Phenol mechanism of toxic action classification and prediction: a decision tree approach.
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 logK(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.
Ren
Shijin
S
Center for Environmental Biotechnology, 676 Dabney Hall, University of Tennessee, Knoxville, TN 37996-1605, USA. sjren@utk.edu
D000818:Animals; D003663:Decision Trees; D005544:Forecasting; D010636:Phenols / Q000633:toxicity*; D013329:Structure-Activity Relationship; D014874:Water Pollutants, Chemical / Q000633:toxicity*
D010636:Phenols; D014874:Water Pollutants, Chemical