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

Juan Du, Lili Xi, Beilei Lei, Jing Lu, Jiazhong Li, Huanxiang Liu, Xiaojun Yao

研究成果: Article同行評審

7 引文 斯高帕斯(Scopus)

摘要

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 R2 of 0.887, cross-validated Q2 of 0.837 and the prediction squared correlation coefficient R 2pred of 0.849, respectively. Furthermore, three-dimensional quantitative structure-activity relationship (3D QSAR) model using comparative molecular field analysis (CoMFA) with R2 of 0.983, Q2 of 0.550 and R2pred of 0.720 was also developed. The obtained results are helpful for the design of novel Chk1 inhibitors with improved activities.

原文English
頁(從 - 到)2783-2793
頁數11
期刊Journal of Computational Chemistry
31
發行號15
DOIs
出版狀態Published - 30 11月 2010
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