利用各种分子对接工具对氯菊酯-人血红蛋白结合进行结构表征

IF 3.1 Q2 TOXICOLOGY
Shweta Singh, Priyanka Gopi, Prateek Pandya, Jyoti Singh
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引用次数: 0

摘要

氯菊酯(PMT)是一种常用的拟除虫菊酯类杀虫剂,因其对多种生物(包括昆虫、水生生物和哺乳动物,包括血红蛋白(HB)人)的毒性作用而闻名。为了评估其与HB靶点的潜在结合,使用不同的软件进行了分子对接模拟。每个软件都有独特的算法和评分方法。使用多种工具帮助我们更好地确认和理解交互。结果表明,在各种对接web服务器之间具有较高的绑定强度。PMT-HB络合通过疏水相互作用和范德华力在很大程度上稳定了。此外,PMT与血红素的结合距离相当远,这表明它不会干扰HB的基本生物学功能,即氧的结合。此外,毒理学参数分析显示PMT具有急性口服和皮肤毒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Structural characterization of permethrin-human hemoglobin binding using various molecular docking tools

A molecular docking investigation was conducted to study the interaction between permethrin (PMT), a commonly used pyrethroid insecticide, known for its toxic effects on various organisms, including insects, aquatic life, and mammals, including humans with hemoglobin (HB). To assess its potential binding with the HB target, molecular docking simulations were conducted using different software. Each software has unique algorithms and scoring methods. Employing multiple tools helped us confirm and understand the interaction better. The results indicated high binding strengths across the various docking web servers. The PMT-HB complexation was largely stabilized via the hydrophobic interactions and Van der Waals forces. Also, PMT exhibited binding at a significant distance from the heme, indicating that it does not interfere with the essential biological function of HB, which is the binding of oxygen. In addition, the analysis of toxicological parameters revealed that PMT possesses the ability to induce acute oral and dermal toxicity.

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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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