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Banaei, Alireza, Pourbasheer, Eslam, Haggi, Fatemeh. (1395). QSAR studies and application of genetic algorithm - multiple linear regressions in prediction of novel p2x7 receptor antagonists’ activity. فصلنامه علمی زیست فناوری گیاهان زراعی, 4(Issue 3, pp. 236-358, Serial No. 12), 318-336.
Alireza Banaei; Eslam Pourbasheer; Fatemeh Haggi. "QSAR studies and application of genetic algorithm - multiple linear regressions in prediction of novel p2x7 receptor antagonists’ activity". فصلنامه علمی زیست فناوری گیاهان زراعی, 4, Issue 3, pp. 236-358, Serial No. 12, 1395, 318-336.
Banaei, Alireza, Pourbasheer, Eslam, Haggi, Fatemeh. (1395). 'QSAR studies and application of genetic algorithm - multiple linear regressions in prediction of novel p2x7 receptor antagonists’ activity', فصلنامه علمی زیست فناوری گیاهان زراعی, 4(Issue 3, pp. 236-358, Serial No. 12), pp. 318-336.
Banaei, Alireza, Pourbasheer, Eslam, Haggi, Fatemeh. QSAR studies and application of genetic algorithm - multiple linear regressions in prediction of novel p2x7 receptor antagonists’ activity. فصلنامه علمی زیست فناوری گیاهان زراعی, 1395; 4(Issue 3, pp. 236-358, Serial No. 12): 318-336.

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

Iranian chemical communication
مقاله 21، دوره 4، Issue 3, pp. 236-358, Serial No. 12، مهر 2016، صفحه 318-336    اصل مقاله (251.34 K)
نوع مقاله: Original Research Article
نویسندگان
Alireza Banaei1؛ Eslam Pourbasheer* 1؛ Fatemeh Haggi2
1Department of Chemistry, Payame Noor University (PNU), P. O. Box 19395-3697
2Department of Chemistry, Payame Noor University (PNU), P. O. Box 19395-3697, Tehran, Iran
چکیده
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.
کلیدواژه‌ها
QSAR؛ genetic algorithms؛ P2x7 receptor antagonists؛ Purine derivatives
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