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

Muhammad Hanifa; Muhammad Salman; Muqaddas Fatima; Naila Mukhtar; Fahad N Almajhdi; Nasib Zaman; Muhammad Suleman; Syed Shujait Ali; Yasir Waheed; Abbas Khan

doi:10.3389/fcell.2022.940863

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

Front Cell Dev Biol. 2023 Jan 17:10:940863. doi: 10.3389/fcell.2022.940863. eCollection 2022.

Authors

Affiliations

¹ Centre for Biotechnology and Microbiology, University of Swat, Charbagh, Khyber Pakhtunkhwa, Pakistan.
² Rashid Latif Medical College, Lahore, Punjab, Pakistan.
³ King Edward Medical University, Lahore, Punjab, Pakistan.
⁴ Department of Botany, University of Okara, Punjab, Pakistan.
⁵ COVID-19 Virus Research Chair, Department of Botany and Microbiology, College of Science, King Saud University, Riyadh, Saudi Arabia.
⁶ Office of Research, Innovation and Commercialization, Shaheed Zulfiqar Ali Bhutto Medical University (SZABMU), Islamabad, Pakistan.
⁷ Gilbert and Rose-Marie Chagoury School of Medicine, Lebanese American University, Byblos, Lebanon.
⁸ Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.

Abstract

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.

Keywords: SARS-CoV-2; docking; genomes; simulation; spike protein; variants.