Phenol mechanism of toxic action classification and prediction: a decision tree approach

Abstract

In this study, the use of decision tree in classifying and predicting the aquatic toxicity mechanisms of phenols was investigated. Four mechanisms including polar narcosis, respiratory uncoupling, pro-electrophilicity, and soft electrophilicity were involved. Using molecular descriptors as splitting variables, a three level decision tree with six terminal nodes was obtained. The tree model first separated polar narcosis/pro-electrophilicity from respiratory uncoupling/soft electrophilicity by E lumo in the first level of the tree. In subsequent levels of the tree, polar narcosis was separated from pro-electrophilicity by N hdon and E homo, and respiratory uncoupling was separated from soft electrophilicity by E lumo and log K ow . Validation of the decision tree approach indicated that the overall mechanism prediction accuracy was approximately 85%. The decision tree model had the advantage of easy interpretation.