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Acta Pharmacologica Sinica
Article . 2009 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
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Pharmacophore-based virtual screening versus docking-based virtual screening: a benchmark comparison against eight targets

Authors: Zhi, Chen; Hong-lin, Li; Qi-jun, Zhang; Xiao-guang, Bao; Kun-qian, Yu; Xiao-min, Luo; Wei-liang, Zhu; +1 Authors

Pharmacophore-based virtual screening versus docking-based virtual screening: a benchmark comparison against eight targets

Abstract

This study was conducted to compare the efficiencies of two virtual screening approaches, pharmacophore-based virtual screening (PBVS) and docking-based virtual screening (DBVS) methods.All 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.Of 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.The PBVS method outperformed DBVS methods in retrieving actives from the databases in our tested targets, and is a powerful method in drug discovery.

Related Organizations
Keywords

Models, Molecular, Databases, Factual, Molecular Conformation, Proteins, Crystallography, X-Ray, Ligands, Drug Design, HIV-1, Animals, Humans, Software, Protein Binding

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
99
Top 1%
Top 10%
Top 10%
bronze