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Accurate and Validated Quantitative Structure–Activity Relationship Model of Caspase‐mediated Apoptosis‐inducing Activity of Phenolic Compounds Using Density Functional Theory Calculation and Genetic Algorithm–Multiple Linear Regression by Jin Chang; Beilei Lei; Jiazhong Li; Shuyan Li; Yulin Shen; Xiaojun Yao is a Chemistry article available to read on EtoBox.

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## Abstract In this work, an accurate and validated Quantitative Structure–Activity Relationship (QSAR) model was developed for the caspase‐mediated apoptosis‐inducing effect of 52 substituted phenolic compounds in a murine leukemia cell line (L1210). All molecules were optimized by the Density Functional Theory (DFT) to obtain lowest energy conformations. The whole dataset was divided into representative training and test sets using DUPLEX method. Then, Multiple Linear Regression (MLR) method was used to build QSAR models based on the descriptors selected by Genetic Algorithm (GA) using training set samples. The built models were rigorously validated both internally and externally. The obtained model based on DFT optimized geometry is better than that based on semi‐empirical optimized geometry and the published work with the correlation coefficient (__R__^2^) of 0.938 for the training set and 0.939 for the test set. The result is discussed in the light of the main features that influence the inducing activity of caspase‐mediated apoptosis.

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Author

Jin Chang; Beilei Lei; Jiazhong Li; Shuyan Li; Yulin Shen; Xiaojun Yao

Publisher

John Wiley and Sons; Wiley (John Wiley & Sons); John Wiley & Sons Ltd.; Wiley (ISSN 1611-020X)

Published

2008

Language

EN

Field

Chemistry (Physical Sciences)