Abstract
Quantitative structuretoxicity relationship (QSTR) studies play an important role in toxicity predicting, and is widely used in the study of modern compounds. Anilines represent one of the most important classes of environmental chemicals. Most of them may cause serious public health and environmental problems. The present work is to develop an effective QSTR model for mutagenicity, a toxicological endpoint which has a significant determinant of cancers, of Anilines. We calculated various descriptors and used linear regression way to select relevant parameters, and built a QSTR model that was correlation with Log P, ELUMO and heat of formation (R2=0.87, SE=0.78, Rcv2=0.867585, F=89.034). The model showed a good forecasting ability. Based on the descriptors, a further discussion was presented for the toxic mechanism. The results show that Log P value has the most important effect on anilines toxicity.
Published Version
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