QSAR analysis of the toxicity of phenols and thiophenols using MLR and ANN

This study gives a quantitative structure-activity relationship (QSAR) analysis of toxicity of phenols and thiophenols to Photobacterium phosphoreum, which is an important indicator for water quality. The chemical structures of 51 phenols and thiophenols have been characterized by electronic and physic-chemical descriptors. The present study was performed using principal components analysis (PCA), multiple regression analysis (MLR) and artificial neural network (ANN). The quantitative model was accordingly proposed and the toxicity of the compounds was interpreted based on the multivariate statistical analysis. This study shows that the results obtained by MLR were suitable and have served to predict toxicity, but compared to the results of the ANN model, we conclude that the prediction achieved by the latter is more effective and better than MLR model. The statistical results of the predictive performance indicate that the ANN model is statistically significant than the previous reported model based on CART-LS-SVR. Following to the obtained results, our proposed model may be useful to predict of toxicity and risk assessment of chemicals.
Source: Journal of Taibah University for Science - Category: Science Source Type: research