Toxicity of Halogen, Sulfur and Chlorinated Aromatic Compounds: A Quantitative-Structure-Toxicity-Relationship (QSTR)

Ashutosh Gupta, A. Chakraborty, S. Giri, V. Subramanian, P. Chattaraj
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引用次数: 10

Abstract

In this paper, quantitative–structure–toxicity–relationship (QSTR) models are developed for predicting the toxicity of halogen, sulfur and chlorinated aromatic compounds. Two sets of compounds, containing mainly halogen and sulfur inorganic compounds in the first set and chlorinated aromatic compounds in the second, are investigated for their toxicity level with the aid of the conceptual Density Functional Theory (DFT) method. Both sets are tested with the conventional density functional descriptors and with a newly proposed net electrophilicity descriptor. Associated R2, R2CV and R2adj values reveal that in the first set, the proposed net electrophilicity descriptor (??±) provides the best result, whereas in the second set, electrophilicity index (?) and a newly proposed descriptor, net electrophilicity index (??±) provide a comparable performance. The potential of net electrophilicity index to act as descriptor in development of QSAR model is also discussed.
卤素、硫和氯化芳香族化合物的毒性:数量-结构-毒性关系(QSTR)
本文建立了定量的 -结构- -毒性-关系(QSTR)模型来预测卤素、硫和氯代芳香族化合物的毒性。本文利用密度泛函理论(DFT)方法研究了两组化合物的毒性水平,第一组化合物主要含卤素和硫无机化合物,第二组化合物主要含氯化芳香族化合物。用传统的密度泛函描述符和新提出的净亲电性描述符对这两组进行了测试。相关的R2、R2CV和R2adj值显示,在第一组中,提出的净亲电性描述符(? ±)提供了最好的结果,而在第二组中,亲电性指数(?)和新提出的描述符,净亲电性指数(? ±)提供了相当的性能。本文还讨论了净亲电性指数作为描述符在QSAR模型发展中的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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