title: Is it possible to increase hit rates in structure-based virtual screening by pharmacophore filtering? An investigation of the advantages and pitfalls of post-filtering.
abstract: We have investigated the influence of post-filtering virtual screening results, with pharmacophoric features generated from an X-ray structure, on enrichment rates. This was performed using three docking softwares, zdock+, Surflex and FRED, as virtual screening tools and pharmacophores generated in UNITY from co-crystallized complexes. Sets of known actives along with 9997 pharmaceutically relevant decoy compounds were docked against six chemically diverse protein targets namely CDK2, COX2, ERalpha, fXa, MMP3, and NA. To try to overcome the inherent limitations of the well-known docking problem, we generated multiple poses for each compound. The compounds were first ranked according to their scores alone and enrichment rates were calculated using only the top scoring pose of each compound. Subsequently, all poses for each compound were passed through the different pharmacophores generated from co-crystallized complexes and the enrichment factors were re-calculated based on the top-scoring passing pose of each compound. Post-filtering with a pharmacophore generated from only one X-ray complex was shown to increase enrichment rates in all investigated targets compared to docking alone. This indicates that this is a general method, which works for diverse targets and different docking softwares.
authors.affiliation: Department of Medicinal Chemistry, Division of Organic Pharmaceutical Chemistry, BMC, Uppsala University, P.O. Box 574, SE-751 23 Uppsala, Sweden.
authors.forename: Daniel
authors.initials: D
authors.lastname: Muthas
authors.forename: Yogesh A
authors.initials: YA
authors.lastname: Sabnis
authors.forename: Magnus
authors.initials: M
authors.lastname: Lundborg
authors.forename: Anders
authors.initials: A
authors.lastname: Karlén
mesh_terms: D000465:Algorithms; D001665:Binding Sites; D003198:Computer Simulation; D018360:Crystallography, X-Ray; D051357:Cyclin-Dependent Kinase 2; D051546:Cyclooxygenase 2 / Q000737:chemistry; D015195:Drug Design; D047628:Estrogen Receptor alpha / Q000737:chemistry; D015951:Factor Xa / Q000737:chemistry; D006801:Humans; D006860:Hydrogen Bonding; D019278:Matrix Metalloproteinase 3 / Q000737:chemistry; D008958:Models, Molecular; D015394:Molecular Structure; D008970:Molecular Weight; D009439:Neuraminidase / Q000737:chemistry; D011485:Protein Binding; D021281:Quantitative Structure-Activity Relationship; D012372:ROC Curve; D012984:Software
chemical_list: D047628:Estrogen Receptor alpha; D051546:Cyclooxygenase 2; C495894:CDK2 protein, human; D051357:Cyclin-Dependent Kinase 2; D009439:Neuraminidase; D015951:Factor Xa; D019278:Matrix Metalloproteinase 3