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Structure‐based quantitative structure‐activity relationship studies of checkpoint kinase 1 inhibitors
Author(s) -
Du Juan,
Xi Lili,
Lei Beilei,
Lu Jing,
Li Jiazhong,
Liu Huanxiang,
Yao Xiaojun
Publication year - 2010
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.21571
Subject(s) - quantitative structure–activity relationship , chemistry , correlation coefficient , stereochemistry , linear regression , docking (animal) , computational biology , computer science , biology , machine learning , medicine , nursing
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 predof 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 predof 0.720 was also developed. The obtained results are helpful for the design of novel Chk1 inhibitors with improved activities. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010