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用于发现抗尼帕病毒药物的综合计算生物物理学方法。

Integrated computational biophysics approach for drug discovery against Nipah virus.

作者信息

Ropón-Palacios Georcki, Silva Jhon Pérez, Gervacio-Villarreal Edinson Alfonzo, Galarza Jean Pierre Ramos, Zuta Manuel Chenet, Otazu Kewin, Del Aguila Ivonne Navarro, Wong Henry Delgado, Amay Frida Sosa, Camps Ihosvany

机构信息

Laboratório de Modelagem Computacional - LaModel, Instituto de Ciências Exatas - ICEx, Universidade Federal de Alfenas UNIFAL-MG, 37133-840, Alfenas, Minas Gerais, Brazil.

Universidad Nacional Tecnológica de Lima Sur UNTELS, Peru.

出版信息

Biochem Biophys Res Commun. 2025 Jan;745:151140. doi: 10.1016/j.bbrc.2024.151140. Epub 2024 Dec 21.

DOI:10.1016/j.bbrc.2024.151140
PMID:39729673
Abstract

The Nipah virus (NiV) poses a pressing global threat to public health due to its high mortality rate, multiple modes of transmission, and lack of effective treatments. NiV glycoprotein G (NiV-G) emerges as a promising target for the discovery of NiV drugs because of its essential role in viral entry and membrane fusion. Therefore, in this study, we applied an integrated computational and biophysics approach to identify potential inhibitors of NiV-G within a curated dataset of Peruvian phytochemicals. The virtual screening results indicated that these compounds could represent a natural source of potential NiV-G inhibitors with ΔG values ranging from -8 to -11 kcal/mol. Among them, procyanidin B2, B3, B7, and C1 exhibited the highest binding affinities and formed the most molecular interactions with NiV-G. Molecular dynamics simulations revealed the induced-fit mechanism of NiV-G pocket interaction with these procyanidins, primarily driven by its hydrophobic nature. Non-equilibrium free energy calculations were used to determine binding affinities, highlighting Procyanidin B3 and B2 as the ligands with the most substantial interactions. In general, this work underscores the potential of Peruvian phytochemicals, particularly procyanidins B2, B3, B7, and C1, as lead compounds for developing anti-NiV drugs through an integrated computational biophysics approach.

摘要

尼帕病毒(NiV)因其高死亡率、多种传播方式以及缺乏有效治疗方法,对全球公共卫生构成了紧迫威胁。由于其在病毒进入和膜融合中的关键作用,尼帕病毒糖蛋白G(NiV-G)成为发现尼帕病毒药物的一个有前景的靶点。因此,在本研究中,我们应用了一种综合计算和生物物理学方法,在一个精心整理的秘鲁植物化学物质数据集中识别NiV-G的潜在抑制剂。虚拟筛选结果表明,这些化合物可能是潜在的NiV-G抑制剂的天然来源,其ΔG值范围为-8至-11千卡/摩尔。其中,原花青素B2、B3、B7和C1表现出最高的结合亲和力,并与NiV-G形成了最多的分子相互作用。分子动力学模拟揭示了NiV-G口袋与这些原花青素相互作用的诱导契合机制,主要由其疏水性驱动。非平衡自由能计算用于确定结合亲和力,突出了原花青素B3和B2作为具有最显著相互作用的配体。总体而言,这项工作强调了秘鲁植物化学物质,特别是原花青素B2、B3、B7和C1,作为通过综合计算生物物理学方法开发抗NiV药物的先导化合物的潜力。

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