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Evaluating the Predictivity of Virtual Screening for A bl Kinase Inhibitors to Hinder Drug Resistance
Author(s) -
Gani Osman A. B. S. M.,
Narayanan Dilip,
Engh Richard A.
Publication year - 2013
Publication title -
chemical biology and drug design
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.59
H-Index - 77
eISSN - 1747-0285
pISSN - 1747-0277
DOI - 10.1111/cbdd.12170
Subject(s) - virtual screening , decoy , chemical space , docking (animal) , computational biology , drug discovery , ligand efficiency , drug , ligand (biochemistry) , chemistry , combinatorial chemistry , chemical library , computer science , small molecule , pharmacology , biochemistry , biology , medicine , receptor , nursing
Virtual screening methods are now widely used in early stages of drug discovery, aiming to rank potential inhibitors. However, any practical ligand set (of active or inactive compounds) chosen for deriving new virtual screening approaches cannot fully represent all relevant chemical space for potential new compounds. In this study, we have taken a retrospective approach to evaluate virtual screening methods for the leukemia target kinase ABL 1 and its drug‐resistant mutant ABL 1‐ T 315 I . ‘Dual active’ inhibitors against both targets were grouped together with inactive ligands chosen from different decoy sets and tested with virtual screening approaches with and without explicit use of target structures (docking). We show how various scoring functions and choice of inactive ligand sets influence overall and early enrichment of the libraries. Although ligand‐based methods, for example principal component analyses of chemical properties, can distinguish some decoy sets from active compounds, the addition of target structural information via docking improves enrichment, and explicit consideration of multiple target conformations (i.e. types I and II ) achieves best enrichment of active versus inactive ligands, even without assuming knowledge of the binding mode. We believe that this study can be extended to other therapeutically important kinases in prospective virtual screening studies.