Molecular basis for the resistance of American sloughgrass to aryloxyphenoxypropionic acid pesticides and its environmental relevance: A combined experimental and computational study.

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. Image 1 • Target-site mutation in American sloughgrass will aggravate pesticide pollution. • The changes in enzyme bioaffinity can greatly affect the pesticides usage. • Computational findings are negatively related to the results of bioassay testing. • Computational screening models could be used for reducing environmental stress. [ABSTRACT FROM AUTHOR]