Hanifa Muhammad, Salman Muhammad, Fatima Muqaddas, Mukhtar Naila, Almajhdi Fahad N, Zaman Nasib, Suleman Muhammad, Ali Syed Shujait, Waheed Yasir, Khan Abbas
Centre for Biotechnology and Microbiology, University of Swat, Charbagh, Khyber Pakhtunkhwa, Pakistan.
Rashid Latif Medical College, Lahore, Punjab, Pakistan.
Front Cell Dev Biol. 2023 Jan 17;10:940863. doi: 10.3389/fcell.2022.940863. eCollection 2022.
The perpetual appearance of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2), and its new variants devastated the public health and social fabric around the world. Understanding the genomic patterns and connecting them to phenotypic attributes is of great interest to devise a treatment strategy to control this pandemic. In this regard, computational methods to understand the evolution, dynamics and mutational spectrum of SARS-CoV-2 and its new variants are significantly important. Thus, herein, we used computational methods to screen the genomes of SARS-CoV-2 isolated from Pakistan and connect them to the phenotypic attributes of spike protein; we used stability-function correlation methods, protein-protein docking, and molecular dynamics simulation. Using the Global initiative on sharing all influenza data (GISAID) a total of 21 unique mutations were identified, among which five were reported as stabilizing while 16 were destabilizing revealed through mCSM, DynaMut 2.0, and I-Mutant servers. Protein-protein docking with Angiotensin-converting enzyme 2 (ACE2) and monoclonal antibody (4A8) revealed that mutation G446V in the receptor-binding domain; R102S and G181V in the N-terminal domain (NTD) significantly affected the binding and thus increased the infectivity. The interaction pattern also revealed significant variations in the hydrogen bonding, salt bridges and non-bonded contact networks. The structural-dynamic features of these mutations revealed the global dynamic trend and the finding energy calculation further established that the G446V mutation increases the binding affinity towards ACE2 while R102S and G181V help in evading the host immune response. The other mutations reported supplement these processes indirectly. The binding free energy results revealed that wild type-RBD has a TBE of -60.55 kcal/mol while G446V-RBD reported a TBE of -73.49 kcal/mol. On the other hand, wild type-NTD reported -67.77 kcal/mol of TBE, R102S-NTD reported -51.25 kcal/mol of TBE while G181V-NTD reported a TBE of -63.68 kcal/mol. In conclusion, the current findings revealed basis for higher infectivity and immune evasion associated with the aforementioned mutations and structure-based drug discovery against such variants.
严重急性呼吸综合征冠状病毒2(SARS-CoV-2)及其新变种的不断出现,给全球公共卫生和社会结构带来了巨大破坏。了解基因组模式并将其与表型特征联系起来,对于制定控制这一疫情的治疗策略具有重要意义。在这方面,利用计算方法来理解SARS-CoV-2及其新变种的进化、动态和突变谱具有至关重要的意义。因此,在本文中,我们使用计算方法筛选了从巴基斯坦分离出的SARS-CoV-2基因组,并将其与刺突蛋白的表型特征联系起来;我们使用了稳定性-功能相关性方法、蛋白质-蛋白质对接和分子动力学模拟。利用全球共享所有流感数据倡议(GISAID)共鉴定出21个独特突变,其中通过mCSM、DynaMut 2.0和I-Mutant服务器发现5个突变具有稳定作用,16个具有不稳定作用。与血管紧张素转换酶2(ACE2)和单克隆抗体(4A8)的蛋白质-蛋白质对接显示,受体结合域中的G446V突变;N端结构域(NTD)中的R102S和G181V突变显著影响结合,从而增加了感染性。相互作用模式还揭示了氢键、盐桥和非键接触网络的显著变化。这些突变的结构动力学特征揭示了整体动态趋势,结合能计算进一步证实,G446V突变增加了对ACE2的结合亲和力,而R102S和G181V有助于逃避宿主免疫反应。报告的其他突变间接补充了这些过程。结合自由能结果显示,野生型-RBD的结合自由能为-60.55千卡/摩尔,而G446V-RBD的结合自由能为-73.49千卡/摩尔。另一方面,野生型-NTD的结合自由能为-67.77千卡/摩尔,R102S-NTD的结合自由能为-51.25千卡/摩尔,而G181V-NTD的结合自由能为-63.68千卡/摩尔。总之,当前研究结果揭示了与上述突变相关的更高感染性和免疫逃逸的基础,以及针对此类变种的基于结构的药物发现。