Mahmoud Saeedi Kelishami - Department of Applied mathematics, Rasht Branch ,Islamic Azad University, Rasht, Iran
Ghasem Ghasemi - Department of Chemistry, Rasht Branch, Islamic Azad University, Rasht, Iran

At present study, quantitative structure activites relationship (QSAR) study has been done on 03chemical compounds of pyridinone analogues as anti HIVprodrug. Genetic algorithm (GA), Artificial neural network (ANN), Multiple linear regression (MLR), partial least squares (PLS), principal component regression (PCR), and least absolute shrinkage and selection operator (LASSO) were used to create QSAR models. The root mean square error of the calibration and R2 using MLR method were obtained as 334000 and 33.0, respectively. The R2 value using LASSO method were obtained as 33.0.The root mean square error of the calibration and R2 using PLS method were obtained as 3332 and 33.., respectively. According to the obtained results, it was found that GA-PLS model is the most favorable method in comparison with other statistical methods and is suitable for use in QSAR models.

QSAR, Pyridinone, Genetic algorithm, Artificial neural network