Evaluating the predictivity of virtual screening for ABL kinase inhibitors to hinder drug resistance

TY - JOUR

T1 - Evaluating the predictivity of virtual screening for ABL kinase inhibitors to hinder drug resistance

AU - Gani, Osman A B S M

AU - Narayanan, Dilip

AU - Engh, Richard A

N1 - © 2013 John Wiley & Sons A/S.

PY - 2013/11

Y1 - 2013/11

N2 - 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 ABL1 and its drug-resistant mutant ABL1-T315I. '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. Virtual screenings were performed on ABL1 kinase to study inhibitors for wild type and T315 mutant form. In addition, chemoinformatic methods were also applied on kinase inhibitors. We show that virtual screening and ligand-based studies are complementary in understanding the features that should be considered during in silico studies.

AB - 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 ABL1 and its drug-resistant mutant ABL1-T315I. '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. Virtual screenings were performed on ABL1 kinase to study inhibitors for wild type and T315 mutant form. In addition, chemoinformatic methods were also applied on kinase inhibitors. We show that virtual screening and ligand-based studies are complementary in understanding the features that should be considered during in silico studies.

KW - Algorithms

KW - Area Under Curve

KW - Binding Sites

KW - Drug Evaluation, Preclinical

KW - Drug Resistance, Neoplasm

KW - Enzyme Activation

KW - Humans

KW - Ligands

KW - Molecular Docking Simulation

KW - Mutation

KW - Principal Component Analysis

KW - Protein Binding

KW - Protein Kinase Inhibitors

KW - Protein Structure, Tertiary

KW - Proto-Oncogene Proteins c-abl

KW - ROC Curve

KW - Recombinant Proteins

KW - Journal Article

U2 - 10.1111/cbdd.12170

DO - 10.1111/cbdd.12170

M3 - Journal article

C2 - 23746052

SN - 1747-0277

VL - 82

SP - 506

EP - 519

JO - Chemical Biology & Drug Design

JF - Chemical Biology & Drug Design

IS - 5

ER -