Impact of mutations in SARS-CoV-2 recombinant sub-variant XBB.1.16 on the binding affinity with human ACE2 receptor

IF 2.7 4区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS Journal of molecular graphics & modelling Pub Date : 2024-06-13 DOI:10.1016/j.jmgm.2024.108813
Syeda Sumayya Tariq , Komal Zia , Mohammad Nur-e-Alam , Dmitry Nerukh , Vladimir S. Farafonov , Zaheer Ul-Haq
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Abstract

Despite the waning threat of the COVID-19 pandemic, its detrimental impact on global health persists. Regardless of natural immunity or immunity obtained through vaccination, emerging variants of the virus continue to undergo mutations and propagate globally. The persistent mutations in SARS-CoV-2, along with the subsequent formation of recombinant sub-variants has become a challenge for researchers and health professionals, raising concerns about the efficacy of current vaccines. Gaining a better understanding of the biochemical interactions between the Spike Protein (RBD) of SARS-CoV-2 variants and the human ACE2 receptor can prove to be beneficial in designing and developing antiviral therapeutics that are equally effective against all strains and emerging variants. Our objective in this study was to investigate the interfacial binding pattern of the SARS-CoV-2 RBD-ACE2 complex of the Wild Type (WT), Omicron, and the Omicron recombinant sub-variant XBB.1.16. We aimed to examine the atomic level factors and observe how mutations influence the interaction between the virus and its host using Molecular Dynamics simulation, MM/GBSA energy calculations, and Principal Component Analysis. Our findings reveal a higher degree of structural deviation and flexibility in XBB.1.16 compared to WT and Omicron. PCA indicated a wider cluster and significant flexibility in the movements of XBB.1.16 which can also be observed in free energy landscapes, while the normal mode analysis revealed converging motions within the RBD-ACE2 complexes which can facilitate the interaction between them. A pattern of decreased binding affinity was observed in case of XBB.1.16 when compared to the WT and Omicron. These observed deviations in XBB.1.16 when compared to its parent lineage Omicron, and WT can be attributed to the mutations specific to it. Collectively, these results enhance our understanding of the impact of mutations on the interaction between this strain and the host, taking us one step closer to designing effective antiviral therapeutics against the continually mutating strains.

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SARS-CoV-2 重组亚变体 XBB.1.16 中的突变对与人类 ACE2 受体结合亲和力的影响
尽管 COVID-19 大流行的威胁正在减弱,但它对全球健康的有害影响依然存在。不管是自然免疫还是通过接种疫苗获得的免疫,新出现的病毒变种仍在继续发生变异,并在全球范围内传播。SARS-CoV-2 的持续变异以及随后形成的重组亚变种已成为研究人员和卫生专业人员面临的挑战,并引发了对现有疫苗有效性的担忧。更好地了解 SARS-CoV-2 变异株的尖峰蛋白(RBD)与人类 ACE2 受体之间的生化相互作用,将有助于设计和开发对所有毒株和新出现的变异株同样有效的抗病毒疗法。本研究的目的是研究野生型(WT)、Omicron 和 Omicron 重组亚变异体 XBB.1.16 的 SARS-CoV-2 RBD-ACE2 复合物的界面结合模式。我们的目的是利用分子动力学模拟、MM/GBSA 能量计算和主成分分析来研究原子层面的因素,并观察突变如何影响病毒与其宿主之间的相互作用。我们的研究结果表明,与 WT 和 Omicron 相比,XBB.1.16 的结构偏离度和灵活性更高。主成分分析表明,XBB.1.16 的运动具有更广泛的群集和显著的灵活性,这也可以在自由能谱中观察到,而正态模式分析则揭示了 RBD-ACE2 复合物内部的趋同运动,这可以促进它们之间的相互作用。与 WT 和 Omicron 相比,XBB.1.16 的结合亲和力下降。与母系 Omicron 和 WT 相比,在 XBB.1.16 中观察到的这些偏差可归因于其特有的突变。总之,这些结果加深了我们对突变对这种病毒株与宿主之间相互作用的影响的理解,使我们离设计出有效的抗病毒疗法来对付不断突变的病毒株更近了一步。
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来源期刊
Journal of molecular graphics & modelling
Journal of molecular graphics & modelling 生物-计算机:跨学科应用
CiteScore
5.50
自引率
6.90%
发文量
216
审稿时长
35 days
期刊介绍: The Journal of Molecular Graphics and Modelling is devoted to the publication of papers on the uses of computers in theoretical investigations of molecular structure, function, interaction, and design. The scope of the journal includes all aspects of molecular modeling and computational chemistry, including, for instance, the study of molecular shape and properties, molecular simulations, protein and polymer engineering, drug design, materials design, structure-activity and structure-property relationships, database mining, and compound library design. As a primary research journal, JMGM seeks to bring new knowledge to the attention of our readers. As such, submissions to the journal need to not only report results, but must draw conclusions and explore implications of the work presented. Authors are strongly encouraged to bear this in mind when preparing manuscripts. Routine applications of standard modelling approaches, providing only very limited new scientific insight, will not meet our criteria for publication. Reproducibility of reported calculations is an important issue. Wherever possible, we urge authors to enhance their papers with Supplementary Data, for example, in QSAR studies machine-readable versions of molecular datasets or in the development of new force-field parameters versions of the topology and force field parameter files. Routine applications of existing methods that do not lead to genuinely new insight will not be considered.
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