Evaluating the predictivity of virtual screening for ABL kinase inhibitors to hinder drug resistance.
Bottom Line: 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.
Affiliation: The Norwegian Structural Biology Center, Department of Chemistry, University of Tromsø, 9037, Tromsø, Norway.Show MeSH
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Mentions: Despite some overlap, active inhibitors and DUD decoys map to distinguishable volumes in chemical space (Figure6A). This itself provides information to filter sets of potential inhibitors to eliminate compounds that match decoys rather than inhibitors. In contrast, plotting ABL1-wt selective inhibitors versus dual active ABL1 inhibitors does not distinguish the sets (Figure6B) in the major PC dimensions.
Affiliation: The Norwegian Structural Biology Center, Department of Chemistry, University of Tromsø, 9037, Tromsø, Norway.