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一种将坎格雷洛重新用作尼帕病毒潜在抑制剂的深度学习和分子建模方法。

A deep learning and molecular modeling approach to repurposing Cangrelor as a potential inhibitor of Nipah virus.

作者信息

John Levin, Dcunha Leona, Ahmed Mukhtar, Thomas Sonet Daniel, Raju Rajesh, Jayanandan Abhithaj

机构信息

Centre for Integrative Omics Data Science, Yenepoya (Deemed to be University), Mangalore, 575018, Karnataka, India.

Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, Scotland, EH16 4UU.

出版信息

Sci Rep. 2025 May 12;15(1):16440. doi: 10.1038/s41598-025-00024-3.

DOI:10.1038/s41598-025-00024-3
PMID:40355437
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12069662/
Abstract

Deforestation, urbanization, and climate change have significantly increased the risk of zoonotic diseases. Nipah virus (NiV) of Paramyxoviridae family and Henipavirus genus is transmitted by Pteropus bats. Climate-induced changes in bat migration patterns and food availability enhances the virus's adaptability, in turn increasing the potential for transmission and outbreak risk. NiV infection has high human fatality rate. With no antiviral drugs or vaccines available, exploring the complex machinery involved in viral RNA synthesis presents a promising target for therapy. Drug repurposing provides a fast-track approach by identifying existing drugs with potential to target NiV RNA-dependent RNA polymerase (L), bypassing the time-consuming process of developing novel compounds. To facilitate this, we developed an attention-based deep learning model that utilizes pharmacophore properties of the active sites and their binding efficacy with NiV L protein. Around 500 FDA-approved drugs were filtered and assessed for their ability to bind NiV L protein. Compared to the control Remdesivir, we identified Cangrelor, an antiplatelet drug for cardiovascular diseases, with stronger binding affinity to NiV L (glide score of -12.30 kcal/mol). Molecular dynamics simulations further revealed stable binding (RMSD of 3.54 Å) and a post-MD binding energy of -181.84 kcal/mol. The strong binding of Cangrelor is illustrated through trajectory analysis, principal component analysis, and solvent accessible surface area, further confirming the stable interaction with the active site of NiV RdRp. Cangrelor can interact with NiV L protein and may potentially interfere with its replication. These findings suggest that Cangrelor will be a potential drug candidate that can effectively interact with the NiV L protein and potentially disrupt the viral replication. Further in vivo studies are warranted to explore its potential as a repurposable antiviral drug.

摘要

森林砍伐、城市化和气候变化显著增加了人畜共患病的风险。副粘病毒科亨尼帕病毒属的尼帕病毒(NiV)通过狐蝠传播。气候引起的蝙蝠迁徙模式和食物供应变化增强了病毒的适应性,进而增加了传播可能性和爆发风险。NiV感染导致的人类死亡率很高。由于没有可用的抗病毒药物或疫苗,探索病毒RNA合成所涉及的复杂机制是一个有前景的治疗靶点。药物再利用通过识别具有靶向NiV RNA依赖性RNA聚合酶(L)潜力的现有药物,提供了一条快速途径,绕过了开发新化合物的耗时过程。为便于开展此项研究,我们开发了一种基于注意力的深度学习模型,该模型利用活性位点的药效团特性及其与NiV L蛋白的结合效力。对约500种美国食品药品监督管理局(FDA)批准的药物进行筛选,并评估它们与NiV L蛋白的结合能力。与对照药物瑞德西韦相比,我们发现一种用于心血管疾病的抗血小板药物坎格雷洛与NiV L的结合亲和力更强(滑行评分-12.30千卡/摩尔)。分子动力学模拟进一步揭示了稳定结合(均方根偏差为3.54埃)以及分子动力学模拟后的结合能为-181.84千卡/摩尔。通过轨迹分析、主成分分析和溶剂可及表面积说明了坎格雷洛的强结合,进一步证实了其与NiV RdRp活性位点的稳定相互作用。坎格雷洛可与NiV L蛋白相互作用,并可能干扰其复制。这些发现表明,坎格雷洛将是一种潜在的药物候选物,能够有效与NiV L蛋白相互作用并可能破坏病毒复制。有必要进一步开展体内研究,以探索其作为可再利用抗病毒药物的潜力。

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