期刊
CHEMOSPHERE
卷 235, 期 -, 页码 1030-1040出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chemosphere.2019.07.044
关键词
Risk assessment; Aryloxyphenoxypropionic acid pesticides; Homology modeling; Screening model; Target-site mutation
资金
- Chang'an Scholars Construction Project [201806CT016]
- State Key Laboratory of the Discovery and Development of Novel Pesticide [2016NYRD02]
- Shandong Provincial Natural Science Foundation [ZR2016CQ02, ZR2016CP19]
- Project of Shandong Province Higher Educational Science and Technology Program [J16LF05]
Organic pesticides are one of the main environmental pollutants, and how to reduce their environmental risks is an important issue. In this contribution, we disclose the molecular basis for the resistance of American sloughgrass to aryloxyphenoxypropionic acid pesticides using site-directed mutagenesis and molecular modeling and then construct an effective screening model. The results indicated that the target-site mutation (Trp-1999-Leu) in acetyl-coenzyme A carboxylase (ACCase) can affect the effectiveness of the pesticides (clodinafop, fenoxaprop, cyhalofop, and metamifop), and the plant resistance to fenoxaprop, clodinafop, cyhalofop, and metamifop was found to be 564, 19.5, 10, and 0.19 times, respectively. The established computational models (i.e. wild-type/mutant ACCase models) could be used for rational screening and evaluation of the resistance to pesticides. The resistance induced by target gene mutation can markedly reduce the bioreactivity of the ACCase-clodinafop/fenoxaprop adducts, and the magnitudes are 10 and 102, respectively. Such event will seriously aggravate environmental pollution. However, the biological issue has no distinct effect on cyhalofop (RI = 10), and meanwhile it may markedly increase the bioefficacy of metamifop (RI = 0.19). We could selectively adopt the two chemicals so as to decrease the residual pesticides in the environment. Significantly, research findings from the computational screening models were found to be negatively correlated with the resistance level derived from the bioassay testing, suggesting that the screening models can be used to guide the usage of pesticides. Obviously, this story may shed novel insight on the reduction of environmental risks of pesticides and other organic pollutants. (C) 2019 Elsevier Ltd. All rights reserved.
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