| scholarly article | Q13442814 |
| review article | Q7318358 |
| P50 | author | Zoe Cournia | Q41047980 |
| P2093 | author name string | Demetrios K Vassilatis | |
| George Spyrou | |||
| Evanthia Lionta | |||
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| Characterization of small molecule binding. I. Accurate identification of strong inhibitors in virtual screening | Q28281920 | ||
| 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 | ||
| PDB2PQR: expanding and upgrading automated preparation of biomolecular structures for molecular simulations | Q29617524 | ||
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| Potential and limitations of ensemble docking | Q30415116 | ||
| Identifying specific kinase substrates through engineered kinases and ATP analogs | Q30433073 | ||
| Prediction of the water content in protein binding sites | Q30495095 | ||
| Complete reconstruction of an enzyme-inhibitor binding process by molecular dynamics simulations. | Q30501558 | ||
| GLARE: a new approach for filtering large reagent lists in combinatorial library design using product properties | Q33251329 | ||
| Enhancement of chemical rules for predicting compound reactivity towards protein thiol groups | Q33277028 | ||
| Virtual screening in drug discovery -- a computational perspective | Q33294074 | ||
| FAF-Drugs2: free ADME/tox filtering tool to assist drug discovery and chemical biology projects | Q33371792 | ||
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| Virtual screening - what does it give us? | Q33435433 | ||
| Fpocket: an open source platform for ligand pocket detection. | Q33457742 | ||
| Design of chemical libraries with potentially bioactive molecules applying a maximum common substructure concept | Q33494087 | ||
| Targeting multifunctional proteins by virtual screening: structurally diverse cytohesin inhibitors with differentiated biological functions | Q33627946 | ||
| Fast and automated functional classification with MED-SuMo: an application on purine-binding proteins. | Q33839028 | ||
| Improving VEGFR-2 docking-based screening by pharmacophore postfiltering and similarity search postprocessing | Q33850040 | ||
| The design and application of target-focused compound libraries | Q33882226 | ||
| The FAF-Drugs2 server: a multistep engine to prepare electronic chemical compound collections | Q33920633 | ||
| Using free energy of binding calculations to improve the accuracy of virtual screening predictions | Q33940014 | ||
| e-LEA3D: a computational-aided drug design web server | Q33957660 | ||
| A ‘Rule of Three’ for fragment-based lead discovery? | Q33973131 | ||
| Molecular properties that influence the oral bioavailability of drug candidates | Q34130727 | ||
| FTMAP: extended protein mapping with user-selected probe molecules | Q34270284 | ||
| Automated recycling of chemistry for virtual screening and library design | Q34289511 | ||
| The many roles of computation in drug discovery | Q34307063 | ||
| Drug-likeness and increased hydrophobicity of commercially available compound libraries for drug screening. | Q34349819 | ||
| Consensus Induced Fit Docking (cIFD): methodology, validation, and application to the discovery of novel Crm1 inhibitors | Q34440071 | ||
| Molecular modeling of organic and biomolecular systems using BOSS and MCPRO. | Q34456227 | ||
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| Fighting obesity with a sugar-based library: discovery of novel MCH-1R antagonists by a new computational-VAST approach for exploration of GPCR binding sites | Q34670175 | ||
| Role of the active-site solvent in the thermodynamics of factor Xa ligand binding | Q34748976 | ||
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| Physiochemical drug properties associated with in vivo toxicological outcomes | Q34806480 | ||
| Binding site detection and druggability index from first principles. | Q34964806 | ||
| Motifs for molecular recognition exploiting hydrophobic enclosure in protein-ligand binding | Q35612259 | ||
| Improving MM-GB/SA Scoring through the Application of the Variable Dielectric Model | Q35955749 | ||
| H++ 3.0: automating pK prediction and the preparation of biomolecular structures for atomistic molecular modeling and simulations | Q36088442 | ||
| Variability in docking success rates due to dataset preparation | Q36095634 | ||
| Docking and scoring with ICM: the benchmarking results and strategies for improvement | Q36098710 | ||
| Surflex-Dock: Docking benchmarks and real-world application | Q36098724 | ||
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| Structure-based discovery of antagonists of nuclear receptor LRH-1. | Q37000608 | ||
| Drug discovery beyond the 'rule-of-five'. | Q37012740 | ||
| Virtual screening and its integration with modern drug design technologies. | Q37066134 | ||
| Towards improving compound selection in structure-based virtual screening | Q37110770 | ||
| Discovery of human macrophage migration inhibitory factor (MIF)-CD74 antagonists via virtual screening | Q37187080 | ||
| Therapeutic potential of "rexinoids" in cancer prevention and treatment | Q37512933 | ||
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| Virtual screening strategies in drug discovery: a critical review. | Q38104785 | ||
| How does a drug molecule find its target binding site? | Q39280041 | ||
| Multiple structures for virtual ligand screening: defining binding site properties-based criteria to optimize the selection of the query | Q39487354 | ||
| Pose prediction and virtual screening performance of GOLD scoring functions in a standardized test. | Q39647348 | ||
| Substantial improvements in large-scale redocking and screening using the novel HYDE scoring function | Q39671594 | ||
| Free Energy Calculations Reveal the Origin of Binding Preference for Aminoadamantane Blockers of Influenza A/M2TM Pore | Q40296442 | ||
| Automated large-scale file preparation, docking, and scoring: evaluation of ITScore and STScore using the 2012 Community Structure-Activity Resource benchmark | Q41886859 | ||
| Recipes for the selection of experimental protein conformations for virtual screening | Q42081112 | ||
| Reproducing crystal binding modes of ligand functional groups using Site-Identification by Ligand Competitive Saturation (SILCS) simulations | Q42130025 | ||
| Quantifying the chemical beauty of drugs. | Q42414958 | ||
| SwissBioisostere: a database of molecular replacements for ligand design. | Q42430081 | ||
| MDpocket: open-source cavity detection and characterization on molecular dynamics trajectories | Q42618711 | ||
| Consensus docking: improving the reliability of docking in a virtual screening context | Q42988621 | ||
| CovalentDock: automated covalent docking with parameterized covalent linkage energy estimation and molecular geometry constraints | Q43816076 | ||
| Protein and ligand preparation: parameters, protocols, and influence on virtual screening enrichments | Q44012277 | ||
| P275 | copyright license | Creative Commons Attribution-NonCommercial 3.0 Unported | Q18810331 |
| P433 | issue | 16 | |
| P921 | main subject | enzyme | Q8047 |
| drug screening | Q10505555 | ||
| drug discovery | Q1418791 | ||
| mechanism of action | Q3271540 | ||
| virtual screening | Q4112105 | ||
| biomedical investigative technique | Q66648976 | ||
| P304 | page(s) | 1923-1938 | |
| P577 | publication date | 2014-01-01 | |
| P1433 | published in | Current Topics in Medicinal Chemistry | Q2734725 |
| P1476 | title | Structure-based virtual screening for drug discovery: principles, applications and recent advances | |
| P478 | volume | 14 |
| Q47995351 | A Pareto Algorithm for Efficient De Novo Design of Multi-functional Molecules. |
| Q92589923 | A Structure-Based Drug Discovery Paradigm |
| Q89808093 | A computational approach yields selective inhibitors of human excitatory amino acid transporter 2 (EAAT2) |
| Q89863068 | A novel EZH2 inhibitor induces synthetic lethality and apoptosis in PBRM1-deficient cancer cells |
| Q52352133 | A novel interaction fingerprint derived from per atom score contributions: exhaustive evaluation of interaction fingerprint performance in docking based virtual screening. |
| Q114864147 | A primer on natural product-based virtual screening |
| Q92163956 | A prospective compound screening contest identified broader inhibitors for Sirtuin 1 |
| Q39842778 | Adapting Document Similarity Measures for Ligand-Based Virtual Screening. |
| Q55281306 | Allosteric binding sites in Rab11 for potential drug candidates. |
| Q41696939 | An iterative compound screening contest method for identifying target protein inhibitors using the tyrosine-protein kinase Yes. |
| Q55044864 | Aromatic Rings Commonly Used in Medicinal Chemistry: Force Fields Comparison and Interactions With Water Toward the Design of New Chemical Entities. |
| Q58555308 | BCPA {,'-1,4-Butanediylbis[3-(2-chlorophenyl)acrylamide]} Inhibits Osteoclast Differentiation through Increased Retention of Peptidyl-Prolyl Isomerase Never in Mitosis A-Interacting 1 |
| Q90053091 | Basic Limonoid modulates Chaperone-mediated Proteostasis and dissolve Tau fibrils |
| Q44606676 | Beauvericin counteracted multi-drug resistant Candida albicans by blocking ABC transporters. |
| Q30392142 | Beyond Membrane Protein Structure: Drug Discovery, Dynamics and Difficulties |
| Q39027317 | Chalcone Derivatives: Promising Starting Points for Drug Design. |
| Q52590901 | Chemical probes and drug leads from advances in synthetic planning and methodology. |
| Q57307431 | Chemical space of Escherichia coli dihydrofolate reductase inhibitors: New approaches for discovering novel drugs for old bugs |
| Q92420815 | Comparison of Target Features for Predicting Drug-Target Interactions by Deep Neural Network Based on Large-Scale Drug-Induced Transcriptome Data |
| Q38612789 | Computational allosteric ligand binding site identification on Ras proteins. |
| Q47889903 | Computer aided drug design and its application to the development of potential drugs for neurodegenerative disorders |
| Q47571750 | Congestion game scheduling for virtual drug screening optimization. |
| Q89647207 | Covalent Complex of DNA and Bacterial Topoisomerase: Implications in Antibacterial Drug Development |
| Q36447801 | DARC: Mapping Surface Topography by Ray-Casting for Effective Virtual Screening at Protein Interaction Sites |
| Q49221491 | Decoys Selection in Benchmarking Datasets: Overview and Perspectives. |
| Q91944343 | DeepBindPoc: a deep learning method to rank ligand binding pockets using molecular vector representation |
| Q90633197 | Design and Selection of Novel C1s Inhibitors by In Silico and In Vitro Approaches |
| Q37631651 | Design, Synthesis and Antifungal Activity Evaluation of New Thiazolin-4-ones as Potential Lanosterol 14α-Demethylase Inhibitors |
| Q60162743 | Development of NMR and thermal shift assays for the evaluation of isocitrate lyase inhibitors |
| Q91642873 | Discovery and Characterisation of Dual Inhibitors of Tryptophan 2,3-Dioxygenase (TDO2) and Indoleamine 2,3-Dioxygenase 1 (IDO1) Using Virtual Screening |
| Q40335742 | Discovery of Cdc25A Lead Inhibitors with a Novel Chemotype by Virtual Screening: Application of Pharmacophore Modeling Based on a Training Set with a Limited Number of Unique Components |
| Q91962741 | Discovery of Immunoproteasome Inhibitors Using Large-Scale Covalent Virtual Screening |
| Q38687108 | Discovery of Potent ALK Inhibitors Using Pharmacophore-Informatics Strategy |
| Q42364599 | Discovery of a Low Toxicity O-GlcNAc Transferase (OGT) Inhibitor by Structure-based Virtual Screening of Natural Products |
| Q48220585 | Drugging tRNA aminoacylation. |
| Q55669060 | Endocrine Disruption at the Androgen Receptor: Employing Molecular Dynamics and Docking for Improved Virtual Screening and Toxicity Prediction. |
| Q42320200 | Enhancing Virtual Screening Performance of Protein Kinases with Molecular Dynamics Simulations |
| Q56273707 | Expanding the medicinal chemistry synthetic toolbox |
| Q38821099 | Exploiting computationally derived out-of-the-box protein conformations for drug design. |
| Q53076714 | Exploring G Protein-Coupled Receptors (GPCRs) Ligand Space via Cheminformatics Approaches: Impact on Rational Drug Design. |
| Q57162600 | G-quadruplex virtual drug screening: A review |
| Q64284066 | Gypsum-DL: an open-source program for preparing small-molecule libraries for structure-based virtual screening |
| Q92726916 | Hidden bias in the DUD-E dataset leads to misleading performance of deep learning in structure-based virtual screening |
| Q56993529 | Identification of Antifungal Targets Based on Computer Modeling |
| Q41181786 | Identification of Direct Activator of Adenosine Monophosphate-Activated Protein Kinase (AMPK) by Structure-Based Virtual Screening and Molecular Docking Approach. |
| Q47286701 | Identification of Novel Aurora Kinase A (AURKA) Inhibitors via Hierarchical Ligand-Based Virtual Screening. |
| Q47129732 | Identification of candidate drugs using tensor-decomposition-based unsupervised feature extraction in integrated analysis of gene expression between diseases and DrugMatrix datasets. |
| Q64092935 | ImmtorLig_DB: repertoire of virtually screened small molecules against immune receptors to bolster host immunity |
| Q92863081 | In silico Methods for Design of Kinase Inhibitors as Anticancer Drugs |
| Q38638421 | In silico studies in drug research against neurodegenerative diseases |
| Q40082701 | In-silico profiling of the biological activities of Amaryllidaceae alkaloids. |
| Q89803412 | Inhibition of striatal-enriched protein tyrosine phosphatase by targeting computationally revealed cryptic pockets |
| Q93200291 | Integrating Ligand and Target-Driven Based Virtual Screening Approaches With in vitro Human Cell Line Models and Time-Resolved Fluorescence Resonance Energy Transfer Assay to Identify Novel Hit Compounds Against BCL-2 |
| Q102633498 | Interpretable Deep Learning in Drug Discovery |
| Q47218921 | Investigating Protein-Ligand Interactions by Solution Nuclear Magnetic Resonance Spectroscopy. |
| Q91942928 | Ligand biological activity predicted by cleaning positive and negative chemical correlations |
| Q92221080 | Ligity: A Non-Superpositional, Knowledge-Based Approach to Virtual Screening |
| Q42695969 | Machine Learning Accelerates MD-based Binding-Pose Prediction between Ligands and Proteins |
| Q45946918 | Machine Learning Consensus Scoring Improves Performance Across Targets in Structure-Based Virtual Screening. |
| Q91809228 | Mimicking Strategy for Protein-Protein Interaction Inhibitor Discovery by Virtual Screening |
| Q38807251 | Modern approaches to accelerate discovery of new antischistosomal drugs. |
| Q91657657 | Molecular Architect: A User-Friendly Workflow for Virtual Screening |
| Q47163647 | Molecular Connectivity Predefines Polypharmacology: Aliphatic Rings, Chirality, and sp3 Centers Enhance Target Selectivity |
| Q90062519 | Molecular Dynamics Simulation Framework to Probe the Binding Hypothesis of CYP3A4 Inhibitors |
| Q50932369 | Molecular Quantum Similarity, Chemical Reactivity and Database Screening of 3D Pharmacophores of the Protein Kinases A, B and G from Mycobacterium tuberculosis. |
| Q26800097 | Molecular docking and structure-based drug design strategies |
| Q64090194 | Molecular modeling simulation studies reveal new potential inhibitors against HPV E6 protein |
| Q92128125 | N-Methylparoxetine Blocked Autophagic Flux and Induced Apoptosis by Activating ROS-MAPK Pathway in Non-Small Cell Lung Cancer Cells |
| Q38334179 | Natural products as leads in schistosome drug discovery. |
| Q98224481 | Novel TRPV1 Channel Agonists With Faster and More Potent Analgesic Properties Than Capsaicin |
| Q47965977 | Novel series of 1,2,4-trioxane derivatives as antimalarial agents |
| Q50089879 | Overview of Methods and Strategies for Conducting Virtual Small Molecule Screening. |
| Q57009477 | P2Rank: machine learning based tool for rapid and accurate prediction of ligand binding sites from protein structure |
| Q92217698 | Patient and Disease-Specific Induced Pluripotent Stem Cells for Discovery of Personalized Cardiovascular Drugs and Therapeutics |
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| Q90430431 | Pharmmaker: Pharmacophore modeling and hit identification based on druggability simulations |
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| Q90153399 | Proposing the Promiscuous Protein Structures in JNK1 and JNK3 for Virtual Screening in Pursuit of Potential Leads |
| Q90589166 | Protein Preparation Automatic Protocol for High-Throughput Inverse Virtual Screening: Accelerating the Target Identification by Computational Methods |
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| Q38553677 | Role of computer-aided drug design in modern drug discovery. |
| Q64078787 | SNP2SIM: a modular workflow for standardizing molecular simulation and functional analysis of protein variants |
| Q96834102 | Signature-based approaches for informed drug repurposing: targeting CNS disorders |
| Q91635347 | Structure-Based Screening of Plasmodium berghei Glutathione S-Transferase Identifies CB-27 as a Novel Antiplasmodial Compound |
| Q89683270 | Structure-Based Virtual Screening of Pseudomonas aeruginosa LpxA Inhibitors Using Pharmacophore-Based Approach |
| Q98205051 | Structure/activity virtual screening and in vitro testing of small molecule inhibitors of 8-hydroxy-5-deazaflavin:NADPH oxidoreductase from gut methanogenic bacteria |
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| Q47690085 | Tailored Approaches in Drug Development and Diagnostics: From Molecular Design to Biological Model Systems |
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| Q38995015 | Targeting of AMP-activated protein kinase: prospects for computer-aided drug design |
| Q51061506 | Targeting the ubiquitin-conjugating enzyme E2D4 for cancer drug discovery-a structure-based approach. |
| Q38782563 | The Development of Target-Specific Pose Filter Ensembles To Boost Ligand Enrichment for Structure-Based Virtual Screening. |
| Q90455206 | The LSD1 inhibitor iadademstat (ORY-1001) targets SOX2-driven breast cancer stem cells: a potential epigenetic therapy in luminal-B and HER2-positive breast cancer subtypes |
| Q64076270 | The Light and Dark Sides of Virtual Screening: What Is There to Know? |
| Q49717083 | The discovery of novel HDAC3 inhibitors via virtual screening and in vitro bioassay. |
| Q90203330 | The role of water and protein flexibility in the structure-based virtual screening of allosteric GPCR modulators: an mGlu5 receptor case study |
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| Q92215786 | Towards accurate high-throughput ligand affinity prediction by exploiting structural ensembles, docking metrics and ligand similarity |
| Q38728101 | Towards pharmacological intervention in inositol pyrophosphate signalling |
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| 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. |
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| Q91088060 | Virtual Screening in the Cloud: How Big Is Big Enough? |
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