qsar studies and application of genetic algorithm - multiple linear regressions in prediction of novel p2x7 receptor antagonists’ activity

quantitative structure-activity relationship (qsar) models were employed for prediction the activity of p2x7 receptor antagonists. a data set consisted of 50 purine derivatives was utilized in the model construction where 40 and 10 of these compounds were in the training and test sets respectively. a suitable group of calculated molecular descriptors was selected by employing stepwise multiple linear regressions (sw-mlr) and genetic algorithm-multiple linear regressions (ga-mlr) as variable selection tools. the proposed mlr models were fully confirmed applying internal and external validation techniques. the obtained results of this qsar study showed the superiority of the ga-mlr model over the sw-mlr model. as a result, the obtained ga–mlr model could be applied as a valuable model for designing similar groups of p2x7 receptor antagonists.