Abstract

The research was carried out in order to study the molecular mechanisms of herbicide binding (pinoxaden, quizalofop-P-tefuril, prometrin, metribuzin, metsulfuron-methyl) with target proteins (acetyl-CoA-carboxylase, acetolactate synthase, cytochrome P450, 4-hydroxyphenylpyruvate dioxygenase) of weeds growing in Siberia: common wild oat (Avena fatua L.), couch grass (Elymus repens (L.) Gould), red-root amaranthus (Amaranthus retroflexus L.), white gauze (Chenopodium album L.), and green foxtail (Setaria viridis (L) P Beauv). The study was carried out in Novosibirsk oblast in 2022–2023. Using the bioinformatic methods, virtual three-dimensional complexes of pesticides and their targets have been created. A new approach to identifying the parameters of the cavity of binding sites is proposed, which consists in combining the alignment method and the machine-learning technology. Docking of pesticides with targets has been carried out. Calculation of the binding energy indicates a high degree of stability of the ligand-protein complexes. The proposed in silico approach may be useful for elucidating the behavior of herbicides when bound to weed enzymes. This approach allows a deeper understanding of the mechanism of action and ecotoxicological aspects of pesticide use. The complexes of herbicides and proteins involved have a potential high stability due to the low energy of binding to receptors, which varies from –5.60 to –13.24 kcal/mol. The value of the binding energy has not shown a direct dependence on the number of amino acid residues of the ligand-binding site. In general, the study has complemented some aspects of the molecular mechanisms of herbicide binding to weed target proteins; however, more in-depth study is required in order to localize critical amino acid points involved in the biological functions of target proteins.

中文翻译：

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利用计算机模拟方法研究除草剂与杂草目标蛋白结合的分子机制

摘要

该研究的目的是研究除草剂（唑啉草酯、精喹禾灵、普罗灭林、赛克津、甲磺隆）与靶蛋白（乙酰辅酶A羧化酶、乙酰乳酸合酶、细胞色素 P450、4-西伯利亚杂草：普通野燕麦 ( Avena fatua L.)、茅草 ( Elymus repens (L.) Gould)、红根苋 ( Amaranthus Retroflexus L.)、白纱布 ( Chenopodium album L.)和绿狐尾草 ( Setaria viridis（左）P 博夫）。该研究于 2022 年至 2023 年在新西伯利亚州进行。利用生物信息学方法，创建了农药及其靶标的虚拟三维复合物。提出了一种识别结合位点腔体参数的新方法，该方法包括将对齐方法与机器学习技术相结合。已开展农药与靶点对接。结合能的计算表明配体-蛋白质复合物具有高度的稳定性。所提出的计算机方法可能有助于阐明除草剂与杂草酶结合时的行为。这种方法可以更深入地了解农药使用的作用机制和生态毒理学方面。除草剂和相关蛋白质的复合物由于与受体结合的能量较低（从 –5.60 到 –13.24 kcal/mol），因此具有潜在的高稳定性。结合能的值并未显示出对配体结合位点的氨基酸残基数量的直接依赖性。总的来说，这项研究补充了除草剂与杂草目标蛋白结合的分子机制的某些方面；然而，需要更深入的研究来定位参与靶蛋白生物学功能的关键氨基酸点。该研究补充了除草剂与杂草目标蛋白结合的分子机制的某些方面；然而，需要更深入的研究来定位参与靶蛋白生物学功能的关键氨基酸点。该研究补充了除草剂与杂草目标蛋白结合的分子机制的某些方面；然而，需要更深入的研究来定位参与靶蛋白生物学功能的关键氨基酸点。