Bioinformatic Analysis of SARS-CoV-2 S Protein

Citation

Elangovan, Pugalzhetha K. and Sia, Boon Zhan and Ng, Chong Han (2022) Bioinformatic Analysis of SARS-CoV-2 S Protein. Lecture Notes in Electrical Engineering, 835. pp. 425-434. ISSN 1876-1100

Full text not available from this repository.

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus is the causative agent of the COVID-19 pandemic possibly originated from an open market in Wuhan, China in December 2019. Multiple variants of SARS-CoV-2 virus have been reported from different regions and this may result in lower efficiency in immune response induced by vaccination. The SARS-CoV-2 spike protein (S protein) facilitates the viral entry into human host cells by binding to human angiotensin converting enzyme 2 (ACE2) receptor protein. A number of nonsynonymous mutations located at various domains of S protein have been reported. Specifically, five mutations which are V367F, G476S, D614G, Q675H and A706V have been identified at receptor binding domain (RBD) and S1-S2 linker region, respectively. The biological consequences of these mutations on the structure and function of the protein remain largely unknown. In this study, these five mutations of S protein are characterized using bioinformatics tools to predict the effect of its structure and function involved in the disease pathogenesis. The mutations involved in these two domains are analyzed with secondary structure prediction analysis, protein structure visualization analysis, protein structure stability analysis and pathogenicity prediction analysis. Our result shows that V367F mutations of S protein may affect the secondary structure while D614G and A706V may affect the protein stability. In addition, V367F and A706V may be deleterious to the structure of S protein whereas Q675H mutation may affect the structure of S protein.

Item Type: Article
Uncontrolled Keywords: SARS-CoV-2, COVID-19, S protein, Bioinformatics
Subjects: Q Science > QH Natural history > QH301 Biology
Divisions: Faculty of Information Science and Technology (FIST)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 09 Aug 2022 03:20
Last Modified: 09 Aug 2022 03:20
URII: http://shdl.mmu.edu.my/id/eprint/10183

Downloads

Downloads per month over past year

View ItemEdit (login required)