Quantitative structureeactivity relationship (QSAR) method was used to predict the pIC50 value of 58 derivatives of 6-methoxy benzamides in this work. The artificial neural network (ANN) and multiple linear regressions (MLR) were used to construct the non-linear and linear QSAR models, respectively. The standard errors in the prediction of pIC50 for training, internal and external test sets, are; 0.280, 0.446 and 0.382 by MLR model and are; 0.175, 0.326 and 0.296 by ANN model, respectively. Also these models were further examined by cross-validation methods which produce the statistics of Q2 ¼ 0.8340 and SPRESS ¼ 0.322 for MLR model and Q2 ¼ 0.8055 and SPRESS ¼ 0.219 for ANN model
