Development of Prediction Models for the Mutagenicity of Nitrated-PAHs Based on Multiple Linear Regression

Abstract

Nitrated polycyclic aromatic hydrocarbons (NPAHs) are a family of toxicants wide spreading in the environment. In this study, quantitative structural-activity relationship (QSAR) models were developed for the prediction of mutagenicity of NPAHs. Structural descriptors were screened and multiple linear regression (MLR) were performed for developing the QSAR models. Totally 1706 descriptors were obtained based on structural optimization using density functional theory (DFT) at the CPCM-B3LYP/6-311+g (d,p) theoretical level in water. External and leave-one-out cross validation were performed to confirm the predictive ability and the models robustness, respectively. Totally 33 QSAR models were generated using one to eight descriptors, in which the model consisting of 4 descriptors, including Eelec, SIC2, RDF040v and GATS4v, has the highest correlation coefficient (R2=0.8755). This study will contribute to not only the prediction of the mutagenicity of NPAHs, but also the development of QSAR modeling methods of toxicants.