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针对奥司他韦耐药流感毒株神经氨酸酶基因H275Y突变的整合虚拟筛选和化合物生成

Integrated virtual screening and compound generation targeting H275Y mutation in the neuraminidase gene of oseltamivir-resistant influenza strains.

作者信息

Khan Wajihul Hasan, Khan Nida, Tembhre Manoj Kumar, Malik Zubbair, Ansari Mairaj Ahmad, Mishra Avinash

机构信息

Virology Unit, Department of Microbiology, All India Institute of Medical Sciences, New Delhi, Delhi, 110029, India.

Department of Chemical Engineering, Indian Institute of Technology, Hauz Khas, New Delhi, 110016, India.

出版信息

Mol Divers. 2025 Mar 14. doi: 10.1007/s11030-025-11163-0.

Abstract

Neuraminidase (NA) is an essential enzyme located at the outer layer of the influenza virus and plays a key role in the release of virions from infected cells. The rising incidence of global epidemics has made the urgent need for effective antiviral medications an urgent public health priority. Furthermore, the emergence of resistance caused by specific mutations in the influenza viral genome exacerbates the challenges of antiviral therapy. In view of this, this study aims to identify and analyse possible inhibitors of NA from different subtypes of influenza viruses. Initially, a thorough search was conducted in the Protein Data Bank (PDB) to gather structures of NA proteins that were attached with oseltamivir, a widely recognized inhibitor of NA. Here, 36 PDB entries were found with NA-oseltamivir complexes which were studied to evaluate the diversity and mutations present in various subtypes. Finally, N1(H1N1) protein was selected that demonstrated low IC50 value of oseltamivir with mutation H275Y. In addition, the study utilized BiMODAL generative model to generate 1000 novel molecules with comparable structures to oseltamivir. A QSAR model, based on machine learning (ML), was built utilizing the ChEMBL database to improve the selection process of candidate inhibitors. These inhibitors were subsequently analysed by molecular docking and further the best hits compounds (compound_375, compound_106 and compound_597) were appended to make a bigger molecule (compound_106-375, compound_106-597, and compound_375-597) to fit into the binding pocket of protein. Further, triplicate molecular dynamics simulations lasting 100 ns to assess their effectiveness and binding stability showed that compound_106-375 had the most stable binding with the protein. Key residues, including Asn146, Ala138, and Tyr155, form critical interactions with the ligand, contributing to its stability. The investigation was enhanced by employing principal component analysis (PCA), free energy landscape (FEL), and binding free energy calculations. The total binding free energy (G) of - 169.62 kcal/mol suggests that the contact between compound_106-375 and the mutant N1 (H1N1) protein is thermodynamically favourable. This approach allowed for a thorough comprehension of the binding interactions and possible effectiveness of the discovered inhibitors. Overall, these findings demonstrate that compound_106-375 exhibits favourable binding characteristics and stability. Further experimental validation is required to confirm its efficacy against the H275Y mutant neuraminidase protein and its potential to overcome influenza drug resistance. However, compound_106-375 is suggested as a promising candidate for further development as a therapeutic agent against the mutant N1 (H1N1) protein. This finding will assist in drug development and to overcome the challenges associated with drug resistance in influenza strains.

摘要

神经氨酸酶(NA)是一种位于流感病毒外层的必需酶,在病毒粒子从受感染细胞中释放的过程中起关键作用。全球流行病发病率的上升使得迫切需要有效的抗病毒药物成为紧迫的公共卫生优先事项。此外,流感病毒基因组中特定突变导致的耐药性出现加剧了抗病毒治疗的挑战。鉴于此,本研究旨在鉴定和分析来自不同亚型流感病毒的NA可能的抑制剂。最初,在蛋白质数据库(PDB)中进行了全面搜索,以收集与奥司他韦(一种广泛认可的NA抑制剂)结合的NA蛋白结构。在此,发现了36个含有NA - 奥司他韦复合物的PDB条目,对其进行研究以评估各种亚型中存在的多样性和突变。最后,选择了N1(H1N1)蛋白,其显示出奥司他韦对突变H275Y的低IC50值。此外,该研究利用双模态生成模型生成了1000个与奥司他韦结构相似的新分子。利用ChEMBL数据库建立了一个基于机器学习(ML)的QSAR模型,以改进候选抑制剂的筛选过程。随后通过分子对接对这些抑制剂进行分析,并进一步将最佳命中化合物(化合物_375、化合物_106和化合物_597)连接成一个更大的分子(化合物_106 - 375、化合物_106 - 597和化合物_375 - 597),以使其适合蛋白质的结合口袋。此外,进行了三次持续100纳秒的分子动力学模拟,以评估它们的有效性和结合稳定性,结果表明化合物_106 - 375与蛋白质的结合最稳定。关键残基,包括Asn146、Ala138和Tyr155,与配体形成关键相互作用,有助于其稳定性。通过采用主成分分析(PCA)、自由能景观(FEL)和结合自由能计算,增强了研究。 - 169.62千卡/摩尔的总结合自由能(G)表明化合物_106 - 375与突变型N1(H1N1)蛋白之间的接触在热力学上是有利的。这种方法有助于全面理解所发现抑制剂的结合相互作用和可能的有效性。总体而言,这些发现表明化合物_106 - 375具有良好的结合特性和稳定性。需要进一步的实验验证来确认其对H275Y突变神经氨酸酶蛋白的疗效及其克服流感耐药性的潜力。然而,化合物_106 - 375被认为是作为针对突变型N1(H1N1)蛋白的治疗剂进行进一步开发的有前途的候选物。这一发现将有助于药物开发并克服与流感毒株耐药性相关的挑战。

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