Identification of potential human targets of glyphosate using in silico target fishing

IF 3.1 Q2 TOXICOLOGY
Alejandro Gómez, Andrés Alarcón, Wilson Acosta, Andrés Malagón
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引用次数: 0

Abstract

Glyphosate is a widely used herbicide known for its effectiveness in weed control; and it is an inhibitor of the plant enzyme 5-enolpyruvylshikimate-3-phosphate synthase. Currently, it is one of the most extensively used non-specific herbicides in agroindustry. However, toxic effects of glyphosate have recently been reported, including endocrine disruption, metabolic alterations, teratogenic, tumorigenic, and hepatorenal effects. Additionally, there are environmental concerns related to possible interactions with proteins from microorganisms, aquatic organisms, and mammals.

Research on the description of these interactions has gained interest, primarily with the aim of generating recommendations in terms of its use and possible regulations. On the other hand, computational methods have emerged to identify potential targets or unintended targets among numerous possible receptors. Several programs, online services, and databases are available for use in these methods.

In this study, we employed a set of online tools for computational target fishing to identify receptors of glyphosate. A set of thirteen targets were selected using six fishing tools. Furthermore, docking procedures were performed to investigate the expected interactions and binding energies. Certain associations with diseases are also reported.

Abstract Image

利用硅学靶标钓法确定草甘膦的潜在人体靶标
草甘膦是一种广泛使用的除草剂,因其在除草方面的功效而闻名;它是植物酶 5-enolpyruvylshikimate-3-phosphate 合成酶的抑制剂。目前,草甘膦是农用工业中使用最广泛的非特异性除草剂之一。然而,最近有报道称草甘膦具有毒性作用,包括干扰内分泌、改变新陈代谢、致畸、致肿瘤和肝肾作用。此外,草甘膦可能与微生物、水生生物和哺乳动物的蛋白质发生相互作用,这也引起了人们对环境问题的关注。对这些相互作用进行描述的研究引起了人们的兴趣,其主要目的是就草甘膦的使用和可能的法规提出建议。另一方面,在众多可能的受体中识别潜在目标或非预期目标的计算方法已经出现。在本研究中,我们使用了一套在线工具来计算草甘膦的受体。本研究采用了一套在线工具来计算草甘膦受体的捕获,并使用六种捕获工具选择了十三个靶标。此外,我们还执行了对接程序,以研究预期的相互作用和结合能。此外,还报告了与疾病的某些关联。
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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