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QSTR studies on the mutagenicity of Anilines

机译:QSTR研究苯胺的致突变性

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Quantitative structure-toxicity 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 (R~2=0.87, SE=0.78, Rcv~2=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.
机译:定量结构毒性关系(QSTR)研究在毒性预测中发挥着重要作用,并且广泛用于现代化合物的研究。苯胺代表了最重要的环境化学品类别之一。其中大多数可能导致严重的公共卫生和环境问题。目前的作品是开发一种有效的Qstr模型,用于致突变性,毒理学终点,其具有癌症的显着决定因素。我们计算了各种描述符并使用了线性回归方式来选择相关参数,并构建了与Log P,ELUMO和地层热量相关的QSTR模型(R〜2 = 0.87,SE = 0.78,RCV〜2 = 0.867585,F = 89.034)。该模型显示出良好的预测能力。基于描述符,提出了毒性机制的进一步讨论。结果表明,Log P值对苯胺毒性最重要的影响。

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