%0 Journal Article
%T Exploring drug repositioning possibilities of kinase inhibitors via molecular simulation.
%A Wang QX
%A Cai J
%A Chen ZJ
%A Liu JC
%A Wang JJ
%A Zhou H
%A Li QQ
%A Wang ZX
%A Wang YB
%A Tong ZJ
%A Yang J
%A Wei TH
%A Zhang MY
%A Zhou Y
%A Dai WC
%A Ding N
%A Leng XJ
%A Yin XY
%A Sun SL
%A Yu YC
%A Li NG
%A Shi ZH
%J Mol Inform
%V 0
%N 0
%D 2024 Jun 21
%M 39031899
%F 4.05
%R 10.1002/minf.202300336
%X Kinases, a class of enzymes controlling various substrates phosphorylation, are pivotal in both physiological and pathological processes. Although their conserved ATP binding pockets pose challenges for achieving selectivity, this feature offers opportunities for drug repositioning of kinase inhibitors (KIs). This study presents a cost-effective in silico prediction of KIs drug repositioning via analyzing cross-docking results. We established the KIs database (278 unique KIs, 1834 bioactivity data points) and kinases database (357 kinase structures categorized by the DFG motif) for carrying out cross-docking. Comparative analysis of the docking scores and reported experimental bioactivity revealed that the Atypical, TK, and TKL superfamilies are suitable for drug repositioning. Among these kinase superfamilies, Olverematinib, Lapatinib, and Abemaciclib displayed enzymatic activity in our focused AKT-PI3K-mTOR pathway with IC50 values of 3.3, 3.2 and 5.8 μM. Further cell assays showed IC50 values of 0.2, 1.2 and 0.6 μM in tumor cells. The consistent result between prediction and validation demonstrated that repositioning KIs via in silico method is feasible.