Combining DFT and QSAR result for predicting the toxicity of a series of substituted phenols

The DFT-B3LYP method, with the basis set 6-31G (d), was employed to calculate some quantum chemical descriptors of 31 substituted phenols compounds. The best descriptors were selected to establish the quantitative structure activity relationship (QSAR) of the toxicity of these compounds to Rana japonica tadpoles by principal components analysis (PCA), to a multiple regression analysis (MLR), to a non-linear regression (RNLM) and to an artificial neural network (ANN). We accordingly propose a quantitative model, and we interpret the activity of the compounds relying on the multivariate statistical analysis. This study shows that the prediction results were in excellent agreement with the experimental value.