QSAR Study of Polychlorinated Dibenzodioxins, Dibenzofurans, and Biphenyls using the Heuristic Method and Support Vector Machine

Abstract

AbstractQuantitative structure activity relationship (QSAR) models for polychlorinated dibenzofurans (PCDFs), dibenzodioxins (PCDDs), and biphenyls (PCBs) binding to the aryl hydrocarbon receptor (AhR) have been developed based on the Heuristic Method (HM) and Support Vector Machine (SVM). Since various members of all three classes of compounds have been shown to produce qualitatively similar toxicities, a combination of the different classes for each bioactivity were performed in one QSAR study. A subset of five molecular descriptors selected by HM in CODESSA was used as inputs for SVM. The results obtained by none linear SVM model were compared with those obtained by the linear heuristic method. The prediction result of the SVM model is better than that obtained by HM. The model of SVM leads to a correlation coefficient (R) of 0.928 and mean‐square error (MSE) of 0.324 for the test set and the values for HM model are 0.845 and 0.667 respectively. This QSAR models provide a rapid, simple and valid way to model the PCDFs, PCDDs, and PCBs binding affinity in relation to the aryl hydrocarbon receptor (AhR).