Sakineh Bashiri pirbazari - Department of chemistry, zanjan Branch, payam noor University, zanjan, Iran
Ghasem Ghasemi - Department of chemistry, Rasht Branch, Islamic Azad University, Rasht, Iran
Atosa Bashiri pirbazari - Department of chemistry, Rasht Branch, Islamic Azad University, Rasht, Iran

Quantitative structure activity relationship models are regression or classification models used in the chemical and biological sciences and engineering. QSAR models first summarize a supposed relationship between chemical structures and biological activity in a data-set of chemicals. Second predict the activities of new chemicals. For example, biological activity can be expressed quantitatively as the concentration of a substance required to give a certain biological response. In work, quantitative structure activites relationship study has been done on pentanamide Compounds analogues acting stomach cancer inhibitors. Genetic algorithm , artificial neural network and multiple linear regression were used to create the non-linear and linear QSAR models. GA-ANN model was much better than other models. Hyperchem, Chemoffice and Gaussian 30 softwares were used for geometry optimization of the molecules and calculation of the quantum chemical descriptors. The root- mean- square errors of the training set and the test set for GA-ANN model using jack-knife were 310100, 319201, R9 = 31.0. Also, the R and R9 values were obtained 3.21, 3123 from GA-stepwise MLR model.

QSAR, Hydroxyl pentanamide , Genetic algorithm, Stomach cancer, Artificial neural network