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This paper deals with developing a linear quantitative structure-activity   relationship (QSAR) model for predicting the RSK inhibition activity of some   new compounds. A dataset consisting of 62 pyrazino [1,2-α] indole, diazepino   [1,2-α] indole, and imidazole derivatives with known inhibitory activities   was used. Multiple linear regressions (MLR) technique combined with the   stepwise (SW) and the genetic algorithm (GA) methods as variable selection   tools was employed. For more checking stability, robustness and   predictability of the proposed models, internal and external validation   techniques were used. Comparison of the results obtained, indicate that the   GA-MLR model is superior to the SW-MLR model and that it isapplicable for   designing novel RSK inhibitors

Application of genetic algorithm - multiple linear regressions to predict the activity of RSK inhibitors