Quantitative structure–activity relationship methods for the prediction of the toxicity of pollutants

被引：0
作者：
Raghunath Satpathy
机构：
[1] MITS Engineering College,Department of Biotechnology
来源：
Environmental Chemistry Letters | 2019年 / 17卷
关键词：
Biodegradation; Computational tools; Database; Descriptors; Environmental toxicity; Quantitative structure–activity relationship modeling; Validation methods; Risk assessment; Toxic compounds;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Continuous flow of toxic and persistent compounds to the environment is a global health issue. However, assessing the toxic effects of compounds is a difficult task, because some compounds may possess a combined effect during exposure. Moreover, toxicity evaluation by animal testing is long and costly. Alternatively, modeling of quantitative structure–activity relationships (QSAR) can be used to predict the acute toxicity of molecules. Properties of toxic compounds are computed and correlated using softwares and databases. Recently, this method has found potential applications for the risk assessment of several untested, toxic chemicals. This review focuses on quantitative structure–activity relationship modeling methods for the analysis of toxic compounds. Computational tool and databases are presented.
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页码：123 / 128
页数：5
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