| scholarly article | Q13442814 |
| P6179 | Dimensions Publication ID | 1001396921 |
| P356 | DOI | 10.1007/S12272-015-0640-5 |
| P698 | PubMed publication ID | 26208641 |
| P50 | author | Sun Choi | Q47909500 |
| Stephani Joy Y Macalino | Q85648696 | ||
| P2093 | author name string | Sunhye Hong | |
| Vijayakumar Gosu | |||
| P2860 | cites work | Application of a Theory of Enzyme Specificity to Protein Synthesis | Q24620284 |
| Flexible ligand docking to multiple receptor conformations: a practical alternative | Q24650066 | ||
| Exploring the role of receptor flexibility in structure-based drug discovery | Q27001129 | ||
| Structure-based virtual screening for drug discovery: a problem-centric review | Q27022502 | ||
| SMARTCyp: A 2D Method for Prediction of Cytochrome P450-Mediated Drug Metabolism | Q27136650 | ||
| PRO_SELECT: combining structure-based drug design and array-based chemistry for rapid lead discovery. 2. The development of a series of highly potent and selective factor Xa inhibitors | Q27638198 | ||
| Scalable molecular dynamics with NAMD | Q27860718 | ||
| CASTp: computed atlas of surface topography of proteins with structural and topographical mapping of functionally annotated residues | Q27860729 | ||
| Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings | Q27861111 | ||
| The price of innovation: new estimates of drug development costs | Q28212140 | ||
| QSAR modeling: where have you been? Where are you going to? | Q28222668 | ||
| Docking ligands into flexible and solvated macromolecules. 4. Are popular scoring functions accurate for this class of proteins? | Q28245128 | ||
| Target identification in chemical genetics: the (often) missing link | Q28262958 | ||
| istar: a web platform for large-scale protein-ligand docking | Q28306830 | ||
| Predicting protein ligand binding sites by combining evolutionary sequence conservation and 3D structure | Q28472023 | ||
| Molecular modeling studies of the novel inhibitors of DNA methyltransferases SGI-1027 and CBC12: implications for the mechanism of inhibition of DNMTs | Q28487027 | ||
| RosettaBackrub--a web server for flexible backbone protein structure modeling and design | Q28914741 | ||
| AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility | Q29547658 | ||
| New substructure filters for removal of pan assay interference compounds (PAINS) from screening libraries and for their exclusion in bioassays | Q29615588 | ||
| GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit | Q29615867 | ||
| A critical assessment of docking programs and scoring functions | Q29616761 | ||
| PARS: a web server for the prediction of Protein Allosteric and Regulatory Sites. | Q30357768 | ||
| Computational approaches for drug discovery. | Q30366521 | ||
| Ensemble-based virtual screening reveals potential novel antiviral compounds for avian influenza neuraminidase. | Q30370020 | ||
| Potential and Limitations of Ensemble Docking | Q30415116 | ||
| MCPath: Monte Carlo path generation approach to predict likely allosteric pathways and functional residues. | Q30431541 | ||
| Development of a Virtual Screening Method for Identification of “Frequent Hitters” in Compound Libraries | Q30783737 | ||
| LIGSITEcsc: predicting ligand binding sites using the Connolly surface and degree of conservation | Q30826242 | ||
| Docking ligands into flexible and solvated macromolecules. 5. Force-field-based prediction of binding affinities of ligands to proteins | Q30903541 | ||
| Flexibility and binding affinity in protein-ligand, protein-protein and multi-component protein interactions: limitations of current computational approaches. | Q31033753 | ||
| Molecular docking and high-throughput screening for novel inhibitors of protein tyrosine phosphatase-1B. | Q31057078 | ||
| Topomer CoMFA: a design methodology for rapid lead optimization | Q31126609 | ||
| LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters | Q31143138 | ||
| Comparative virtual and experimental high-throughput screening for glycogen synthase kinase-3beta inhibitors | Q33228824 | ||
| Protein protein interaction inhibition (2P2I) combining high throughput and virtual screening: Application to the HIV-1 Nef protein | Q33307477 | ||
| Docking ligands into flexible and solvated macromolecules. 2. Development and application of fitted 1.5 to the virtual screening of potential HCV polymerase inhibitors | Q33323904 | ||
| FAF-Drugs2: free ADME/tox filtering tool to assist drug discovery and chemical biology projects | Q33371792 | ||
| Recent advances in computer-aided drug design | Q33443633 | ||
| Fpocket: an open source platform for ligand pocket detection. | Q33457742 | ||
| Fast and automated functional classification with MED-SuMo: an application on purine-binding proteins. | Q33839028 | ||
| Integrating Structure-Based and Ligand-Based Approaches for Computational Drug Design | Q33893108 | ||
| A critical comparative assessment of predictions of protein-binding sites for biologically relevant organic compounds | Q33897575 | ||
| The design of phenylglycine containing benzamidine carboxamides as potent and selective inhibitors of factor Xa. | Q43552139 | ||
| How far can virtual screening take us in drug discovery? | Q43630348 | ||
| Comparative evaluation of 11 scoring functions for molecular docking | Q44457437 | ||
| Effect of detergent on "promiscuous" inhibitors | Q44523300 | ||
| "Soft docking": matching of molecular surface cubes | Q44675898 | ||
| Preclinical safety evaluation of biotechnology-derived pharmaceuticals | Q44888930 | ||
| Impact of high-throughput screening in biomedical research | Q45352809 | ||
| Identification of cavities on protein surface using multiple computational approaches for drug binding site prediction. | Q45936749 | ||
| eFindSite: Improved prediction of ligand binding sites in protein models using meta-threading, machine learning and auxiliary ligands | Q45958946 | ||
| Sequence-derived three-dimensional pharmacophore models for G-protein-coupled receptors and their application in virtual screening | Q46053003 | ||
| Strategies for generating less toxic P-selectin inhibitors: pharmacophore modeling, virtual screening and counter pharmacophore screening to remove toxic hits | Q46257269 | ||
| 3D-QSAR studies of heterocyclic quinones with inhibitory activity on vascular smooth muscle cell proliferation using pharmacophore-based alignment | Q46310466 | ||
| MetaSite: understanding metabolism in human cytochromes from the perspective of the chemist | Q46775772 | ||
| Comparison of several molecular docking programs: pose prediction and virtual screening accuracy. | Q47708648 | ||
| Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins | Q47746759 | ||
| Docking ligands into flexible and solvated macromolecules. 3. Impact of input ligand conformation, protein flexibility, and water molecules on the accuracy of docking programs | Q47948640 | ||
| Comparative assessment of scoring functions on a diverse test set. | Q48026800 | ||
| Automatic clustering of docking poses in virtual screening process using self-organizing map. | Q48247332 | ||
| Q-SiteFinder: an energy-based method for the prediction of protein-ligand binding sites | Q48498889 | ||
| Classification of current scoring functions | Q50603070 | ||
| Quantitative structure-activity relationship models that stand the test of time | Q50765091 | ||
| A virtual screening approach to finding novel and potent antagonists at the melanin-concentrating hormone 1 receptor | Q50798139 | ||
| Comparing sixteen scoring functions for predicting biological activities of ligands for protein targets | Q50958912 | ||
| Improving the scoring of protein-ligand binding affinity by including the effects of structural water and electronic polarization | Q51013950 | ||
| McQSAR: a multiconformational quantitative structure-activity relationship engine driven by genetic algorithms | Q51314952 | ||
| ChemBioServer: a web-based pipeline for filtering, clustering and visualization of chemical compounds used in drug discovery | Q51325204 | ||
| High-throughput screening and structure-based approaches to hit discovery: is there a clear winner? | Q51344025 | ||
| AcquaAlta: A Directional Approach to the Solvation of Ligand–Protein Complexes | Q51552985 | ||
| Molecular docking with ligand attached water molecules | Q51583403 | ||
| RosettaLigand docking with full ligand and receptor flexibility | Q51861937 | ||
| FLIPDock: docking flexible ligands into flexible receptors | Q51913931 | ||
| Docking ligands into flexible and solvated macromolecules. 1. Development and validation of FITTED 1.0. | Q51922137 | ||
| Fast prediction and visualization of protein binding pockets with PASS. | Q52078631 | ||
| Side-chain flexibility in proteins upon ligand binding | Q52080522 | ||
| DrugScore meets CoMFA: adaptation of fields for molecular comparison (AFMoC) or how to tailor knowledge-based pair-potentials to a particular protein | Q52413367 | ||
| Diverse, high-quality test set for the validation of protein-ligand docking performance | Q55043208 | ||
| The FAF-Drugs2 server: a multistep engine to prepare electronic chemical compound collections | Q33920633 | ||
| A ‘Rule of Three’ for fragment-based lead discovery? | Q33973131 | ||
| Combining 2D and 3D in silico methods for rapid selection of potential PDE5 inhibitors from multimillion compounds' repositories: biological evaluation | Q34030603 | ||
| Molecular properties that influence the oral bioavailability of drug candidates | Q34130727 | ||
| Recognizing pitfalls in virtual screening: a critical review | Q34204731 | ||
| The process of structure-based drug design | Q34266765 | ||
| Strategies for the generation, validation and application of in silico ADMET models in lead generation and optimization. | Q34360291 | ||
| Incorporating backbone flexibility in MedusaDock improves ligand-binding pose prediction in the CSAR2011 docking benchmark | Q34511491 | ||
| The holistic integration of virtual screening in drug discovery | Q34557548 | ||
| PHASE: a new engine for pharmacophore perception, 3D QSAR model development, and 3D database screening: 1. Methodology and preliminary results | Q34584338 | ||
| Target identification and mechanism of action in chemical biology and drug discovery | Q34626974 | ||
| Role of the active-site solvent in the thermodynamics of factor Xa ligand binding | Q34748976 | ||
| Lead discovery using molecular docking | Q34754631 | ||
| Discovery of novel human histamine H4 receptor ligands by large-scale structure-based virtual screening | Q34776186 | ||
| Emerging methods for ensemble-based virtual screening | Q34908421 | ||
| Identifying and characterizing binding sites and assessing druggability | Q34980548 | ||
| Integration of virtual and high-throughput screening | Q34988235 | ||
| Challenges, applications, and recent advances of protein-ligand docking in structure-based drug design. | Q35206344 | ||
| Hierarchical virtual screening approaches in small molecule drug discovery | Q35214824 | ||
| Structure-based virtual screening for drug discovery: principles, applications and recent advances. | Q35282223 | ||
| Docking ligands into flexible and solvated macromolecules. 7. Impact of protein flexibility and water molecules on docking-based virtual screening accuracy | Q35299602 | ||
| Methods for generating and applying pharmacophore models as virtual screening filters and for bioactivity profiling | Q35476224 | ||
| Learning from PAINful lessons | Q35566894 | ||
| Structural insight into tetrameric hTRPV1 from homology modeling, molecular docking, molecular dynamics simulation, virtual screening, and bioassay validations | Q35867767 | ||
| SiteComp: a server for ligand binding site analysis in protein structures | Q35883739 | ||
| APoc: large-scale identification of similar protein pockets | Q36638534 | ||
| Methods for the prediction of protein-ligand binding sites for structure-based drug design and virtual ligand screening | Q36638820 | ||
| An improved relaxed complex scheme for receptor flexibility in computer-aided drug design | Q36838120 | ||
| SPACER: Server for predicting allosteric communication and effects of regulation. | Q36953906 | ||
| Assessment of the blood-brain barrier in CNS drug discovery | Q37576219 | ||
| Structure-based drug design strategies in medicinal chemistry | Q37597256 | ||
| Scoring functions and their evaluation methods for protein-ligand docking: recent advances and future directions. | Q37781709 | ||
| Accounting for Induced-Fit Effects in Docking: What is Possible and What is Not? | Q37799620 | ||
| Structure-based drug design to augment hit discovery | Q37910375 | ||
| Integration of virtual and high throughput screening in lead discovery settings. | Q37917802 | ||
| De novodesign: balancing novelty and confined chemical space | Q38029143 | ||
| Approaches to efficiently estimate solvation and explicit water energetics in ligand binding: the use of WaterMap | Q38071408 | ||
| Virtual screening strategies in drug discovery: a critical review. | Q38104785 | ||
| Impact of Computational Structure-based Methods on Drug Discovery | Q38129098 | ||
| Combination of ligand- and structure-based methods in virtual screening | Q38139474 | ||
| Recent advances in multidimensional QSAR (4D-6D): a critical review | Q38160267 | ||
| 3D-QSAR approaches in drug design: perspectives to generate reliable CoMFA models | Q38203930 | ||
| BP-Dock: a flexible docking scheme for exploring protein-ligand interactions based on unbound structures | Q41043727 | ||
| A detergent-based assay for the detection of promiscuous inhibitors | Q42007896 | ||
| PEP-SiteFinder: a tool for the blind identification of peptide binding sites on protein surfaces | Q42122972 | ||
| PepSite: prediction of peptide-binding sites from protein surfaces | Q42233071 | ||
| POOL server: machine learning application for functional site prediction in proteins. | Q42243409 | ||
| MDpocket: open-source cavity detection and characterization on molecular dynamics trajectories | Q42618711 | ||
| Detection of peptide-binding sites on protein surfaces: the first step toward the modeling and targeting of peptide-mediated interactions | Q42925767 | ||
| Multistep virtual screening for rapid and efficient identification of non-nucleoside bacterial thymidine kinase inhibitors | Q42963091 | ||
| Consensus docking: improving the reliability of docking in a virtual screening context | Q42988621 | ||
| Ligand-protein cross-docking with water molecules | Q43160905 | ||
| The discovery of Kv1.5 blockers as a case study for the application of virtual screening approaches | Q43437990 | ||
| Allosite: a method for predicting allosteric sites | Q43492056 | ||
| P433 | issue | 9 | |
| P921 | main subject | drug discovery | Q1418791 |
| P304 | page(s) | 1686-1701 | |
| P577 | publication date | 2015-07-25 | |
| P13046 | publication type of scholarly work | review article | Q7318358 |
| P1433 | published in | Archives of Pharmacal Research | Q13557312 |
| P1476 | title | Role of computer-aided drug design in modern drug discovery | |
| P478 | volume | 38 |
| Q89808093 | A computational approach yields selective inhibitors of human excitatory amino acid transporter 2 (EAAT2) |
| Q88361335 | An NMR strategy to detect conformational differences in a protein complexed with highly analogous inhibitors in solution |
| Q92084099 | Bioassay Directed Isolation, Biological Evaluation and in Silico Studies of New Isolates from Pteris cretica L |
| Q94953111 | COVID-19: CADD to the rescue |
| Q39027317 | Chalcone Derivatives: Promising Starting Points for Drug Design. |
| Q42276494 | Characterizing the Hot Spots Involved in RON-MSPβ Complex Formation Using In Silico Alanine Scanning Mutagenesis and Molecular Dynamics Simulation |
| Q40063790 | Chemical genetics-based development of small molecules targeting hepatitis C virus |
| Q59132978 | Chemoinformatics Strategies for Leishmaniasis Drug Discovery |
| Q59294029 | Classifying Calpain Inhibitors for the Treatment of Cataracts: A Self Organising Map (SOM) ANN/KM Approach in Drug Discovery |
| Q48232132 | Combined molecular modelling and 3D-QSAR study for understanding the inhibition of NQO1 by heterocyclic quinone derivatives |
| Q90164445 | Computationally Designed Peptides for Zika Virus Detection: An Incremental Construction Approach |
| Q64118692 | D3R Grand Challenge 3: blind prediction of protein-ligand poses and affinity rankings |
| Q50433350 | Demonstration of AutoDock as an Educational Tool for Drug Discovery. |
| Q60046976 | Editorial: Chemoinformatics Approaches to Structure- and Ligand-Based Drug Design |
| Q58697064 | Evolution of In Silico Strategies for Protein-Protein Interaction Drug Discovery |
| Q30398313 | Experimental conformational energy maps of proteins and peptides |
| Q93190439 | Exploring Novel N-Myristoyltransferase Inhibitors: A Molecular Dynamics Simulation Approach |
| Q48875877 | Fusing Docking Scoring Functions Improves the Virtual Screening Performance for Discovering Parkinson's Disease Dual Target Ligands |
| Q92078005 | Identification of Zika Virus NS2B-NS3 Protease Inhibitors by Structure-Based Virtual Screening and Drug Repurposing Approaches |
| Q61451256 | Identifying Protein Features Responsible for Improved Drug Repurposing Accuracies Using the CANDO Platform: Implications for Drug Design |
| Q64092935 | ImmtorLig_DB: repertoire of virtually screened small molecules against immune receptors to bolster host immunity |
| Q89597711 | In Silico Strategies in Tuberculosis Drug Discovery |
| Q53739072 | In silico binding mechanism prediction of benzimidazole based corticotropin releasing factor-1 receptor antagonists by quantitative structure activity relationship, molecular docking and pharmacokinetic parameters calculation |
| Q64072132 | In silico structural elucidation of RNA-dependent RNA polymerase towards the identification of potential Crimean-Congo Hemorrhagic Fever Virus inhibitors |
| Q93126855 | Molecular Docking: Shifting Paradigms in Drug Discovery |
| Q39438950 | Molecular docking and CoMFA studies of thiazoloquin(az)olin(on)es as CD38 inhibitors: determination of inhibitory mechanism, pharmacophore interactions, and design of new inhibitors. |
| Q37676906 | Multi-Functional Diarylurea Small Molecule Inhibitors of TRPV1 with Therapeutic Potential for Neuroinflammation |
| Q90589166 | Protein Preparation Automatic Protocol for High-Throughput Inverse Virtual Screening: Accelerating the Target Identification by Computational Methods |
| Q90047436 | Small Molecule Wnt Pathway Modulators from Natural Sources: History, State of the Art and Perspectives |
| Q64074484 | Structure Based Design and Molecular Docking Studies for Phosphorylated Tau Inhibitors in Alzheimer's Disease |
| Q59335445 | Structure and Function Studies of Asian Corn Borer Ostrinia furnacalis Pheromone Binding Protein2 |
| Q94589436 | Study of combining virtual screening and antiviral treatments of the Sars-CoV-2 (Covid-19) |
| Q64076270 | The Light and Dark Sides of Virtual Screening: What Is There to Know? |
| Q92620072 | The Methodological Trends of Traditional Herbal Medicine Employing Network Pharmacology |
| Q92723796 | The Promises and Challenges of Toxico-Epigenomics: Environmental Chemicals and Their Impacts on the Epigenome |
| Q94317027 | The rcdk and cluster R packages applied to drug candidate selection |
Search more.