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用于鉴定基孔肯雅甲病毒nsP3天然抑制剂的生物电子等排体和虚拟筛选方法

Bioisosteric and Virtual Screening Approach to Identify Natural Inhibitors of Chikunguya alphavirus nsP3.

作者信息

Lopes Cássia Milene Ribeiro, de Araújo Leonardo Pereira, Mariano Caio Pacífico, Falleiros Lorena, de Azevedo Junior Walter Filgueira, Coelho Luiz Felipe Leomil, da Silveira Nelson José Freitas

机构信息

Laboratory of Molecular Modeling and Computer Simulation, Federal University of Alfenas (UNIFAL), Alfenas, Minas Gerais, Brazil.

Laboratory of Molecular Biology of Microorganisms, Federal University of Alfenas (UNIFAL), Alfenas, Minas Gerais, Brazil.

出版信息

Cell Biochem Biophys. 2025 Aug 26. doi: 10.1007/s12013-025-01849-5.

Abstract

Chikungunya fever is an arboviral disease characterized by high fever, rash, and intense polyarthralgia, which may persist and evolve into a chronic condition, significantly impairing quality of life. The etiological agent, Chikungunya virus (CHIKV), is an alphavirus transmitted by Aedes aegypti mosquitoes and represents an increasing global public health concern due to its epidemic potential, economic burden, and the lack of specific antiviral therapies. In this context, in silico methodologies have become valuable tools in drug discovery and repurposing. This study aimed to predict natural compounds capable of inhibiting CHIKV non-structural protein 3 (nsP3). A total of 84,215 natural compounds from the ZINC20 database were screened through molecular docking using AutoDock Vina, with nsP3 as the target receptor. Ligand-protein interactions were visualized and analyzed with LigPlot+ and PyMOL. The top candidates were further refined through bioisosteric modifications using MolOpt, and their pharmacokinetic properties were predicted via the pkCSM platform. Among the optimized molecules, three bioisosteres, Chikv_bio1, Chikv_bio2, and Chikv_bio3, demonstrated favorable docking scores, interaction profiles, and ADMET properties, suggesting promising inhibitory activity against nsP3. These findings support the potential of natural compound-based drug design and highlight the importance of advancing to in vitro and in vivo validation to confirm the therapeutic relevance of these candidates and contribute to the development of specific treatments for Chikungunya fever.

摘要

基孔肯雅热是一种虫媒病毒病,其特征为高热、皮疹和严重的多关节痛,这些症状可能持续并演变成慢性疾病,严重损害生活质量。病原体基孔肯雅病毒(CHIKV)是一种由甲蚊传播的甲病毒,由于其流行潜力、经济负担以及缺乏特异性抗病毒疗法,已成为全球日益关注的公共卫生问题。在这种背景下,计算机模拟方法已成为药物发现和重新利用的宝贵工具。本研究旨在预测能够抑制基孔肯雅病毒非结构蛋白3(nsP3)的天然化合物。使用AutoDock Vina通过分子对接对ZINC20数据库中的84,215种天然化合物进行了筛选,以nsP3作为靶标受体。使用LigPlot+和PyMOL对配体-蛋白质相互作用进行了可视化和分析。通过使用MolOpt进行生物电子等排体修饰对顶级候选物进行了进一步优化,并通过pkCSM平台预测了它们的药代动力学性质。在优化的分子中,三种生物电子等排体Chikv_bio1、Chikv_bio2和Chikv_bio3表现出良好的对接分数、相互作用图谱和ADMET性质,表明对nsP3具有有前景的抑制活性。这些发现支持了基于天然化合物的药物设计的潜力,并强调了推进体外和体内验证以确认这些候选物的治疗相关性并为基孔肯雅热的特异性治疗开发做出贡献的重要性。

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