Structure-based quantitative structure-activity relationship studies of checkpoint kinase 1 inhibitors

Abstract

Structure-based quantitative structure-activity relationship (QSAR) studies on a series of checkpoint kinase 1 (Chk1) inhibitors were performed to find the key structural features responsible for their inhibitory activity. Molecular docking was employed to explore the binding mode of all inhibitors at the active site of Chk1 and determine the active conformation for the QSAR studies. Ligand and structure-based descriptors incorporating the ligand-receptor interaction were generated based on the docked complex. Genetic Algorithm-Multiple Linear Regression (GA-MLR) method was used to build 2D QSAR model. The 2D QSAR model gave a squared correlation coefficient R(2) of 0.887, cross-validated Q(2) of 0.837 and the prediction squared correlation coefficient R(2)(pred) of 0.849, respectively. Furthermore, three-dimensional quantitative structure-activity relationship (3D QSAR) model using comparative molecular field analysis (CoMFA) with R(2) of 0.983, Q(2) of 0.550 and R(2)(pred) of 0.720 was also developed. The obtained results are helpful for the design of novel Chk1 inhibitors with improved activities.