ArticleActa pharmacologica Sinica2009
Pharmacophore-based virtual screening versus docking-based virtual screening: a benchmark comparison against eight targets.
Article in Acta pharmacologica Sinica, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed.
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- In silico identification of prospective p53-MDM2 inhibitors from ASINEX database using a comprehensive molecular modelling approach.Scientific reports · 2025Article
- Evaluating ligand docking methods for drugging protein-protein interfaces: insights from AlphaFold2 and molecular dynamics refinement.Journal of cheminformatics · 2025Article
- Structural Bioinformatics Applied to Acetylcholinesterase Enzyme Inhibition.International journal of molecular sciences · 2025Review
- Molecular Docking in Drug Discovery: Techniques, Applications, and Advancements.Current medicinal chemistry · 2025Review
- Computational prediction of CNP0387675 as a non-nucleoside inhibitor of MraY, from natural product-based multi-template screening againstFrontiers in microbiology · 2025Article
- In silico design of dehydrophenylalanine containing peptide activators of glucokinase using pharmacophore modelling, molecular dynamics and machine learning: implications in type 2 diabetes.Journal of computer-aided molecular design · 2024Article
- Molecular Regulator Driving Endometriosis Towards Endometrial Cancer: A Multi-Scale Computational Investigation to Repurpose Anti-Cancer drugs.Cell biochemistry and biophysics · 2024Article
- Advances in Drug Discovery and Design using Computer-aided Molecular Modeling.Current computer-aided drug design · 2024Review
- InhibitingPharmaceuticals (Basel, Switzerland) · 2023Article
- Exploration of a Large Virtual Chemical Space: Identification of Potent Inhibitors of Lactate Dehydrogenase-A against Pancreatic Cancer.Journal of chemical information and modeling · 2023Article
- Article
- Identification and Validation of Novel Biomarkers and Potential Targeted Drugs in Cholangiocarcinoma: Bioinformatics, Virtual Screening, and Biological Evaluation.Journal of microbiology and biotechnology · 2022Article
- Discovery of Anticancer Activity of Amentoflavone on Esophageal Squamous Cell Carcinoma: Bioinformatics, Structure-Based Virtual Screening, and Biological Evaluation.Journal of microbiology and biotechnology · 2022Article
- Drug Design-Past, Present, Future.Molecules (Basel, Switzerland) · 2022Review
- Virtual Combinatorial Chemistry and Pharmacological Screening: A Short Guide to Drug Design.International journal of molecular sciences · 2022Review
- Ligand and structure-based approaches for the exploration of structure-activity relationships of fusidic acid derivatives as antibacterial agents.Frontiers in chemistry · 2022Article
- Discovery of Small Molecules as Membrane-Bound Catechol-Pharmaceuticals (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimThis study was conducted to compare the efficiencies of two virtual screening approaches, pharmacophore-based virtual screening (PBVS) and docking-based virtual screening (DBVS) methods.
methodsAll virtual screens were performed on two data sets of small molecules with both actives and decoys against eight structurally diverse protein targets, namely angiotensin converting enzyme (ACE), acetylcholinesterase (AChE), androgen receptor (AR), D-alanyl-D-alanine carboxypeptidase (DacA), dihydrofolate reductase (DHFR), estrogen receptors alpha (ERalpha), HIV-1 protease (HIV-pr), and thymidine kinase (TK). Each pharmacophore model was constructed based on several X-ray structures of protein-ligand complexes. Virtual screens were performed using four screening standards, the program Catalyst for PBVS and three docking programs (DOCK, GOLD and Glide) for DBVS.
resultsOf the sixteen sets of virtual screens (one target versus two testing databases), the enrichment factors of fourteen cases using the PBVS method were higher than those using DBVS methods. The average hit rates over the eight targets at 2% and 5% of the highest ranks of the entire databases for PBVS are much higher than those for DBVS.
conclusionThe PBVS method outperformed DBVS methods in retrieving actives from the databases in our tested targets, and is a powerful method in drug discovery.
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