Development of CHARMM compatible force field parameters and molecular dynamics simulations for the pesticide flupyradifurone

IF 3.4 3区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY
Zakaria Bouchouireb, Steeve H. Thany, Jean-Yves Le Questel
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引用次数: 0

Abstract

Flupyradifurone (FLU) is a novel butenolide insecticide with partial agonist activity for insect nicotinic acetylcholine receptors. Its safety for non-target organisms has been questioned in the literature, despite initial claims of its harmlessness. Detailed understanding of its toxicity and related molecular mechanisms remain under discussion. Thus, in this work, an optimized set of CHARMM compatible parameters for FLU is presented. CHARMM General Force Field program was used as a starting point while the non-bonded and bonded parameters were adjusted and optimized to reproduce MP2/6-31G(d) accuracy level results. For the validity assessment of these parameters, infrared spectrum, water-octanol partition coefficient, and normal modes were computed and compared to experimental values found in the literature. Several MD simulations of FLU in water and FLU in complex with an acetylcholine-binding protein were performed to estimate the ability of the optimized parameters to correctly describe its torsional space and reproduce observed crystallographic trends respectively.

Abstract Image

Abstract Image

农药氟吡喃酮CHARMM兼容力场参数及分子动力学模拟的建立。
氟吡喃醌是一种新型丁烯内酯类杀虫剂,对昆虫烟碱乙酰胆碱受体具有部分激动剂活性。尽管最初声称其无害,但其对非目标生物的安全性在文献中受到质疑。对其毒性和相关分子机制的详细了解仍在讨论中。因此,在这项工作中,提出了一组优化的CHARMM兼容FLU参数。以CHARMM通用力场程序为起点,调整和优化非粘结和粘结参数,重现MP2/6-31G(d)精度水平结果。为了评估这些参数的有效性,我们计算了红外光谱、水-辛醇分配系数和正态模态,并与文献中的实验值进行了比较。本文对水中的流感和与乙酰胆碱结合蛋白的流感复合物进行了MD模拟,分别评估了优化参数正确描述其扭转空间和再现观察到的晶体学趋势的能力。
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来源期刊
CiteScore
6.60
自引率
3.30%
发文量
247
审稿时长
1.7 months
期刊介绍: This distinguished journal publishes articles concerned with all aspects of computational chemistry: analytical, biological, inorganic, organic, physical, and materials. The Journal of Computational Chemistry presents original research, contemporary developments in theory and methodology, and state-of-the-art applications. Computational areas that are featured in the journal include ab initio and semiempirical quantum mechanics, density functional theory, molecular mechanics, molecular dynamics, statistical mechanics, cheminformatics, biomolecular structure prediction, molecular design, and bioinformatics.
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