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Glide:  A New Approach for Rapid, Accurate Docking and Scoring. 2. Enrichment Factors in Database Screening

Journal of Medicinal Chemistry · 2004 · Vol. 47(7) · pp. 1750–1759
Thomas A. HalgrenRobert B. MurphyRichard A. FriesnerHege S. BeardLeah L. FryeW. Thomas PollardJay L. Banks

Abstract

Glide's ability to identify active compounds in a database screen is characterized by applying Glide to a diverse set of nine protein receptors. In many cases, two, or even three, protein sites are employed to probe the sensitivity of the results to the site geometry. To make the database screens as realistic as possible, the screens use sets of "druglike" decoy ligands that have been selected to be representative of what we believe is likely to be found in the compound collection of a pharmaceutical or biotechnology company. Results are presented for releases 1.8, 2.0, and 2.5 of Glide. The comparisons show that average measures for both "early" and "global" enrichment for Glide 2.5 are 3 times higher than for Glide 1.8 and more than 2 times higher than for Glide 2.0 because of better results for the least well-handled screens. This improvement in enrichment stems largely from the better balance of the more widely parametrized GlideScore 2.5 function and the inclusion of terms that penalize ligand-protein interactions that violate established principles of physical chemistry, particularly as it concerns the exposure to solvent of charged protein and ligand groups. Comparisons to results for the thymidine kinase and estrogen receptors published by Rognan and co-workers (J. Med. Chem. 2000, 43, 4759-4767) show that Glide 2.5 performs better than GOLD 1.1, FlexX 1.8, or DOCK 4.01.

Computational Drug Discovery MethodsMonoclonal and Polyclonal Antibodies ResearchReceptor Mechanisms and SignalingDocking (animal)DOCKChemistryDatabaseLigand (biochemistry)Virtual screeningProtein Data BankComputational biologyReceptorCombinatorial chemistry

MeSH terms

Binding SitesLigandsModels, MolecularMolecular ConformationProtein ConformationProteinsDrug DesignMolecular StructureDatabases, FactualQuantitative Structure-Activity Relationship
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