3D-QSAR Analysis on ATR Protein Kinase Inhibitors Using CoMFA and CoMSIA
Xiurong Li, Mao Shu, Yuanqiang Wang, Rui Yu, Shuang Yao and Zhihua LinAffiliation:
School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing 400054, China.
AbstractAtaxia telangiectasia-mutated and Rad3-related (ATR) protein kinase is an attractive anticancer target. In this study, comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) were performed on a series of aminopyrazine ATR inhibitors. The models generated by CoMFA had a cross-validated coefficient (q2) of 0.752 and a regression coefficient (r2) of 0.947. The CoMSIA models had a q2 of 0.728 and an r2 of 0.936. The reasonable quantitative structure-activity relationship model showed robust predictive ability. The contour map provided guidelines for building novel virtual compounds based on compound NO.40. In addition, the 3D structure of ATR was modeled by homology modeling. Molecular dynamic simulations were employed to optimize the structure. The docking results offered insights into the interactions between the inhibitors and the active site for potent analysis. This study provides useful guidance for the discovery of more potent compounds.
ATR inhibitor, 3D-QSAR, CoMFA, CoMSIA, docking, homology modeling, molecular design.
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