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

IF 3.9 2区 化学 Q2 CHEMISTRY, APPLIED Molecular Diversity Pub Date : 2025-03-14 DOI:10.1007/s11030-025-11163-0
Wajihul Hasan Khan, Nida Khan, Manoj Kumar Tembhre, Zubbair Malik, Mairaj Ahmad Ansari, Avinash Mishra
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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 (GTOTAL) 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.

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针对耐奥司他韦流感病毒株神经氨酸酶基因 H275Y 突变的综合虚拟筛选和化合物生成。
神经氨酸酶(NA)是位于流感病毒外层的一种重要酶,在受感染细胞释放病毒的过程中发挥着关键作用。随着全球流行病发病率的不断上升,对有效抗病毒药物的迫切需求已成为公共卫生领域的当务之急。此外,由流感病毒基因组中的特定突变引起的抗药性的出现加剧了抗病毒治疗的挑战。有鉴于此,本研究旨在从不同亚型的流感病毒中找出并分析可能的 NA 抑制剂。首先,我们在蛋白质数据库(PDB)中进行了全面搜索,以收集与奥司他韦--一种公认的 NA 抑制剂--相连的 NA 蛋白结构。在此发现了 36 个含有 NA 与奥司他韦复合物的 PDB 条目,并对其进行了研究,以评估不同亚型中存在的多样性和突变。最后,研究人员选择了 N1(H1N1) 蛋白,该蛋白在发生 H275Y 突变后,奥司他韦的 IC50 值较低。此外,该研究还利用 BiMODAL 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。随后对这些抑制剂进行了分子对接分析,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)添加到更大的分子(化合物_106-375、化合物_106-597 和化合物_375-597)中,以适合蛋白质的结合口袋。此外,通过持续 100 毫微秒的三重分子动力学模拟来评估它们的有效性和结合稳定性,结果表明化合物_106-375 与蛋白质的结合最为稳定。包括 Asn146、Ala138 和 Tyr155 在内的关键残基与配体形成了关键的相互作用,从而提高了配体的稳定性。采用主成分分析(PCA)、自由能景观(FEL)和结合自由能计算加强了研究。总结合自由能(GTOTAL)为- 169.62 kcal/mol,表明化合物_106-375 与突变 N1(H1N1)蛋白之间的接触在热力学上是有利的。通过这种方法可以全面了解发现的抑制剂的结合相互作用和可能的有效性。总之,这些发现表明化合物_106-375 具有良好的结合特性和稳定性。要确认其对 H275Y 突变体神经氨酸酶蛋白的疗效及其克服流感耐药性的潜力,还需要进一步的实验验证。不过,化合物_106-375 被认为是一种有希望进一步开发的候选药物,可作为针对突变 N1(H1N1)蛋白的治疗药物。这一发现将有助于药物开发和克服与流感病毒株耐药性相关的挑战。
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来源期刊
Molecular Diversity
Molecular Diversity 化学-化学综合
CiteScore
7.30
自引率
7.90%
发文量
219
审稿时长
2.7 months
期刊介绍: Molecular Diversity is a new publication forum for the rapid publication of refereed papers dedicated to describing the development, application and theory of molecular diversity and combinatorial chemistry in basic and applied research and drug discovery. The journal publishes both short and full papers, perspectives, news and reviews dealing with all aspects of the generation of molecular diversity, application of diversity for screening against alternative targets of all types (biological, biophysical, technological), analysis of results obtained and their application in various scientific disciplines/approaches including: combinatorial chemistry and parallel synthesis; small molecule libraries; microwave synthesis; flow synthesis; fluorous synthesis; diversity oriented synthesis (DOS); nanoreactors; click chemistry; multiplex technologies; fragment- and ligand-based design; structure/function/SAR; computational chemistry and molecular design; chemoinformatics; screening techniques and screening interfaces; analytical and purification methods; robotics, automation and miniaturization; targeted libraries; display libraries; peptides and peptoids; proteins; oligonucleotides; carbohydrates; natural diversity; new methods of library formulation and deconvolution; directed evolution, origin of life and recombination; search techniques, landscapes, random chemistry and more;
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