-task learning for pKa prediction |
Q70790863 | Multiconformational composite molecular potential fields in the analysis of drug action. I. Methodology and first evaluation using 5-HT and histamine action as examples |
Q30875856 | Multiobjective optimization of combinatorial libraries |
Q52260133 | Multiple automatic base selection: protein-ligand docking based on incremental construction without manual intervention. |
Q84230608 | Multiple ligand docking by Glide: implications for virtual second-site screening |
Q46628596 | Multiple ligand-binding modes in bacterial R67 dihydrofolate reductase |
Q80697151 | Multiple protein structures and multiple ligands: effects on the apparent goodness of virtual screening results |
Q38670015 | Multiple receptor-ligand based pharmacophore modeling and molecular docking to screen the selective inhibitors of matrix metalloproteinase-9 from natural products |
Q58137155 | Multivariate analysis of experimental and computational descriptors of molecular lipophilicity |
Q42256315 | Mutation effects of neuraminidases and their docking with ligands: a molecular dynamics and free energy calculation study |
Q100729202 | Mutation-mediated influences on binding of anaplastic lymphoma kinase to crizotinib decoded by multiple replica Gaussian accelerated molecular dynamics |
Q58114859 | Mycobacterium tuberculosis serine/threonine protein kinases: structural information for the design of their specific ATP-competitive inhibitors |
Q34871486 | NMR-assisted computational studies of peptidomimetic inhibitors bound in the hydrophobic pocket of HIV-1 glycoprotein 41. |
Q38302873 | NMR-restrained docking of a peptidic inhibitor to the N-terminal domain of the phosphoenolpyruvate:sugar phosphotransferase enzyme I. |
Q90814699 | Network-based piecewise linear regression for QSAR modelling |
Q67891436 | Networks |
Q51890925 | Neural network-based QSAR and insecticide discovery: spinetoram. |
Q43844943 | Neuronal nicotinic receptor agonists: a multi-approach development of the pharmacophore |
Q56978998 | New 3D molecular descriptors: the WHIM theory and QSAR applications |
Q57460266 | New approaches to QSAR: Neural networks and machine learning |
Q47276095 | New atom-type-based AI topological indices: application to QSPR studies of aldehydes and ketones |
Q53851119 | New designs for MRI contrast agents. |
Q51638309 | New developments in PEST shape/property hybrid descriptors. |
Q43021736 | New insight in the structural features of haloadaptation in α-amylases from halophilic Archaea following homology modeling strategy: folded and stable conformation maintained through low hydrophobicity and highly negative charged surface |
Q85651588 | New insights from molecular dynamic simulation studies of the multiple binding modes of a ligand with G-quadruplex DNA |
Q43047168 | New insights into flavivirus biology: the influence of pH over interactions between prM and E proteins. |
Q50576810 | New insights into human farnesyl pyrophosphate synthase inhibition by second-generation bisphosphonate drugs. |
Q40177843 | New insights into the stereochemical requirements of the bradykinin B2 receptor antagonists binding |
Q45261846 | New leads for selective GSK-3 inhibition: pharmacophore mapping and virtual screening studies |
Q78683448 | New methods in predictive metabolism |
Q46652883 | New molecular shape descriptors: application in database screening |
Q69475767 | New products and rumors of new products |
Q102370437 | Non-equilibrium approach for binding free energies in cyclodextrins in SAMPL7: force fields and software |
Q91455965 | Non-zero Lennard-Jones parameters for the Toukan-Rahman water model: more accurate calculations of the solvation free energy of organic substances |
Q70661459 | Nonlinear dependence in comparative molecular field analysis |
Q91289731 | Nonparametric chemical descriptors for the calculation of ligand-biopolymer affinities with machine-learning scoring functions |
Q52382622 | Novel algorithms for searching conformational space. |
Q35026098 | Novel anti-plasmodial hits identified by virtual screening of the ZINC database |
Q51943955 | Novel approach to evolutionary neural network based descriptor selection and QSAR model development. |
Q58050992 | Novel inhibitors to Taenia solium Cu/Zn superoxide dismutase identified by virtual screening |
Q27670945 | Novel isoquinolone PDK1 inhibitors discovered through fragment-based lead discovery |
Q96819168 | Novel phosphatidylinositol 4-kinases III beta (PI4KIIIβ) inhibitors discovered by virtual screening using free energy models |
Q72393568 | Nucleotide-binding properties of adenylate kinase from Escherichia coli: a molecular dynamics study in aqueous and vacuum environments |
Q41874011 | OVID and SUPER: Two overlap programs for drug design |
Q30404061 | Obituary: Corwin H. Hansch |
Q45944054 | Obituary: Toshio Fujita, QSAR pioneer. |
Q50957370 | Objective models for steroid binding sites of human globulins. |
Q92137312 | Octanol-water partition coefficient measurements for the SAMPL6 blind prediction challenge |
Q30485257 | Of possible cheminformatics futures |
Q43084203 | On homology modeling of the M₂ muscarinic acetylcholine receptor subtype. |
Q91934947 | On the activation and deactivation pathways of the Lck kinase domain: a computational study |
Q57278502 | On the active site of mononuclear B1 metallo β-lactamases: a computational study |
Q30844876 | On the detection of multiple-binding modes of ligands to proteins, from biological, structural, and modeling data |
Q71347769 | On the electrostatic and steric similarity of lactam compounds and the natural substrate for bacterial cell-wall biosynthesis |
Q38971591 | On the fly estimation of host-guest binding free energies using the movable type method: participation in the SAMPL5 blind challenge |
Q80865383 | On the importance of topological descriptors in understanding structure-property relationships |
Q46375027 | On the interpretation and interpretability of quantitative structure-activity relationship models |
Q73572205 | On the molecular interaction between lactoferrin and the dye Red HE-3b. A novel approach for docking a charged and highly flexible molecule to protein surfaces |
Q126276684 | On the relevance of query definition in the performance of 3D ligand-based virtual screening |
Q44485548 | On the representation of electrostatic fields around ab initio charge distributions |
Q52417243 | On the suitability of semiempirical calculations as sources of force field parameters. |
Q72593914 | On the use of LUDI to search the Fine Chemicals Directory for ligands of proteins of known three-dimensional structure |
Q70233006 | On the use of isovalued surfaces to determine molecule shape and reaction pathways |
Q43979139 | One site fits both: a model for the ternary complex of folate + NADPH in R67 dihydrofolate reductase, a D2 symmetric enzyme |
Q28530221 | Online chemical modeling environment (OCHEM): web platform for data storage, model development and publishing of chemical information |
Q51544926 | Open3DALIGN: an open-source software aimed at unsupervised ligand alignment. |
Q37522061 | OpenCDLig: a free web application for sharing resources about cyclodextrin/ligand complexes. |
Q53493142 | Opening mechanism of adenylate kinase can vary according to selected molecular dynamics force field. |
Q42691078 | Optimal affinity ranking for automated virtual screening validated in prospective D3R grand challenges. |
Q36116506 | Optimal strategies for virtual screening of induced-fit and flexible target in the 2015 D3R Grand Challenge |
Q91248939 | Optimisation of human VH domain antibodies specific to Mycobacterium tuberculosis heat shock protein (HSP16.3) |
Q28264356 | Optimization of CAMD techniques 3. Virtual screening enrichment studies: a help or hindrance in tool selection? |
Q43701183 | Optimization of a mathematical topological pattern for the prediction of antihistaminic activity |
Q28294267 | Optimization of biaryl piperidine and 4-amino-2-biarylurea MCH1 receptor antagonists using QSAR modeling, classification techniques and virtual screening |
Q37111553 | Optimizing Dvl PDZ domain inhibitor by exploring chemical space. |
Q36858968 | Optimizing doped libraries by using genetic algorithms |
Q67981520 | Orientation and structure-building role of the water molecules bound at the contact surface of the dihydrofolate reductase-methotrexate complex |
Q46841895 | Orientational sampling and rigid-body minimization in molecular docking revisited: on-the-fly optimization and degeneracy removal |
Q30363018 | Outliers in SAR and QSAR: 2. Is a flexible binding site a possible source of outliers? |
Q30360124 | Outliers in SAR and QSAR: is unusual binding mode a possible source of outliers? |
Q38818618 | Overview of the SAMPL5 host-guest challenge: Are we doing better? |
Q58556734 | Overview of the SAMPL6 host-guest binding affinity prediction challenge |
Q111149480 | Overview of the SAMPL6 pKa challenge: evaluating small molecule microscopic and macroscopic pKa predictions |
Q84129411 | Overview of the perspectives devoted to tautomerism in molecular design |
Q45897104 | Oxygen-containing fragments in natural products |
Q51500631 | PAPQMD parametrization of molecular systems with cyclopropyl rings: conformational study of homopeptides constituted by 1-aminocyclopropane-1-carboxylic acid. |
Q34584338 | PHASE: a new engine for pharmacophore perception, 3D QSAR model development, and 3D database screening: 1. Methodology and preliminary results |
Q81055528 | PLASS: protein-ligand affinity statistical score--a knowledge-based force-field model of interaction derived from the PDB |
Q48474613 | PLS modelling of structure-activity relationships of catechol O-methyltransferase inhibitors |
Q36703753 | PRO-LIGAND: an approach to de novo molecular design. 1. Application to the design of organic molecules |
Q52346352 | PRO-LIGAND: an approach to de novo molecular design. 3. A genetic algorithm for structure refinement. |
Q48785859 | PRODRG, a program for generating molecular topologies and unique molecular descriptors from coordinates of small molecules. |
Q36763967 | PROGEN: an automated modelling algorithm for the generation of complete protein structures from the alpha-carbon atomic coordinates |
Q36682015 | PRO_LIGAND: an approach to de novo molecular design. 4. Application to the design of peptides |
Q36794957 | PRO_LIGAND: an approach to de novo molecular design. 6. Flexible fitting in the design of peptides |
Q36852276 | PRO_SELECT: combining structure-based drug design and combinatorial chemistry for rapid lead discovery. 1. Technology |
Q60194845 | Parameterization of a coarse-grained model of cholesterol with point-dipole electrostatics |
Q46345653 | Parameterization of an empirical model for the prediction of n-octanol, alkane and cyclohexane/water as well as brain/blood partition coefficients |
Q73041078 | Parametrization of a force field for metals complexed to biomacromolecules: applications to Fe(II), Cu(II) and Pb(II) |
Q39373257 | Partition coefficients for the SAMPL5 challenge using transfer free energies. |
Q52227962 | Patenting computer-designed peptides. |
Q45110662 | Pattern recognition display methods for the analysis of computed molecular properties |
Q69724835 | Pattern recognition study of QSAR substituent descriptors |
Q98647314 | Pattern-free generation and quantum mechanical scoring of ring-chain tautomers |
Q39301033 | Pep-Calc.com: a set of web utilities for the calculation of peptide and peptoid properties and automatic mass spectral peak assignment |
Q46016087 | Peptide mimetics as enzyme inhibitors: use of free energy perturbation calculations to evaluate isosteric replacement for amide bonds in a potent HIV protease inhibitor. |
Q91063630 | Performance evaluation of molecular docking and free energy calculations protocols using the D3R Grand Challenge 4 dataset |
Q38613029 | Performance of HADDOCK and a simple contact-based protein-ligand binding affinity predictor in the D3R Grand Challenge 2. |
Q47797655 | Performance of multiple docking and refinement methods in the pose prediction D3R prospective Grand Challenge 2016. |
Q46892685 | Performance of the IEF-MST solvation continuum model in the SAMPL2 blind test prediction of hydration and tautomerization free energies. |
Q45110960 | Performance of the SMD and SM8 models for predicting solvation free energy of neutral solutes in methanol, dimethyl sulfoxide and acetonitrile |
Q89949715 | Performing solvation free energy calculations in LAMMPS using the decoupling approach |
Q51937689 | Permuting input for more effective sampling of 3D conformer space. |
Q47796440 | Peroxisome proliferator-activated receptors target family landscape: a chemometrical approach to ligand selectivity based on protein binding site analysis |
Q67981523 | Perspectives in QSAR: computer chemistry and pattern recognition |
Q47796455 | Pharmacophore and receptor models for neurokinin receptors |
Q58748185 | Pharmacophore development for antagonists at α1 adrenergic receptor subtypes |
Q68121896 | Pharmacophore identification by molecular modeling and chemometrics: the case of HMG-CoA reductase inhibitors |
Q80260250 | Pharmacophore model for bile acids recognition by the FPR receptor |
Q57010606 | Pharmacophore modeling and parallel screening for PPAR ligands |
Q35395528 | Pharmacophore modeling improves virtual screening for novel peroxisome proliferator-activated receptor-gamma ligands |
Q74006401 | Pharmacophore modelling of structurally unusual diltiazem mimics at L-type calcium channels |
Q49177235 | Pharmacophore refinement of gpIIb/IIIa antagonists based on comparative studies of antiadhesive cyclic and acyclic RGD peptides. |
Q36124531 | Pharmacophore-based virtual screening, biological evaluation and binding mode analysis of a novel protease-activated receptor 2 antagonist |
Q33744181 | Pharmacophore-driven identification of PPARγ agonists from natural sources. |
Q97549635 | Phenylalkylamines in calcium channels: computational analysis of experimental structures |
Q48540899 | Philip S. Magee: a life in QSAR. |
Q43012038 | Phosphorylation and ATP-binding induced conformational changes in the PrkC, Ser/Thr kinase from B. subtilis |
Q52311354 | Placement of medium-sized molecular fragments into active sites of proteins. |
Q96349424 | Plausible compounds drawn from plants as curative agents for neurodegeneration: An in-silico approach |
Q39647348 | Pose prediction and virtual screening performance of GOLD scoring functions in a standardized test. |
Q31023601 | Possibilities for transfer of relevant data without revealing structural information |
Q45942180 | Possible allosteric interactions of monoindazole-substituted P2 cyclic urea analogues with wild-type and mutant HIV-1 protease. |
Q48053795 | Practical computational toolkits for dendrimers and dendrons structure design |
Q43520105 | Predicted 3D structures of olfactory receptors with details of odorant binding to OR1G1. |
Q36268544 | Predicting DPP-IV inhibitors with machine learning approaches. |
Q80865387 | Predicting allergic contact dermatitis: a hierarchical structure-activity relationship (SAR) approach to chemical classification using topological and quantum chemical descriptors |
Q43786256 | Predicting anti-HIV activity: computational approach using a novel topological descriptor |
Q44325902 | Predicting anticonvulsant activity of benzamides/benzylamines: computational approach using topological descriptors |
Q36645023 | Predicting binding affinities of host-guest systems in the SAMPL3 blind challenge: the performance of relative free energy calculations |
Q39310536 | Predicting binding poses and affinities for protein - ligand complexes in the 2015 D3R Grand Challenge using a physical model with a statistical parameter estimation. |
Q90046659 | Predicting binding poses and affinity ranking in D3R Grand Challenge using PL-PatchSurfer2.0. |
Q51477064 | Predicting bioactive conformations and binding modes of macrocycles. |
Q39449581 | Predicting cyclohexane/water distribution coefficients for the SAMPL5 challenge using MOSCED and the SMD solvation model |
Q47679935 | Predicting drug pharmacokinetic properties using molecular interaction fields and SIMCA. |
Q47600233 | Predicting drug-induced liver injury in human with Naïve Bayes classifier approach |
Q34108242 | Predicting hydration free energies of polychlorinated aromatic compounds from the SAMPL-3 data set with FiSH and LIE models |
Q84014403 | Predicting hydration free energies using all-atom molecular dynamics simulations and multiple starting conformations |
Q34351290 | Predicting hydration free energies with a hybrid QM/MM approach: an evaluation of implicit and explicit solvation models in SAMPL4 |
Q48887633 | Predicting hydration free energies with chemical accuracy: the SAMPL4 challenge. |
Q79273419 | Predicting infinite dilution activity coefficients of organic compounds in water by quantum-connectivity descriptors |
Q57167810 | Predicting ligand binding affinity using on- and off-rates for the SAMPL6 SAMPLing challenge |
Q52244281 | Predicting nucleic acid torsion angle values using artificial neural networks. |
Q89460097 | Predicting octanol/water partition coefficients for the SAMPL6 challenge using the SM12, SM8, and SMD solvation models |
Q92787012 | Predicting partition coefficients of drug-like molecules in the SAMPL6 challenge with Drude polarizable force fields |
Q91248938 | Predicting protein-ligand binding modes for CELPP and GC3: workflows and insight |
Q96349416 | Predicting reactivity to drug metabolism: beyond P450s-modelling FMOs and UGTs |
Q41616028 | Predicting relative binding affinities of non-peptide HIV protease inhibitors with free energy perturbation calculations |
Q74336775 | Predicting sequences and structures of MHC-binding peptides: a computational combinatorial approach |
Q92006812 | Predicting skin permeability using the 3D-RISM-KH theory based solvation energy descriptors for a diverse class of compounds |
Q44608034 | Predicting targets of compounds against neurological diseases using cheminformatic methodology. |
Q47980758 | Predicting the affinity of Farnesoid X Receptor ligands through a hierarchical ranking protocol: a D3R Grand Challenge 2 case study. |
Q36590236 | Predicting the effects of amino acid replacements in peptide hormones on their binding affinities for class B GPCRs and application to the design of secretin receptor antagonists |
Q67976695 | Predicting the product specificity and coupling of cytochrome P450cam |
Q53185669 | Predicting the relative binding affinity of mineralocorticoid receptor antagonists by density functional methods. |
Q37549125 | Predicting water-to-cyclohexane partitioning of the SAMPL5 molecules using dielectric balancing of force fields |
Q40775415 | Prediction and analysis of structure, stability and unfolding of thermolysin-like proteases |
Q50978597 | Prediction and interpretation of the lipophilicity of small peptides. |
Q90797642 | Prediction of CB[8] host-guest binding free energies in SAMPL6 using the double-decoupling method |
Q91347521 | Prediction of P-glycoprotein inhibitors with machine learning classification models and 3D-RISM-KH theory based solvation energy descriptors |
Q51709682 | Prediction of SAMPL2 aqueous solvation free energies and tautomeric ratios using the SM8, SM8AD, and SMD solvation models. |
Q36060565 | Prediction of SAMPL3 host-guest affinities with the binding energy distribution analysis method (BEDAM). |
Q34249481 | Prediction of SAMPL3 host-guest binding affinities: evaluating the accuracy of generalized force-fields |
Q87307951 | Prediction of SAMPL4 host-guest binding affinities using funnel metadynamics |
Q28285760 | Prediction of binding constants of protein ligands: a fast method for the prioritization of hits obtained from de novo design or 3D database search programs |
Q47625069 | Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling. |
Q48114822 | Prediction of blood-brain barrier permeation using quantum chemically derived information |
Q39122338 | Prediction of blood-brain partitioning using Monte Carlo simulations of molecules in water |
Q48054774 | Prediction of cyclohexane-water distribution coefficient for SAMPL5 drug-like compounds with the QMPFF3 and ARROW polarizable force fields. |
Q31125942 | Prediction of cyclohexane-water distribution coefficients for the SAMPL5 data set using molecular dynamics simulations with the OPLS-AA force field. |
Q31117677 | Prediction of cyclohexane-water distribution coefficients with COSMO-RS on the SAMPL5 data set. |
Q34267386 | Prediction of free energies of hydration with COSMO-RS on the SAMPL3 data set. |
Q30732705 | Prediction of free energies of hydration with COSMO-RS on the SAMPL4 data set. |
Q58048746 | Prediction of hydration free energies for aliphatic and aromatic chloro derivatives using molecular dynamics simulations with the OPLS-AA force field |
Q30766874 | Prediction of hydration free energies for the SAMPL4 data set with the AMOEBA polarizable force field. |
Q58048721 | Prediction of hydration free energies for the SAMPL4 diverse set of compounds using molecular dynamics simulations with the OPLS-AA force field |
Q44882015 | Prediction of in vitro metabolic stability of calcitriol analogs by QSAR. |
Q51967777 | Prediction of inter-residue contacts map based on genetic algorithm optimized radial basis function neural network and binary input encoding scheme. |
Q99637607 | Prediction of ligand binding mode among multiple cross-docking poses by molecular dynamics simulations |
Q92787028 | Prediction of octanol-water partition coefficients for the SAMPL6-[Formula: see text] molecules using molecular dynamics simulations with OPLS-AA, AMBER and CHARMM force fields |
Q88917747 | Prediction of partition and distribution coefficients in various solvent pairs with COSMO-RS |
Q39394471 | Prediction of peptide binding to a major histocompatibility complex class I molecule based on docking simulation |
Q51960741 | Prediction of plasma protein binding of drugs using Kier-Hall valence connectivity indices and 4D-fingerprint molecular similarity analyses. |
Q37761334 | Prediction of protein-ligand binding affinity by free energy simulations: assumptions, pitfalls and expectations |
Q45965982 | Prediction of standard Gibbs energies of the transfer of peptide anions from aqueous solution to nitrobenzene based on support vector machine and the heuristic method. |
Q39887697 | Prediction of tautomer ratios by embedded-cluster integral equation theory |
Q45756379 | Prediction of the binding mode of N2-phenylguanine derivative inhibitors to herpes simplex virus type 1 thymidine kinase |
Q34662381 | Prediction of the binding site of 1-benzyl-4-[(5,6-dimethoxy-1-indanon-2-yl)methyl]piperidine in acetylcholinesterase by docking studies with the SYSDOC program |
Q49177167 | Prediction of the binding sites of huperzine A in acetylcholinesterase by docking studies. |
Q91498593 | Prediction of the n-octanol/water partition coefficients in the SAMPL6 blind challenge from MST continuum solvation calculations |
Q70413433 | Prediction of the three-dimensional structure of the enzymatic domain of t-PA |
Q73315105 | Prediction of the three-dimensional structure of the human Fas receptor by comparative molecular modeling |
Q45966205 | Prediction of the tissue/blood partition coefficients of organic compounds based on the molecular structure using least-squares support vector machines. |
Q45739100 | Prediction of trypsin/molecular fragment binding affinities by free energy decomposition and empirical scores |
Q43114172 | Predictions of hydration free energies from continuum solvent with solute polarizable models: the SAMPL2 blind challenge |
Q44254255 | Predictive QSAR modeling based on diversity sampling of experimental datasets for the training and test set selection |
Q38688678 | Predictive cartography of metal binders using generative topographic mapping |
Q96349427 | Predictive potential of eigenvalue-based topological molecular descriptors |
Q51966056 | Preface to the special issue in memory of Phil Magee. |
Q30995883 | Presenting data in such a fashion that they can be used by other scientists |
Q99610230 | ProIn-Fuse: improved and robust prediction of proinflammatory peptides by fusing of multiple feature representations |
Q44201458 | ProSeg: a database of local structures of protein segments. |
Q85010731 | Proceedings of the Third Annual Statistical Assessment of the Modeling of Proteins and Ligands (SAMPL) Challenge and Workshop. June 2009. Montreal, Canada |
Q42860793 | Prodrugs of aza nucleosides based on proton transfer reaction |
Q30855791 | Property distribution of drug-related chemical databases. |
Q36092809 | Prospective evaluation of shape similarity based pose prediction method in D3R Grand Challenge 2015. |
Q39022371 | Prospective virtual screening for novel p53-MDM2 inhibitors using ultrafast shape recognition |
Q33241709 | Protein Alpha Shape (PAS) Dock: a new gaussian-based score function suitable for docking in homology modelled protein structures |
Q44490744 | Protein Alpha Shape Similarity Analysis (PASSA): a new method for mapping protein binding sites. Application in the design of a selective inhibitor of tyrosine kinase 2. |
Q45390949 | Protein Data Bank Japan (PDBj): an interview with Haruki Nakamura of Osaka University by Wendy A. Warr |
Q44012277 | Protein and ligand preparation: parameters, protocols, and influence on virtual screening enrichments |
Q83139531 | Protein farnesyltransferase: flexible docking studies on inhibitors using computational modeling |
Q40775421 | Protein fold recognition |
Q40518742 | Protein fragment reconstruction using various modeling techniques |
Q62761925 | Protein ligand docking based on empirical method for binding affinity estimation |
Q50872388 | Protein pocket and ligand shape comparison and its application in virtual screening. |
Q32065414 | Protein secondary structure templates derived from bioactive natural products. Combinatorial chemistry meets structure-based design |
Q30351756 | Protein structure prediction by tempering spatial constraints. |
Q47655078 | Protein-ligand binding free energy estimation using molecular mechanics and continuum electrostatics. Application to HIV-1 protease inhibitors |
Q47382465 | Protein-ligand docking using FFT based sampling: D3R case study |
Q36788480 | Protein-ligand docking with multiple flexible side chains |
Q50051009 | Protein-ligand interfaces are polarized: discovery of a strong trend for intermolecular hydrogen bonds to favor donors on the protein side with implications for predicting and designing ligand complexes. |
Q91056148 | Protein-small molecule docking with receptor flexibility in iMOLSDOCK |
Q30349715 | ProteinShop: a tool for interactive protein manipulation and steering. |
Q57829621 | Protein–ligand pose and affinity prediction: Lessons from D3R Grand Challenge 3 |
Q39108153 | Proteochemometric model for predicting the inhibition of penicillin-binding proteins |
Q30400560 | Proteus: a random forest classifier to predict disorder-to-order transitioning binding regions in intrinsically disordered proteins |
Q46628587 | Protonation-induced stereoisomerism in nicotine: conformational studies using classical (AMBER) and ab initio (Car-Parrinello) molecular dynamics |
Q74006409 | Pseudoreceptor model for ryanodine derivatives at calcium release channels |
Q28292791 | Public access to X-ray diffraction data |
Q36718321 | Pushing the boundaries of 3D-QSAR. |
Q42281612 | Pyridones as NNRTIs against HIV-1 mutants: 3D-QSAR and protein informatics |
Q52033849 | Q-fit: a probabilistic method for docking molecular fragments by sampling low energy conformational space. |
Q54683502 | QM/MM based 3D QSAR models for potent B-Raf inhibitors. |
Q30392776 | QMOD: physically meaningful QSAR |
Q30358007 | QSAR analyses on avian influenza virus neuraminidase inhibitors using CoMFA, CoMSIA, and HQSAR. |
Q40468021 | QSAR and classification models of a novel series of COX-2 selective inhibitors: 1,5-diarylimidazoles based on support vector machines. |
Q72803831 | QSAR and conformational analysis of the antiinflammatory agent amfenac and analogues |
Q104112873 | QSAR and molecular docking for the search of AOX inhibitors: a rational drug discovery approach |
Q33412179 | QSAR application for the prediction of compound permeability with in silico descriptors in practical use. |
Q30587124 | QSAR model based on weighted MCS trees approach for the representation of molecule data sets |
Q38857036 | QSAR modeling and chemical space analysis of antimalarial compounds |
Q81437670 | QSAR modeling based on the bias/variance compromise: a harmonious and parsimonious approach |
Q44587142 | QSAR modeling of beta-lactam binding to human serum proteins |
Q77763150 | QSAR modeling with the electrotopological state indices: corticosteroids |
Q28211747 | QSAR of benzene derivatives: comparison of classical descriptors, quantum theoretic parameters and flip regression, exemplified by phenylalkylamine hallucinogens |
Q67976701 | QSAR of conformationally flexible molecules: comparative molecular field analysis of protein-tyrosine kinase inhibitors |
Q44420537 | QSAR of heterocyclic antifungal agents by flip regression |
Q30985338 | QSAR study and VolSurf characterization of anti-HIV quinolone library. |
Q78249924 | QSAR using 2D descriptors and TRIPOS' SIMCA |
Q40218957 | QSAR with experimental and predictive distributions: an information theoretic approach for assessing model quality |
Q39835112 | QSAR without arbitrary descriptors: the electron-conformational method |
Q40800449 | QSAR workbench: automating QSAR modeling to drive compound design |
Q80480221 | QSAR: dead or alive? |
Q53539064 | QSID Tool: a new three-dimensional QSAR environmental tool. |
Q51093734 | QSPR ensemble modelling of the 1:1 and 1:2 complexation of Co²⁺, Ni²⁺, and Cu²⁺ with organic ligands: relationships between stability constants. |
Q51912723 | QSPR modeling of UV absorption intensities. |
Q52260139 | QXP: powerful, rapid computer algorithms for structure-based drug design. |
Q39896264 | Qualitative prediction of blood-brain barrier permeability on a large and refined dataset |
Q51892184 | Quantitative Series Enrichment Analysis (QSEA): a novel procedure for 3D-QSAR analysis. |
Q53551924 | Quantitative measurement of protease ligand conformation. |
Q51961345 | Quantitative prediction of imprinting factor of molecularly imprinted polymers by artificial neural network. |
Q46793452 | Quantitative structure-activity relationship analysis of canonical inhibitors of serine proteases |
Q46703800 | Quantitative structure-activity relationship analysis of pyridinone HIV-1 reverse transcriptase inhibitors using the k nearest neighbor method and QSAR-based database mining |
Q33774384 | Quantitative structure-activity relationship analysis of β-amyloid aggregation inhibitors |
Q46767212 | Quantitative structure-activity relationship studies of mushroom tyrosinase inhibitors |
Q73233699 | Quantitative structure-activity relationships and comparative molecular field analysis of TIBO derivatised HIV-1 reverse transcriptase inhibitors |
Q52373584 | Quantitative structure-activity relationships by neural networks and inductive logic programming. I. The inhibition of dihydrofolate reductase by pyrimidines. |
Q52373580 | Quantitative structure-activity relationships by neural networks and inductive logic programming. II. The inhibition of dihydrofolate reductase by triazines. |
Q51992732 | Quantitative structure-activity relationships from optimised ab initio bond lengths: steroid binding affinity and antibacterial activity of nitrofuran derivatives. |
Q50091251 | Quantitative structure-activity relationships of mutagenic activity from quantum topological descriptors: triazenes and halogenated hydroxyfuranones (mutagen-X) derivatives. |
Q71749035 | Quantitative structure-agonist activity relationship of capsaicin analogues |
Q89208049 | Quantitative surface field analysis: learning causal models to predict ligand binding affinity and pose |
Q58108987 | Quantum chemical and molecular mechanics studies on the assessment of interactions between resveratrol and mutant SOD1 (G93A) protein |
Q89460086 | Quantum chemical predictions of water-octanol partition coefficients applied to the SAMPL6 logP blind challenge |
Q91291272 | Quantum chemical studies on anion specificity of CαNN motif in functional proteins |
Q44194554 | Quantum chemical studies on tautomerism of barbituric acid in gas phase and in solution |
Q67558776 | Quantum chemical study on the interaction of some bisphosphonates and Ca2+: the role of molecular electrostatic potentials in the prediction of binding geometry |
Q41931981 | Quantum mechanical polar surface area |
Q46445371 | Quantum mechanics study of the hydroxyethylamines-BACE-1 active site interaction energies |
Q38950911 | Quantum probability ranking principle for ligand-based virtual screening |
Q107739603 | Quantum simulations of SARS-CoV-2 main protease M enable high-quality scoring of diverse ligands |
Q100739180 | Quantum-mechanical property prediction of solvated drug molecules: what have we learned from a decade of SAMPL blind prediction challenges? |
Q51359512 | R-group template CoMFA combines benefits of "ad hoc" and topomer alignments using 3D-QSAR for lead optimization. |
Q80651562 | RIP MDL information systems. Is this really the beginning of a new era? |
Q31062836 | RNA unrestrained molecular dynamics ensemble improves agreement with experimental NMR data compared to single static structure: a test case |
Q48335722 | RNAHelix: computational modeling of nucleic acid structures with Watson-Crick and non-canonical base pairs. |
Q45950111 | ROCS-derived features for virtual screening. |
Q38647554 | Ranking docking poses by graph matching of protein-ligand interactions: lessons learned from the D3R Grand Challenge 2. |
Q57245415 | Rapamycin: Biological and therapeutic effects, binding by immunophilins and molecular targets of action |
Q39675574 | Rapid activity prediction of HIV-1 integrase inhibitors: harnessing docking energetic components for empirical scoring by chemometric and artificial neural network approaches |
Q33832248 | Rapid discovery of inhibitors of Toxoplasma gondii using hybrid structure-based computational approach |
Q44262192 | Rapid prediction of solvation free energy. 3. Application to the SAMPL2 challenge |
Q91945283 | Rational Design, synthesis and biological evaluation of novel triazole derivatives as potent and selective PRMT5 inhibitors with antitumor activity |
Q92776270 | Rational creation and systematic analysis of cervical cancer kinase-inhibitor binding profile |
Q33873862 | Rational design of an enzyme mutant for anti-cocaine therapeutics |
Q38931722 | Rational design of biaryl pharmacophore inserted noscapine derivatives as potent tubulin binding anticancer agents |
Q72593889 | Rational design of hirulog-type inhibitors of thrombin |
Q72393577 | Rational design of novel neurotensin mimetics: discovery of a pharmacologically unprecedented agent exhibiting concentration-dependent dual effects as antagonist and full agonist |
Q84040958 | Rational design, synthesis and biological evaluations of amino-noscapine: a high affinity tubulin-binding noscapinoid |
Q31165909 | Rational selection of training and test sets for the development of validated QSAR models |
Q34133282 | Rationalizing fragment based drug discovery for BACE1: insights from FB-QSAR, FB-QSSR, multi objective (MO-QSPR) and MIF studies. |
Q98505048 | ReSCoSS: a flexible quantum chemistry workflow identifying relevant solution conformers of drug-like molecules |
Q30875868 | Reactant- and product-based approaches to the design of combinatorial libraries |
Q67891433 | Reaction mechanisms in peptide synthesis. Part 1. Semiquantitative characteristics of the reactivity of 2-methyl-5(4H)-oxazolone with water and ammonia in the gas phase and weakly polar media |
Q54071826 | Reaction mechanisms in peptide synthesis. Part 2. Tautomerism of the peptide bond. |
Q51400164 | Real value prediction of protein folding rate change upon point mutation. |
Q78683425 | Recent advances in molecular diversity |
Q107113685 | Recent insights into cysteine protease specificity: Lessons for drug design |
Q68494321 | Receptor model for the molecular basis of tissue selectivity of 1, 4-dihydropyridine calcium channel drugs |
Q58860167 | Receptor-based 3D QSAR analysis of estrogen receptor ligands--merging the accuracy of receptor-based alignments with the computational efficiency of ligand-based methods |
Q28755020 | Recommendations for evaluation of computational methods |
Q73010965 | Reconstruction of the 3D coordinates of alpha-carbon atoms of proteins from a pair of stereographic figures |
Q78429536 | Recovery of known T-cell epitopes by computational scanning of a viral genome |
Q35841379 | Refined homology model of monoacylglycerol lipase: toward a selective inhibitor |
Q59188927 | Refinement of Catalyst hypotheses using simplex optimisation |
Q52081432 | Refinement of modelled structures by knowledge-based energy profiles and secondary structure prediction: application to the human procarboxypeptidase A2. |
Q48514606 | Reflections on the past 25 years. |
Q60194881 | Reinforcing the membrane-mediated mechanism of action of the anti-tuberculosis candidate drug thioridazine with molecular simulations |
Q47952018 | Relative binding affinity prediction of farnesoid X receptor in the D3R Grand Challenge 2 using FEP. |
Q63916807 | Relative binding orientations of adenosine A1 receptor ligands — A test case for Distributed Multipole Analysis in medicinal chemistry |
Q44833190 | Relative free energies of binding to thymidylate synthase of 2- and/or 4-thio and/or 5-fluoro analogues of dUMP. |
Q43275587 | Relative solvation free energies calculated using an ab initio QM/MM-based free energy perturbation method: dependence of results on simulation length |
Q48439266 | Remembrances of Corwin Hansch. |
Q71749022 | Replacement of steric 6-12 potential-derived interaction energies by atom-based indicator variables in CoMFA leads to models of higher consistency |
Q51390000 | Replica exchange Monte-Carlo simulations of helix bundle membrane proteins: rotational parameters of helices. |
Q57460082 | Representation of molecular structure using quantum topology with inductive logic programming in structure–activity relationships |
Q44711419 | Representation, searching and discovery of patterns of bases in complex RNA structures |
Q74568406 | Reproducing the conformations of protein-bound ligands: a critical evaluation of several popular conformational searching tools |
Q90707908 | Repurposing of known drugs for leishmaniasis treatment using bioinformatic predictions, in vitro validations and pharmacokinetic simulations |
Q61999145 | Rescoring of docking poses under Occam’s Razor: are there simpler solutions? |
Q73803116 | Research on anti-HIV-1 agents. Investigation on the CD4-Suradista binding mode through docking experiments |
Q37588671 | Resolving the problem of trapped water in binding cavities: prediction of host-guest binding free energies in the SAMPL5 challenge by funnel metadynamics. |
Q112283807 | RestraintMaker: a graph-based approach to select distance restraints in free-energy calculations with dual topology |
Q91748155 | Resveratrol as a nontoxic excipient stabilizes insulin in a bioactive hexameric form |
Q42661891 | Rethinking 3D-QSAR. |
Q91978101 | Revealing cytotoxic substructures in molecules using deep learning |
Q48059059 | Revealing the importance of linkers in K-series oxime reactivators for tabun-inhibited AChE using quantum chemical, docking and SMD studies. |
Q48114689 | Reverse engineering chemical structures from molecular descriptors: how many solutions? |
Q81131521 | Reverse-docking as a computational tool for the study of asymmetric organocatalysis |
Q95276292 | Revisiting allostery in CREB-binding protein (CBP) using residue-based interaction energy |
Q52230459 | RigFit: a new approach to superimposing ligand molecules. |
Q50627884 | Ring system-based chemical graph generation for de novo molecular design. |
Q45963765 | Robust optimization of scoring functions for a target class. |
Q40513178 | Role of R292K mutation in influenza H7N9 neuraminidase toward oseltamivir susceptibility: MD and MM/PB(GB)SA study |
Q86504064 | Role of indirect readout mechanism in TATA box binding protein-DNA interaction |
Q81944524 | Role of protein flexibility in the design of Bcl-X(L) targeting agents: insight from molecular dynamics |
Q88564664 | Role of protein structure and the role of individual fingers in zinc finger protein-DNA recognition: a molecular dynamics simulation study and free energy calculations |
Q73194561 | Role of tautomerism of 2-azaadenine and 2-azahypoxanthine in substrate recognition by xanthine oxidase |
Q43107625 | SAMPL2 and continuum modeling |
Q84121860 | SAMPL2 challenge: prediction of solvation energies and tautomer ratios |
Q59795479 | SAMPL3: blinded prediction of host–guest binding affinities, hydration free energies, and trypsin inhibitors |
Q37735497 | SAMPL4 & DOCK3.7: lessons for automated docking procedures |
Q45204541 | SAMPL4, a blind challenge for computational solvation free energies: the compounds considered |
Q45975662 | SAMPL5: 3D-RISM partition coefficient calculations with partial molar volume corrections and solute conformational sampling. |
Q92787006 | SAMPL6 Octanol-water partition coefficients from alchemical free energy calculations with MBIS atomic charges |
Q90785851 | SAMPL6 blind predictions of water-octanol partition coefficients using nonequilibrium alchemical approaches |
Q57463683 | SAMPL6 challenge results from [Formula: see text] predictions based on a general Gaussian process model |
Q92892921 | SAMPL6 host-guest binding affinities and binding poses from spherical-coordinates-biased simulations |
Q56342046 | SAMPL6 host-guest blind predictions using a non equilibrium alchemical approach |
Q91500741 | SAMPL6 host-guest challenge: binding free energies via a multistep approach |
Q89460093 | SAMPL6 logP challenge: machine learning and quantum mechanical approaches |
Q58048679 | SAMPL6: calculation of macroscopic pKa values from ab initio quantum mechanical free energies |
Q100512762 | SAMPL7 TrimerTrip host-guest binding affinities from extensive alchemical and end-point free energy calculations |
Q98293823 | SAMPL7 TrimerTrip host-guest binding poses and binding affinities from spherical-coordinates-biased simulations |
Q101325799 | SAMPL7: Host-guest binding prediction by molecular dynamics and quantum mechanics |
Q58225487 | SCF-MO study of the polyglycine II structure |
Q32058654 | SLATE: a method for the superposition of flexible ligands. |
Q51650890 | SMART: a solvent-accessible triangulated surface generator for molecular graphics and boundary element applications. |
Q61960988 | SPROUT, HIPPO and CAESA: Tools for de novo structure generation and estimation of synthetic accessibility |
Q52398734 | SPROUT: a program for structure generation. |
Q72741870 | Sample-distance partial least squares: PLS optimized for many variables, with application to CoMFA |
Q44833188 | Sampling and convergence in free energy calculations of protein-ligand interactions: the binding of triphenoxypyridine derivatives to factor Xa and trypsin |
Q92269008 | Sampling and refinement protocols for template-based macrocycle docking: 2018 D3R Grand Challenge 4 |
Q52321857 | Sampling conformational hyperspace: techniques for improving completeness. |
Q45722871 | Scaffold mining of kinase hinge binders in crystal structure database |
Q28654727 | Scientific and technical data sharing: a trading perspective |
Q24621331 | Scientific workflow systems: Pipeline Pilot and KNIME |
Q37288619 | Scoring confidence index: statistical evaluation of ligand binding mode predictions |
Q36289042 | Scoring functions--the first 100 years. |
Q74633107 | Scoring functions: a view from the bench |
Q71851460 | Scoring noncovalent protein-ligand interactions: a continuous differentiable function tuned to compute binding affinities |
Q81055524 | Scoring protein-protein docked structures based on the balance and tightness of binding |
Q33530648 | Screening of benzamidine-based thrombin inhibitors via a linear interaction energy in continuum electrostatics model |
Q32060283 | Screening the molecular surface of human anticoagulant protein C: a search for interaction sites |
Q33475687 | Second-generation de novo design: a view from a medicinal chemist perspective |
Q31015468 | Secure analysis of distributed chemical databases without data integration |
Q57976083 | Seeing our way to drug design |
Q85723134 | Seeking potential anticonvulsant agents that target GABAA receptors using experimental and theoretical procedures |
Q78057587 | Selective assembly of cyclodextrins on poly(ethylene oxide)-poly(propylene oxide) block copolymers |
Q43631520 | Selective inhibition of 6-phosphogluconate dehydrogenase from Trypanosoma brucei. |
Q74006420 | Selectivity analysis of 5-(arylthio)-2,4-diaminoquinazolines as inhibitors of Candida albicans dihydrofolate reductase by molecular dynamics simulations |
Q82059180 | Selenoglycosides in silico: ab initio-derived reparameterization of MM4, conformational analysis using histo-blood group ABH antigens and lectin docking as indication for potential of bioactivity |
Q46558730 | Semi-rigid analogues of the calcium antagonist verapamil: a molecular modelling study |
Q30333072 | Sensitivity of molecular docking to induced fit effects in influenza virus neuraminidase. |
Q91834657 | Sequence specificity in DNA-drug intercalation: MD simulation and density functional theory approaches |
Q48082192 | Shape information from a critical point analysis of calculated electron density maps: application to DNA-drug systems |
Q90797777 | Shape similarity guided pose prediction: lessons from D3R Grand Challenge 3 |
Q41961153 | Shaping suvorexant: application of experimental and theoretical methods for driving synthetic designs |
Q68049862 | Shell Conference on Computer-Aided Molecular Modelling. October 4-6, 1987, Hoenderloo, The Netherlands |
Q83841243 | Sialyldisaccharide conformations: a molecular dynamics perspective |
Q48055229 | Side chain flexibility and the pore dimensions in the GABAA receptor. |
Q96349420 | Side chain virtual screening of matched molecular pairs: a PDB-wide and ChEMBL-wide analysis |
Q33374550 | Side-chain conformational space analysis (SCSA): a multi conformation-based QSAR approach for modeling and prediction of protein-peptide binding affinities |
Q92164230 | Significantly different effects of tetrahydroberberrubine enantiomers on dopamine D1/D2 receptors revealed by experimental study and integrated in silico simulation |
Q82908722 | Silver threads |
Q56835065 | Similarity and Dissimilarity: A Medicinal Chemist's View |
Q30424998 | Similarity and complementarity of molecular shapes: applicability of a topological analysis approach |
Q44490734 | Similarity based SAR (SIBAR) as tool for early ADME profiling |
Q44684389 | Similarity of molecular shape |
Q30890613 | Similarity screening of molecular data sets |
Q52273177 | Similarity searching in files of three-dimensional chemical structures: representation and searching of molecular electrostatic potentials using field-graphs. |
Q43701172 | Similarity searching in large combinatorial chemistry spaces |
Q57012717 | Similarity versus docking in 3D virtual screening |
Q56917067 | Similarity-based descriptors (SIBAR) – A tool for safe exchange of chemical information? |
Q73331725 | Simple knowledge-based descriptors to predict protein-ligand interactions. methodology and validation |
Q96158677 | Simplified activity cliff network representations with high interpretability and immediate access to SAR information |
Q71749025 | Simulation analysis of formycin 5'-monophosphate analog substrates in the ricin A-chain active site |
Q91538138 | Simulation of MDM2 N-terminal domain conformational lability in the presence of imidazoline based inhibitors of MDM2-p53 protein-protein interaction |
Q38302869 | Simulation of carbohydrate-protein interactions: computer-aided design of a second generation GM1 mimic. |
Q33323615 | Simulation-based cheminformatic analysis of organelle-targeted molecules: lysosomotropic monobasic amines |
Q43805832 | Simultaneous prediction of aqueous solubility and octanol/water partition coefficient based on descriptors derived from molecular structure |
Q41905100 | Simultaneous prediction of binding free energy and specificity for PDZ domain-peptide interactions |
Q43111257 | Site of metabolism prediction on cytochrome P450 2C9: a knowledge-based docking approach. |
Q40412571 | Site-Identification by Ligand Competitive Saturation (SILCS) assisted pharmacophore modeling |
Q47240999 | Size-intensive descriptors |
Q30577535 | Small molecule correctors of F508del-CFTR discovered by structure-based virtual screening |
Q43000482 | So you think you understand tautomerism? |
Q92389169 | Software to obtain spatially localized functions from different radial functions |
Q71483796 | Solution conformation by NMR and molecular modeling of three sulfide-free somatostatin octapeptide analogs compared to angiopeptin |
Q43730054 | Solvation free energies and partition coefficients with the coarse-grained and hybrid all-atom/coarse-grained MARTINI models. |
Q57975330 | Solvation of the active site of cytochrome P450-cam |
Q45002483 | Solvent effect on the synthesis of clarithromycin: a molecular dynamics study |
Q42649305 | Solvent effects on dimeric self-association of 2-pyrrolidinone: an ab initio study |
Q57829045 | Some conclusions regarding the predictions of tautomeric equilibria in solution based on the SAMPL2 challenge |
Q51482694 | Some findings relevant to the mechanistic interpretation in the case of predictive models for carcinogenicity based on the counter propagation artificial neural network. |
Q57009135 | Some thoughts on the “A” in computer-aided molecular design |
Q91480966 | Source of oseltamivir resistance due to single E119D and double E119D/H274Y mutations in pdm09H1N1 influenza neuraminidase |
Q49993604 | Sparse QSAR modelling methods for therapeutic and regenerative medicine. |
Q40145049 | Spatial chemical distance based on atomic property fields |
Q83762002 | Stability and free energy calculation of LNA modified quadruplex: a molecular dynamics study |
Q89690113 | Standard state free energies, not pKas, are ideal for describing small molecule protonation and tautomeric states |
Q46902419 | Statistical analyses and computational prediction of helical kinks in membrane proteins |
Q36568029 | Statistical analysis of EGFR structures' performance in virtual screening |
Q41432276 | Statistical dictionaries for hypothetical in silico model of the early-stage intermediate in protein folding. |
Q30843844 | Statistical relationships among docking scores for different protein binding sites |
Q57907612 | Statistical variation in progressive scrambling |
Q89032540 | Statistics in molecular modeling: a summary |
Q72803827 | Stereochemistry of charged nitrogen-aromatic interactions and its involvement in ligand-receptor binding |
Q36761310 | Stereochemistry of ulapualides, a new family of tris-oxazole-containing macrolide ionophores from marine nudibranchs. A molecular mechanics study |
Q73013874 | Steroid binding by antibodies and artificial receptors: exploration of theoretical methods to determine the origins of binding affinities and specificities |
Q50149089 | Strategic approaches to drug design. I. An integrated software framework for molecular modelling. |
Q69843559 | Strategic approaches to drug design. II. Modelling studies on phosphodiesterase substrates and inhibitors |
Q56040349 | Strategies I |
Q68844987 | Strategies II |
Q68049867 | Strategies for modelling of catalysts |
Q38558154 | Strategies for the determination of pharmacophoric 3D database queries |
Q79489038 | Strategies to design pyrazolyl urea derivatives for p38 kinase inhibition: a molecular modeling study |
Q91777930 | Structural analysis of the Aβ(11-42) amyloid fibril based on hydrophobicity distribution |
Q73803111 | Structural analysis of the KGD sequence loop of barbourin, an alphaIIbbeta3-specific disintegrin |
Q43021660 | Structural and functional analysis of a novel psychrophilic β-mannanase from Glaciozyma antarctica PI12. |
Q67520713 | Structural changes by sulfoxidation of phenothiazine drugs |
Q90445530 | Structural characterization and molecular dynamics simulations of the caprine and bovine solute carrier family 11 A1 (SLC11A1) |
Q71657322 | Structural comparison of NK2 receptor agonists and antagonists |
Q30009248 | Structural dynamics of native and V260E mutant C-terminal domain of HIV-1 integrase |
Q60470924 | Structural evaluation of an alternative Protein A biomimetic ligand for antibody purification |
Q93383637 | Structural explanation for the tunable substrate specificity of an E. coli nucleoside hydrolase: insights from molecular dynamics simulations |
Q46647594 | Structural functionality, catalytic mechanism modeling and molecular allergenicity of phenylcoumaran benzylic ether reductase, an olive pollen (Ole e 12) allergen |
Q34068107 | Structural insight into exosite binding and discovery of novel exosite inhibitors of botulinum neurotoxin serotype A through in silico screening |
Q38673001 | Structural insight into the role of Gln293Met mutation on the Peloruside A/Laulimalide association with αβ-tubulin from molecular dynamics simulations, binding free energy calculations and weak interactions analysis |
Q61697352 | Structural insights for the design of new PPARgamma partial agonists with high binding affinity and low transactivation activity |
Q35228394 | Structural insights into binding of small molecule inhibitors to Enhancer of Zeste Homolog 2. |
Q39469790 | Structural insights into the mechanism of translational inhibition by the fungicide sordarin |
Q36168250 | Structural insights into transient receptor potential vanilloid type 1 (TRPV1) from homology modeling, flexible docking, and mutational studies |
Q35950237 | Structural insights of a PI3K/mTOR dual inhibitor with the morpholino-triazine scaffold |
Q52445252 | Structural investigations and modeling of cavities in clathrates |
Q46457886 | Structural modeling of glucanase-substrate complexes suggests a conserved tyrosine is involved in carbohydrate recognition in plant 1,3-1,4-beta-D-glucanases |
Q33455932 | Structural models in the assessment of protein druggability based on HTS data |
Q38550766 | Structural models of antibody variable fragments: a method for investigating binding mechanisms |
Q33698990 | Structural organization of G-protein-coupled receptors |
Q43600959 | Structural pairwise comparisons of HLM stability of phenyl derivatives: Introduction of the Pfizer metabolism index (PMI) and metabolism-lipophilicity efficiency (MLE). |
Q43015827 | Structural prediction of a novel chitinase from the psychrophilic Glaciozyma antarctica PI12 and an analysis of its structural properties and function |
Q47813312 | Structural rationale for the cross-resistance of tumor cells bearing the A399V variant of elongation factor eEF1A1 to the structurally unrelated didemnin B, ternatin, nannocystin A and ansatrienin B. |
Q34525694 | Structural requirements of Na+-dependent antidopaminergic agents: Tropapride, Piquindone, Zetidoline, and Metoclopramide. Comparison with Na+-independent ligands |
Q50044099 | Structural-dynamical investigation of the ZnuA histidine-rich loop: involvement in zinc management and transport. |
Q47361820 | Structure and dynamics of mesophilic variants from the homing endonuclease I-DmoI. |
Q79759895 | Structure and reaction based evaluation of synthetic accessibility |
Q41022676 | Structure based classification for bile salt export pump (BSEP) inhibitors using comparative structural modeling of human BSEP. |
Q91843408 | Structure based design of selective SHP2 inhibitors by De novo design, synthesis and biological evaluation |
Q71870821 | Structure determination of a tetradecapeptide mimicking the RXVRG consensus sequence recognized by a Xenopus laevis skin endoprotease: an approach based on simulated annealing and 1H NMR |
Q71483765 | Structure of a cyclic peptide with a catalytic triad, determined by computer simulation and NMR spectroscopy |
Q71347767 | Structure-activity analysis of fluorinated 1-N-arylamino-1-arylmethanephosphonic acid esters as inhibitors of the NADH:ubiquinone oxidoreductase (complex I) |
Q71347776 | Structure-activity correlation study of HIV-1 inhibitors: electronic and molecular parameters |
Q67509932 | Structure-activity relationship between the 3D distribution of the electrophilicity of sugar derivatives and their cytotoxic and antiviral properties |
Q60546558 | Structure-activity relationship of Ca2+ channel blockers: A study using conformational analysis and chemometric methods |
Q33230213 | Structure-activity relationships for a new family of sulfonylurea herbicides |
Q68843235 | Structure-activity relationships for apomorphine congeners. Conformational energies vs. biological activities |
Q73604203 | Structure-activity relationships of cannabinoids: a joint CoMFA and pseudoreceptor modelling study |
Q39790677 | Structure-activity relationships of diphenyl-ether as protoporphyrinogen oxidase inhibitors: insights from computational simulations |
Q52444142 | Structure-activity relationships of pyrethroid insecticides. Part 2. The use of molecular dynamics for conformation searching and average parameter calculation. |
Q51029309 | Structure-activity relationships of thiostrepton derivatives: implications for rational drug design. |
Q38348110 | Structure-affinity relationships for the binding of actinomycin D to DNA. |
Q43631515 | Structure-based 3D QSAR and design of novel acetylcholinesterase inhibitors |
Q46380009 | Structure-based CoMFA and CoMSIA study of indolinone inhibitors of PDK1. |
Q44371167 | Structure-based QSAR study on differential inhibition of human prostaglandin endoperoxide H synthase-2 (COX-2) by nonsteroidal anti-inflammatory drugs. |
Q36134510 | Structure-based approach for identification of novel phenylboronic acids as serine-β-lactamase inhibitors. |
Q31101083 | Structure-based combinatorial library design: discovery of non-peptidic inhibitors of caspases 3 and 8. |
Q46522604 | Structure-based design of Aurora A & B inhibitors. |
Q46732054 | Structure-based design of ligands for protein basic domains: application to the HIV-1 Tat protein |
Q34270442 | Structure-based design of oxygen-linked macrocyclic kinase inhibitors: discovery of SB1518 and SB1578, potent inhibitors of Janus kinase 2 (JAK2) and Fms-like tyrosine kinase-3 (FLT3). |
Q74006396 | Structure-based design of potent CDK1 inhibitors derived from olomoucine |
Q35158312 | Structure-based design, synthesis and biological evaluation of β-glucuronidase inhibitors. |
Q48023914 | Structure-based drug design, synthesis and biological assays of P. falciparum Atg3-Atg8 protein-protein interaction inhibitors. |
Q30420492 | Structure-based identification and clustering of protein families and superfamilies |
Q30330267 | Structure-based ligand design for flexible proteins: application of new F-DycoBlock. |
Q44711412 | Structure-based prediction of free energy changes of binding of PTP1B inhibitors |
Q34380036 | Structure-based virtual screening of small-molecule antagonists of platelet integrin αIIbβ3 that do not prime the receptor to bind ligand |
Q40333119 | Structure-guided fragment-based in silico drug design of dengue protease inhibitors. |
Q35103542 | Structure-guided optimization of small molecule c-Abl activators |
Q48332149 | Structure-reactivity modeling using mixture-based representation of chemical reactions. |
Q53401303 | Structure-toxicity relationships of polycyclic aromatic hydrocarbons using molecular quantum similarity. |
Q43293597 | Studies of chirality effect of 4-(phenylamino)-pyrrolo[2,1-f][1,2,4]triazine on p38alpha by molecular dynamics simulations and free energy calculations |
Q39671594 | Substantial improvements in large-scale redocking and screening using the novel HYDE scoring function |
Q60860104 | Substrate binding to mammalian 15-lipoxygenase |
Q45903781 | Substrate recognition by norovirus polymerase: microsecond molecular dynamics study. |
Q54376746 | Substructural fragments: an universal language to encode reactions, molecular and supramolecular structures |
Q34249453 | Substructure and whole molecule approaches for calculating log P. |
Q34413555 | Subunit rotation models activation of serotonin 5-HT3AB receptors by agonists |
Q51699038 | Successful identification of key chemical structure modifications that lead to improved ADME profiles. |
Q40634123 | Superimposition evaluation of ecdysteroid agonist chemotypes through multidimensional QSAR. |
Q100995310 | Supervised molecular dynamics for exploring the druggability of the SARS-CoV-2 spike protein |
Q51918959 | Support vector inductive logic programming outperforms the naive Bayes classifier and inductive logic programming for the classification of bioactive chemical compounds. |
Q67475420 | Surface comparisons of some odour molecules: Conformational calculations on sandalwood odour V |
Q46358770 | Surflex-Dock 2.1: robust performance from ligand energetic modeling, ring flexibility, and knowledge-based search |
Q36098724 | Surflex-Dock: Docking benchmarks and real-world application |
Q31015460 | Surrogate data--a secure way to share corporate data |
Q33227352 | Surrogate docking: structure-based virtual screening at high throughput speed |
Q67971693 | Symposium overview. Minnesota Conference on Supercomputing in Biology: Proteins, Nucleic Acids, and Water |
Q39567997 | Symposium overview. The Shell Conference on Computer-Aided Molecular Modelling |
Q30425177 | Synthesis and conformational analysis by 1H NMR and restrained molecular dynamics simulations of the cyclic decapeptide [Ser-Tyr-Ser-Met-Glu-His-Phe-Arg-Trp-Gly] |
Q30564569 | Systematic assessment of scaffold distances in ChEMBL: prioritization of compound data sets for scaffold hopping analysis in virtual screening |
Q92642794 | Systematic computational identification of promiscuity cliff pathways formed by inhibitors of the human kinome |
Q87307728 | Systematic mining of analog series with related core structures in multi-target activity space |
Q34130507 | T-Analyst: a program for efficient analysis of protein conformational changes by torsion angles |
Q47703604 | TMDIM: an improved algorithm for the structure prediction of transmembrane domains of bitopic dimers |
Q38450152 | TOPS-MODE versus DRAGON descriptors to predict permeability coefficients through low-density polyethylene |
Q51939563 | TRAJELIX: a computational tool for the geometric characterization of protein helices during molecular dynamics simulations. |
Q30988299 | Tales from the war on error: the art and science of curating QSAR data |
Q112712975 | Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse docking |
Q90374510 | TargetCPP: accurate prediction of cell-penetrating peptides from optimized multi-scale features using gradient boost decision tree |
Q36014246 | TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models |
Q77428763 | Tautomeric equilibria in 8-oxopurines: implications for mutagenicity |
Q39885239 | Tautomerism in chemical information management systems |
Q84274723 | Tautomerism in drug discovery |
Q33918117 | Tautomerism in large databases |
Q73010959 | Tautomerism of xanthine and alloxanthine: a model for substrate recognition by xanthine oxidase |
Q51713084 | Tautomerism, Hammett sigma, and QSAR. |
Q43683239 | Tautomers and reference 3D-structures: the orphans of in silico drug design |
Q83816713 | Tautomers and topomers: challenging the uncertainties of direct physicochemical modeling |
Q44282349 | Techniques for the calculation of three-dimensional structural similarity using inter-atomic distances |
Q87963470 | Temperature effect on poly(dA).poly(dT): molecular dynamics simulation studies of polymeric and oligomeric constructs |
Q51118133 | Testing and validation of the Automated Topology Builder (ATB) version 2.0: prediction of hydration free enthalpies. |
Q87184813 | Testing the semi-explicit assembly model of aqueous solvation in the SAMPL4 challenge |
Q46006136 | Testing the semi-explicit assembly solvation model in the SAMPL3 community blind test. |
Q46720955 | The 3D structure of the binding pocket of the human oxytocin receptor for benzoxazine antagonists, determined by molecular docking, scoring functions and 3D-QSAR methods |
Q27676336 | The DINGO dataset: a comprehensive set of data for the SAMPL challenge |
Q69386533 | The Gold Rush of '89 |
Q30832654 | The IUPAC aqueous and non-aqueous experimental pKa data repositories of organic acids and bases |
Q48545009 | The Journal of Computer-Aided Molecular Design: a bibliometric note. |
Q28654725 | The Protein Data Bank archive as an open data resource |
Q30840331 | The Royal Society of Chemistry and the delivery of chemistry data repositories for the community |
Q51145300 | The SAMPL2 blind prediction challenge: introduction and overview. |
Q83811405 | The SAMPL3 blind prediction challenge: transfer energy overview |
Q33740864 | The SAMPL4 host-guest blind prediction challenge: an overview. |
Q39113611 | The SAMPL4 hydration challenge: evaluation of partial charge sets with explicit-water molecular dynamics simulations |
Q38828454 | The SAMPL5 challenge for embedded-cluster integral equation theory: solvation free energies, aqueous pK a, and cyclohexane-water log D. |
Q39379522 | The SAMPL5 host-guest challenge: computing binding free energies and enthalpies from explicit solvent simulations by the attach-pull-release (APR) method |
Q92956891 | The SAMPL6 SAMPLing challenge: assessing the reliability and efficiency of binding free energy calculations |
Q90729516 | The SAMPL6 challenge on predicting aqueous pKa values from EC-RISM theory |
Q92934486 | The SAMPL6 challenge on predicting octanol-water partition coefficients from EC-RISM theory |
Q69843556 | The active analog approach applied to the pharmacophore identification of benzodiazepine receptor ligands |
Q84373290 | The advent and evolution of QSAR at Pomona College |
Q71851466 | The agonistic binding site at the histamine H2 receptor. I. Theoretical investigations of histamine binding to an oligopeptide mimicking a part of the fifth transmembrane alpha-helix |
Q71851470 | The agonistic binding site at the histamine H2 receptor. II. Theoretical investigations of histamine binding to receptor models of the seven alpha-helical transmembrane domain |
Q53119806 | The analysis of the market success of FDA approvals by probing top 100 bestselling drugs. |
Q46164687 | The application of three approximate free energy calculations methods to structure based ligand design: trypsin and its complex with inhibitors |
Q70790879 | The atom assignment problem in automated de novo drug design. 1. Transferability of molecular fragment properties |
Q52334003 | The atom assignment problem in automated de novo drug design. 2. A method for molecular graph and fragment perception. |
Q52333998 | The atom assignment problem in automated de novo drug design. 3. Algorithms for optimization of fragment placement onto 3D molecular graphs. |
Q52327717 | The atom assignment problem in automated de novo drug design. 4. Tests for site-directed fragment placement based on molecular complementarity. |
Q70984344 | The atom assignment problem in automated de novo drug design. 5. Tests for envelope-directed fragment placement based on molecular similarity |
Q91846661 | The backbone of our chemical computations |
Q42636964 | The big problems don't go away by themselves |
Q33228624 | The centroidal algorithm in molecular similarity and diversity calculations on confidential datasets |
Q30977737 | The challenges of making decisions using uncertain data |
Q39674506 | The character of molecular modeling |
Q30051305 | The chirality problem in P-substituted oligonucleotides |
Q52289439 | The comparison of geometric and electronic properties of molecular surfaces by neural networks: application to the analysis of corticosteroid-binding globulin activity of steroids. |
Q68012970 | The computational design of test compounds with potentially specific biological activity: histamine-H2 agonists derived from 5-HT/H2 antagonists |
Q33214112 | The computer program LUDI: a new method for the de novo design of enzyme inhibitors |
Q46862343 | The concept of template-based de novo design from drug-derived molecular fragments and its application to TAR RNA. |
Q52066527 | The configurational dependence of binding free energies: a Poisson-Boltzmann study of Neuraminidase inhibitors. |
Q68665070 | The conformational preferences of gamma-lactam and its role in constraining peptide structure |
Q48020849 | The consequences of translational and rotational entropy lost by small molecules on binding to proteins |
Q45959177 | The continuous molecular fields approach to building 3D-QSAR models. |
Q71347782 | The coordination of the catalytic zinc in alcohol dehydrogenase studied by combined quantum-chemical and molecular mechanics calculations |
Q101240285 | The critical role of QM/MM X-ray refinement and accurate tautomer/protomer determination in structure-based drug design |
Q46630851 | The de novo design of median molecules within a property range of interest |
Q34326042 | The development of a simple empirical scoring function to estimate the binding constant for a protein-ligand complex of known three-dimensional structure |
Q52247866 | The discovery of indicator variables for QSAR using inductive logic programming. |
Q67865142 | The discovery of novel auxin transport inhibitors by molecular modeling and three-dimensional pattern analysis |
Q69601247 | The educational foundation of Computational Chemistry |
Q83949384 | The effect of CH3, F and NO2 substituents on the individual hydrogen bond energies in the adenine-thymine and guanine-cytosine base pairs |
Q73652657 | The effect of isodensity surface sampling on ESP derived charges and the effect of adding bondcenters on DMA derived charges |
Q48592247 | The effect of numerical error on the reproducibility of molecular geometry optimizations. |
Q45087562 | The effect of physical organic properties on hydrophobic fields |
Q45002480 | The effect of tightly bound water molecules on the structural interpretation of ligand-derived pharmacophore models. |
Q46666631 | The effects of characteristics of substituents on toxicity of the nitroaromatics: HiT QSAR study |
Q43084564 | The effects of tautomerism on the nature of molecules in the solid state |
Q39664353 | The errors of our ways: taking account of error in computer-aided drug design to build confidence intervals for our next 25 years |
Q30395547 | The evolution of drug design at Merck Research Laboratories |
Q34241696 | The future of molecular dynamics simulations in drug discovery |
Q41830975 | The good, the bad and the twisted: a survey of ligand geometry in protein crystal structures. |
Q39671847 | The great descriptor melting pot: mixing descriptors for the common good of QSAR models |
Q67649805 | The histamine H1-receptor antagonist binding site. Part I: Active conformation of cyproheptadine |
Q54964899 | The immunophilins |
Q30997856 | The impact of data integrity on decision making in early lead discovery |
Q52098154 | The implementation of ab initio quantum chemistry calculations on transporters. |
Q35016524 | The importance of molecular complexity in the design of screening libraries. |
Q48055147 | The importance of protonation and tautomerization in relative binding affinity prediction: a comparison of AMBER TI and Schrödinger FEP. |
Q30421420 | The importance of short structural motifs in protein structure analysis |
Q70233002 | The inclusion of electrostatic hydration energies in molecular mechanics calculations |
Q39681298 | The inevitable QSAR renaissance |
Q89448145 | The influence of hydrogen bonding on partition coefficients |
Q72240650 | The matching of electrostatic extrema: a useful method in drug design? A study of phosphodiesterase III inhibitors |
Q31963506 | The measurement of molecular diversity by receptor site interaction simulation |
Q36843694 | The measurement of molecular diversity: a three-dimensional approach |
Q39568009 | The modelling of nucleophilic and electrophilic additions to organometallic complexes using molecular graphics techniques |
Q39794961 | The molecular mechanism studies of chirality effect of PHA-739358 on Aurora kinase A by molecular dynamics simulation and free energy calculations |
Q44342941 | The mu- and delta-opioid pharmacophore conformations of cyclic beta-casomorphin analogues indicate docking of the Phe3 residue to different domains of the opioid receptors |
Q33464348 | The multi-copy simultaneous search methodology: a fundamental tool for structure-based drug design |
Q33469695 | The multiple roles of computational chemistry in fragment-based drug design |
Q44587151 | The nature of topological parameters. I. Are topological parameters 'fundamental properties'? |
Q47622456 | The nature of topological parameters. II. The composition of topological parameters |
Q39084836 | The need for scientific software engineering in the pharmaceutical industry |
Q73913489 | The orientation of N-H...O=C and N-H...N hydrogen bonds in biological systems: how good is a point charge as a model for a hydrogen bonding atom? |
Q39676663 | The perspectives of computational chemistry modeling |
Q45966344 | The prediction of human oral absorption for diffusion rate-limited drugs based on heuristic method and support vector machine. |
Q34648848 | The probable conformation of substrates recognized by dipeptidyl-peptidase IV and some aspects of the catalytic mechanism derived from theoretical investigations |
Q84966543 | The receptor-dependent LQTA-QSAR: application to a set of trypanothione reductase inhibitors |
Q77763162 | The reconstruction of atomic co-ordinates from a protein stereo ribbon diagram when additional information for sufficient sidechain positions is available |
Q51555075 | The reductionist paradox: are the laws of chemistry and physics sufficient for the discovery of new drugs? |
Q92829701 | The role of human in the loop: lessons from D3R challenge 4 |
Q91108678 | The role of hydration effects in 5-fluorouridine binding to SOD1: insight from a new 3D-RISM-KH based protocol for including structural water in docking simulations |
Q90203330 | The role of water and protein flexibility in the structure-based virtual screening of allosteric GPCR modulators: an mGlu5 receptor case study |
Q57235382 | The search for a new model structure of beta-factor XIIa |
Q73233694 | The sensitivity of the results of molecular docking to induced fit effects: application to thrombin, thermolysin and neuraminidase |
Q56904259 | The sequence homologies of cytochromes P-450 and active-site geometries |
Q83972920 | The state of the guanosine nucleotide allosterically affects the interfaces of tubulin in protofilament |
Q40415316 | The statistics of virtual screening and lead optimization |
Q77365350 | The structural and electronical factors that contribute affinity for the time-dependent inhibition of PGHS-1 by indomethacin, diclofenac and fenamates |
Q67822565 | The structure-activity relationship of inhibitors of serotonin uptake and receptor binding |
Q52395210 | The use of an algorithmic method for small molecule superimpositions in the design of antiviral agents. |
Q51103643 | The use of docking-based comparative intermolecular contacts analysis to identify optimal docking conditions within glucokinase and to discover of new GK activators. |
Q43993646 | The veil of commercialism |
Q58005877 | The voltage-gated potassium channel: Sequence analysis and molecular modelling of the pore domain |
Q59614151 | Theoretical descriptors for the quantitative rationalisation of plastocyanin mutant functional propertiess |
Q59614218 | Theoretical investigation of substrate specificity for cytochromes P450 IA2, P450 IID6 and P450 IIIA4 |
Q68079169 | Theoretical models for the conformations and the protonation of triacetonamine |
Q89414557 | Theoretical models to predict the inhibitory effect of ligands of sphingosine kinase 1 using QTAIM calculations and hydrogen bond dynamic propensity analysis |
Q69386532 | Theoretical studies of the mechanism of the action of the neurohypophyseal hormones. I. Molecular electrostatic potential (MEP) and molecular electrostatic field (MEF) maps of some vasopressin analogues |
Q50473551 | Theoretical studies on effective metal-to-ligand charge transfer characteristics of novel ruthenium dyes for dye sensitized solar cells. |
Q34024760 | Theoretical studies on the interaction of partial agonists with the 5-HT2A receptor |
Q53736952 | Theoretical studies on the reaction of mono- and ditriflate derivatives of 1,4:3,6-dianhydro-D-mannitol with trimethylamine--Can a quaternary ammonium salt be a source of the methyl group? |
Q44896304 | Theoretical study of selective methylation in the synthesis of azithromycin |
Q43605230 | Thermodynamic aspects of hydrophobicity and biological QSAR. |
Q44835970 | Thermodynamic conformational analysis and structural stability of the nicotinic analgesic ABT-594. |
Q68843238 | Thermodynamic cycle integration by computer simulation as a tool for obtaining free energy differences in molecular chemistry |
Q33961846 | Thermodynamic integration to predict host-guest binding affinities |
Q27702163 | Thermodynamics of protein-ligand interactions as a reference for computational analysis: how to assess accuracy, reliability and relevance of experimental data |
Q91624885 | This issue: Drug Design Data Resource Grand Challenge 4, first of two issues |
Q30356850 | Three dimensional model of severe acute respiratory syndrome coronavirus helicase ATPase catalytic domain and molecular design of severe acute respiratory syndrome coronavirus helicase inhibitors. |
Q38559642 | Three-dimensional hydrogen-bond geometry and probability information from a crystal survey |
Q42547091 | Three-dimensional modelling of human cytochrome P450 1A2 and its interaction with caffeine and MeIQ. |
Q45184582 | Three-dimensional quantitative structure-activity and structure-selectivity relationships of dihydrofolate reductase inhibitors. |
Q46865333 | Three-dimensional quantitative structure-activity relationship (3D QSAR) and pharmacophore elucidation of tetrahydropyran derivatives as serotonin and norepinephrine transporter inhibitors. |
Q38562048 | Three-dimensional quantitative structure-activity relationships of steroid aromatase inhibitors |
Q41387262 | Time dependent analysis of assay comparability: a novel approach to understand intra- and inter-site variability over time. |
Q51648149 | Time-efficient flexible superposition of medium-sized molecules. |
Q92164237 | ToGo-WF: prediction of RNA tertiary structures and RNA-RNA/protein interactions using the KNIME workflow |
Q56985255 | Tomocomd-Cardd, a novel approach for computer-aided ? rational? drug design: I. Theoretical and experimental assessment of a promising method for computational screening and in silico design of new anthelmintic compounds |
Q48260317 | Tools, techniques, organisation and culture of the CADD group at Sygnature Discovery |
Q51958833 | Topological side-chain classification of beta-turns: ideal motifs for peptidomimetic development. |
Q89036698 | Touching proteins with virtual bare hands : Visualizing protein-drug complexes and their dynamics in self-made virtual reality using gaming hardware |
Q81305424 | Toward Mycobacterium tuberculosis DXR inhibitor design: homology modeling and molecular dynamics simulations |
Q51637459 | Toward better QSAR/QSPR modeling: simultaneous outlier detection and variable selection using distribution of model features. |
Q39331916 | Toward the discovery of inhibitors of babesipain-1, a Babesia bigemina cysteine protease: in vitro evaluation, homology modeling and molecular docking studies |
Q77428758 | Toward the identification of the cardiac cGMP inhibited-phosphodiesterase catalytic site |
Q35029376 | Towards a new age of virtual ADME/TOX and multidimensional drug discovery |
Q52897990 | Towards a rational spacer design for bivalent inhibition of estrogen receptor. |
Q52462682 | Towards an identification of the pyrethroid pharmacophore. A molecular modelling study of some pyrethroid esters. |
Q71699021 | Towards an understanding of the molecular basis of hydrophobicity |
Q80082282 | Towards discovering dual functional inhibitors against both wild type and K103N mutant HIV-1 reverse transcriptases: molecular docking and QSAR studies on 4,1-benzoxazepinone analogues |
Q36827832 | Towards the automatic design of synthetically accessible protein ligands: peptides, amides and peptidomimetics |
Q51967888 | Towards the chemometric dissection of peptide--HLA-A*0201 binding affinity: comparison of local and global QSAR models. |
Q45940902 | Towards the comprehensive, rapid, and accurate prediction of the favorable tautomeric states of drug-like molecules in aqueous solution. |
Q89724281 | Towards the understanding of the activity of G9a inhibitors: an activity landscape and molecular modeling approach |
Q39841282 | Trainable structure-activity relationship model for virtual screening of CYP3A4 inhibition. |
Q44207658 | Transferable scoring function based on semiempirical quantum mechanical PM6-DH2 method: CDK2 with 15 structurally diverse inhibitors. |
Q52473279 | Triangulation algorithms for the representation of molecular surface properties. |
Q36328661 | Triple hydrogen bonding in a circular arrangement: ab initio, DFT and first-principles MD studies of tris-hydroxyaryl enamines |
Q33273270 | TrixX: structure-based molecule indexing for large-scale virtual screening in sublinear time |
Q45232748 | Tuning of hydrogen bond strength using substituents on phenol and aniline: a possible ligand design strategy |
Q50921495 | Two-track virtual screening approach to identify both competitive and allosteric inhibitors of human small C-terminal domain phosphatase 1. |
Q33271049 | Ultrafast de novo docking combining pharmacophores and combinatorics |
Q30379556 | Ultrafast protein structure-based virtual screening with Panther. |
Q90857877 | Uncovering abnormal changes in logP after fluorination using molecular dynamics simulations |
Q91480971 | Undersampling: case studies of flaviviral inhibitory activities |
Q53663557 | Understanding and modulating cyclin-dependent kinase inhibitor specificity: molecular modeling and biochemical evaluation of pyrazolopyrimidinones as CDK2/cyclin A and CDK4/cyclin D1 inhibitors. |
Q51913215 | Understanding hERG inhibition with QSAR models based on a one-dimensional molecular representation. |
Q51580291 | Understanding molecular structure from molecular mechanics. |
Q46456237 | Understanding the mechanism of cellulose dissolution in 1-butyl-3-methylimidazolium chloride ionic liquid via quantum chemistry calculations and molecular dynamics simulations |
Q84230612 | Understanding the molecular interactions of different radical scavengers with ribonucleotide reductase M2 (hRRM2) domain: opening the gates and gaining access |
Q61644525 | Unraveling the distinctive features of hemorrhagic and non-hemorrhagic snake venom metalloproteinases using molecular simulations |
Q92452767 | Unravelling the covalent binding of zampanolide and taccalonolide AJ to a minimalist representation of a human microtubule |
Q57012683 | Unsupervised guided docking of covalently bound ligands |
Q39784558 | Upperbound procedures for the identification of similar three-dimensional chemical structures |
Q50790893 | Urgency and austerity as drivers of success. |
Q62511444 | Use of electron-electron repulsion energy as a molecular descriptor in QSAR and QSPR studies |
Q91347516 | Use of molecular dynamics fingerprints (MDFPs) in SAMPL6 octanol-water log P blind challenge |
Q30328519 | Use of surface area computations to describe atom-atom interactions. |
Q52885309 | Use of the hydrogen bond potential function in a comparative molecular field analysis (CoMFA) on a set of benzodiazepines. |
Q43892219 | Using a homology model of cytochrome P450 2D6 to predict substrate site of metabolism |
Q79761837 | Using a pharmacophore representation concept to elucidate molecular similarity of dopamine antagonists |
Q46457884 | Using a staged multi-objective optimization approach to find selective pharmacophore models |
Q115732707 | Using diverse potentials and scoring functions for the development of improved machine-learned models for protein–ligand affinity and docking pose prediction |
Q47301557 | Using halogen bonds to address the protein backbone: a systematic evaluation |
Q47622439 | Using particle swarms for the development of QSAR models based on K-nearest neighbor and kernel regression |
Q47614697 | Using physics-based pose predictions and free energy perturbation calculations to predict binding poses and relative binding affinities for FXR ligands in the D3R Grand Challenge 2. |
Q58614302 | Using steered molecular dynamics to study the interaction between ADP and the nucleotide-binding domain of yeast Hsp70 protein Ssa1 |
Q31147061 | Utilizing high throughput screening data for predictive toxicology models: protocols and application to MLSCN assays |
Q27136493 | VEGA – An open platform to develop chemo-bio-informatics applications, using plug-in architecture and script programming |
Q56749500 | VSDMIP 1.5: an automated structure- and ligand-based virtual screening platform with a PyMOL graphical user interface |
Q33378588 | VSDMIP: virtual screening data management on an integrated platform. |
Q46819561 | Validated ligand mapping of ACE active site |
Q92787024 | Validating the validation: reanalyzing a large-scale comparison of deep learning and machine learning models for bioactivity prediction |
Q31112340 | Validation of an empirical RNA-ligand scoring function for fast flexible docking using Ribodock |
Q47863372 | Validation of tautomeric and protomeric binding modes by free energy calculations. A case study for the structure based optimization of D-amino acid oxidase inhibitors |
Q64168637 | Validation tools for variable subset regression |
Q36095634 | Variability in docking success rates due to dataset preparation |
Q45281821 | Variable selection and model validation of 2D and 3D molecular descriptors |
Q30983470 | Variable selection and specification of robust QSAR models from multicollinear data: arylpiperazinyl derivatives with affinity and selectivity for alpha2-adrenoceptors |
Q40715107 | Vascular endothelial growth factor receptor-2 (VEGFR-2) inhibitors: development and validation of predictive 3-D QSAR models through extensive ligand- and structure-based approaches |
Q43605232 | Very empirical treatment of solvation and entropy: a force field derived from log Po/w |
Q56897201 | Viral cysteine proteinases |
Q27136404 | Virtual Computational Chemistry Laboratory – Design and Description |
Q50550611 | Virtual and experimental high-throughput screening (HTS) in search of novel inosine 5'-monophosphate dehydrogenase II (IMPDH II) inhibitors. |
Q30864246 | Virtual fragment screening: an exploration of various docking and scoring protocols for fragments using Glide |
Q34368348 | Virtual fragment screening: exploration of MM-PBSA re-scoring |
Q51900328 | Virtual screening applications: a study of ligand-based methods and different structure representations in four different scenarios. |
Q34065423 | Virtual screening of integrase inhibitors by large scale binding free energy calculations: the SAMPL4 challenge |
Q42241501 | Virtual screening of the SAMPL4 blinded HIV integrase inhibitors dataset. |
Q34243088 | Virtual screening using a conformationally flexible target protein: models for ligand binding to p38α MAPK. |
Q40578605 | Virtual screening with AutoDock Vina and the common pharmacophore engine of a low diversity library of fragments and hits against the three allosteric sites of HIV integrase: participation in the SAMPL4 protein-ligand binding challenge |
Q48886770 | Visual exploration of structure-activity relationship using maximum common framework. |
Q50141323 | Visualisation and integration of G protein-coupled receptor related information help the modelling: description and applications of the Viseur program. |
Q48057902 | Visualisation and subsets of the chemical universe database GDB-13 for virtual screening |
Q33913583 | Visualisation of the chemical space of fragments, lead-like and drug-like molecules in PubChem |
Q53596460 | Visualization of multi-property landscapes for compound selection and optimization. |
Q93119097 | Visualizing protein-ligand binding with chemical energy-wise decomposition (CHEWD): application to ligand binding in the kallikrein-8 S1 Site |
Q43887271 | Visually impaired researchers get their hands on quantum chemistry: application to a computational study on the isomerization of a sterol |
Q33226137 | VolSurf analysis of pharmacokinetic properties for several antifungal sesquiterpene lactones isolated from Greek Centaurea sp. |
Q62495668 | WIZARD: AI in conformational analysis |
Q40521899 | WONKA: objective novel complex analysis for ensembles of protein-ligand structures. |
Q29644511 | Warfarin: history, tautomerism and activity |
Q30642554 | Warmr: a data mining tool for chemical data |
Q68121901 | Watching our numbers double |
Q91524112 | Water molecules in protein-ligand interfaces. Evaluation of software tools and SAR comparison |
Q52300010 | Wavelets and molecular structure. |
Q91459321 | Weak interactions in furan dimers |
Q42059670 | Web application for studying the free energy of binding and protonation states of protein-ligand complexes based on HINT. |
Q45957087 | Weighted voting-based consensus clustering for chemical structure databases. |
Q30481529 | What do we know and when do we know it? |
Q33367595 | What induces pocket openings on protein surface patches involved in protein-protein interactions? |
Q69601231 | What is research? |
Q44857621 | When is an answer the answer? |
Q49722094 | WhichP450: a multi-class categorical model to predict the major metabolising CYP450 isoform for a compound. |
Q56973975 | Why relevant chemical information cannot be exchanged without disclosing structures |
Q83380497 | Why you should read Dr. Cramer's perspective |
Q47684449 | Workflows and performances in the ranking prediction of 2016 D3R Grand Challenge 2: lessons learned from a collaborative effort |
Q48280343 | Yada: a novel tool for molecular docking calculations. |
Q67822571 | Yesterday, today and perhaps tomorrow |
Q45958946 | eFindSite: improved prediction of ligand binding sites in protein models using meta-threading, machine learning and auxiliary ligands. |
Q47291934 | iScreen: world's first cloud-computing web server for virtual screening and de novo drug design based on TCM database@Taiwan |
Q31104033 | kScore: a novel machine learning approach that is not dependent on the data structure of the training set. |
Q39449589 | mRAISE: an alternative algorithmic approach to ligand-based virtual screening |
Q58597404 | pK measurements for the SAMPL6 prediction challenge for a set of kinase inhibitor-like fragments |
Q85113134 | pK(a) based protonation states and microspecies for protein-ligand docking |
Q37386275 | pi-SCF-molecular mechanics PIMM: formulation, parameters, applications |
Q90600677 | www.3d-qsar.com: a web portal that brings 3-D QSAR to all electronic devices-the Py-CoMFA web application as tool to build models from pre-aligned datasets |
Q5205842 | DOCK | described by source | P1343 |
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