QSAR modeling the toxicity of pesticides against Americamysis bahia

被引:29
作者
Yang, Lu [1 ,2 ]
Wang, Yinghuan [1 ]
Chang, Jing [1 ]
Pan, Yifan [1 ,2 ]
Wei, Ruojin [1 ,2 ]
Li, Jianzhong [1 ]
Wang, Huili [1 ]
机构
[1] Chinese Acad Sci, Res Ctr Ecoenvironm Sci, 18 Shuangqing Rd, Beijing 100085, Peoples R China
[2] Univ Chinese Acad Sci, Yuquan RD 19A, Beijing 100049, Peoples R China
基金
中国国家自然科学基金;
关键词
QSAR; Americamysis bahia; Toxicity; Pesticides; RISK-ASSESSMENT; CORRELATION-COEFFICIENT; VALIDATION; PREDICTION; PARAMETERS; REGRESSION; INSECTICIDES;
D O I
10.1016/j.chemosphere.2020.127217
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The widespread use of pesticides has received increasing attention in regulatory agencies because their extensive overuse and various adverse effects on all living organisms. Organizations such as EPA and ECHA have published laws that pesticides should be fully evaluated before bring them to market. In the present study, we evaluated the pesticides toxicity using the Quantitative Structural-Activity Relationship (QSAR) method. The models for the single class pesticides (herbicides, insecticides and fungicides) as well as the general class pesticides (the combined dataset plus some microbicides, molluscicides, etc.) were developed using the Genetic Algorithm and Multiple Linear Regression method. The internal and external validation results suggested that all the obtained models were stable and predictive. According to the modeling descriptors, the lipophilic descriptors contributed positively while all the electrotopological state descriptors showed a negative contribution, their presences in every model verified the conspicuous influence of molecular lipophilicity and hydrophilicity on the pesticides toxicity. However, the influence of topological structure descriptors was different and varies with the physiochemical information they encode. Finally, the models presented in this paper would help assess the pesticides toxicity against Americamysis bahia, shorten test time, and reduce the cost of pesticides risk assessment. (C) 2020 Elsevier Ltd. All rights reserved.
引用
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页数:8
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