Iranian chemical communication 2423-4958 4 Issue 3, pp. 236-358, Serial No. 12 2016 07 01 QSAR studies and application of genetic algorithm - multiple linear regressions in prediction of novel p2x7 receptor antagonists’ activity 318 336 2218 EN Alireza Banaei Department of Chemistry, Payame Noor University (PNU), P. O. Box 19395-3697 Eslam Pourbasheer Department of Chemistry, Payame Noor University (PNU), P. O. Box 19395-3697 Fatemeh Haggi Department of Chemistry, Payame Noor University (PNU), P. O. Box 19395-3697, Tehran, Iran Journal Article 2015 07 25 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. https://icc.journals.pnu.ac.ir/article_2218_58904f61641264f060152628a967b698.pdf