Computational perspectives on Chlorpyrifos and its degradants as human glutathione S-transferases inhibitors: DFT calculations, molecular docking study and MD simulations

IF 3.1 Q2 TOXICOLOGY
Nikita Tiwari , Anil Mishra
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引用次数: 2

Abstract

Chlorpyrifos is the toxicant chemical from the class of organophosphorus insecticides. The insecticide undergoes environmental degradation to chlorpyrifos‐oxon (CPYO), des‐ethyl chlorpyrifos (DEC), 3,5,6‐trichloro‐2‐methoxypyridine (TMP) and 3,5,6‐trichloro‐2‐pyridinol (TCP). Herein, CPF along with its degradants were optimized employing density functional theory (DFT) and B3LYP/6-311G+(d,p) basis set to elucidate their thermal and frontier molecular orbital properties. The DFT outcome revealed that TCP showed the lowest HOMO-LUMO gap (4.38 eV), also highest dipole moment, electrophilicity index and basicity. Docking was done using AutoDock 4.2.6 against human glutathione S-transferases to search binding affinity and interactions of all pollutants with the protein. The docking results expressed that TCP required least binding energy (−5.51 kcal mol−1) which is relatable to the DFT studies and might act as the most powerful inhibitor. GROMACS 5.1.1 was utilized to perform simulation studies for each ligand–protein docked complexes. Results concluded that CPF, DEC, TMP, CPYO and TCP could possibly perform as toxic and inhibit enzymatic activity by interrupting the metabolic pathways in humans.

毒死蜱及其降解物作为人谷胱甘肽S-转移酶抑制剂的计算前景:DFT计算、分子对接研究和MD模拟
毒死蜱是有机磷类杀虫剂中的有毒化学物质。该杀虫剂在环境中降解为毒死蜱-氧(CPYO)、去乙基毒死蜱(DEC)、3,5,6‐三氯‐2‐甲氧基吡啶(TMP)和3,5,6‐三氯‐2‐吡啶(TCP)。本文采用密度泛函理论(DFT)和B3LYP/6-311G+(d,p)基集对CPF及其降解物进行了优化,阐明了它们的热性质和前沿分子轨道性质。DFT结果显示,TCP具有最低的HOMO-LUMO间隙(4.38 eV)、最高的偶极矩、亲电性指数和碱度。使用AutoDock 4.2.6对人谷胱甘肽s -转移酶进行对接,以搜索所有污染物与蛋白质的结合亲和力和相互作用。对接结果表明,TCP所需的结合能最小(- 5.51 kcal mol - 1),这与DFT研究相关,可能是最有效的抑制剂。利用GROMACS 5.1.1对每个配体-蛋白对接复合物进行模拟研究。结果表明,CPF、DEC、TMP、CPYO和TCP可能通过阻断人体代谢途径发挥毒性和抑制酶活性的作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Computational Toxicology
Computational Toxicology Computer Science-Computer Science Applications
CiteScore
5.50
自引率
0.00%
发文量
53
审稿时长
56 days
期刊介绍: Computational Toxicology is an international journal publishing computational approaches that assist in the toxicological evaluation of new and existing chemical substances assisting in their safety assessment. -All effects relating to human health and environmental toxicity and fate -Prediction of toxicity, metabolism, fate and physico-chemical properties -The development of models from read-across, (Q)SARs, PBPK, QIVIVE, Multi-Scale Models -Big Data in toxicology: integration, management, analysis -Implementation of models through AOPs, IATA, TTC -Regulatory acceptance of models: evaluation, verification and validation -From metals, to small organic molecules to nanoparticles -Pharmaceuticals, pesticides, foods, cosmetics, fine chemicals -Bringing together the views of industry, regulators, academia, NGOs
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