Genetic algorithm for CoMFA setting optimization: 3D‐QSAR study on α‐aminosuberic acid derivatives as anti‐cancer compounds

In most three‐dimensional quantitative structure–activity relationship studies, default SYBYL parameters for comparative molecular field analysis (CoMFA) have been used to derive the models. In this work, a genetic algorithm has been employed for the first time to select the best set of parameters. Three‐dimensional quantitative structure–activity relationship analysis of a set of 33 analogues of α‐aminosuberic acid as a new generation of histone deacetylase inhibitors was performed. Contrary to the ordinary and region focusing CoMFA models, in genetic algorithm optimized model, H‐bond was the preferred field type. Genetic algorithm optimized model showed a better predictive ability (r²_pred = 0.982, q²_LOO = 0.828, and q²_LMO = 0.795) compared with ordinary (r²_pred = 0.937, q²_LOO = 0.629, and q²_LMO = 0.537) and region focusing (r²_pred = 0.954, q²_LOO = 0.665, and q²_LMO = 0.564) models derived by CoMFA default set of parameters. Copyright © 2013 John Wiley & Sons, Ltd.