Evaluating the predictivity of virtual screening for ABL kinase inhibitors to hinder drug resistance
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Evaluating the predictivity of virtual screening for ABL kinase inhibitors to hinder drug resistance. / Gani, Osman A B S M; Narayanan, Dilip; Engh, Richard A.
In: Chemical Biology & Drug Design, Vol. 82, No. 5, 11.2013, p. 506-19.Research output: Contribution to journal › Journal article › Research › peer-review
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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.
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.
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
VL - 82
SP - 506
EP - 519
JO - Chemical Biology and Drug Design (Print)
JF - Chemical Biology and Drug Design (Print)
SN - 1747-0277
IS - 5
ER -
ID: 172765641