Mutational analysis of the spike protein of SARS-COV-2 isolates revealed atomistic features responsible for higher binding and infectivity

被引:1
作者
Hanifa, Muhammad [1 ]
Salman, Muhammad [2 ]
Fatima, Muqaddas [3 ]
Mukhtar, Naila [4 ]
Almajhdi, Fahad N. [5 ]
Zaman, Nasib [1 ]
Suleman, Muhammad [1 ]
Ali, Syed Shujait [1 ]
Waheed, Yasir [6 ,7 ]
Khan, Abbas [8 ]
机构
[1] Univ Swat, Ctr Biotechnol & Microbiol, Charbagh, Khyber Pakhtunk, Pakistan
[2] Rashid Latif Med Coll, Lahore, Punjab, Pakistan
[3] King Edward Med Univ, Lahore, Punjab, Pakistan
[4] Univ Okara, Dept Bot, Okara, Punjab, Pakistan
[5] King Saud Univ, Coll Sci, COVID 19 Virus Res Chair, Dept Bot & Microbiol, Riyadh, Saudi Arabia
[6] Shaheed Zulfiqar Ali Bhutto Med Univ SZABMU, Off Res Innovat & Commercializat, Islamabad, Pakistan
[7] Lebanese Amer Univ, Gilbert & Rose Marie Chagoury Sch Med, Byblos, Lebanon
[8] Shanghai Jiao Tong Univ, Sch Life Sci & Biotechnol, Dept Bioinformat & Biol Stat, Shanghai, Peoples R China
来源
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY | 2023年 / 10卷
关键词
SARS-CoV-2; variants; genomes; spike protein; docking; simulation; UCSF CHIMERA; VISUALIZATION; SOFTWARE; AFFINITY; SERVER; AMBER;
D O I
10.3389/fcell.2022.940863
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
Introduction: 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. Materials and Methods: 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. Results: 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. Conclusions: 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.
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页数:15
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