Whole proteome screening and identification of potential epitopes of SARS-CoV-2 for vaccine design-an immunoinformatic, molecular docking and molecular dynamics simulation accelerated robust strategy.
J Biomol Struct Dyn
; 40(14): 6477-6502, 2022 09.
Article
in English
| MEDLINE | ID: covidwho-1081511
ABSTRACT
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the most cryptic pandemic outbreak of the 21st century, has gripped more than 1.8 million people to death and infected almost eighty six million. As it is a new variant of SARS, there is no approved drug or vaccine available against this virus. This study aims to predict some promising cytotoxic T lymphocyte epitopes in the SARS-CoV-2 proteome utilizing immunoinformatic approaches. Firstly, we identified 21 epitopes from 7 different proteins of SARS-CoV-2 inducing immune response and checked for allergenicity and conservancy. Based on these factors, we selected the top three epitopes, namely KAYNVTQAF, ATSRTLSYY, and LTALRLCAY showing functional interactions with the maximum number of MHC alleles and no allergenicity. Secondly, the 3D model of selected epitopes and HLA-A*2902 were built and Molecular Docking simulation was performed. Most interestingly, the best two epitopes predicted by docking are part of two different structural proteins of SARS-CoV-2, namely Membrane Glycoprotein (ATSRTLSYY) and Nucleocapsid Phosphoprotein (KAYNVTQAF), which are generally target of choice for vaccine designing. Upon Molecular Docking, interactions between selected epitopes and HLA-A*2902 were further validated by 50 ns Molecular Dynamics (MD) simulation. Analysis of RMSD, Rg, SASA, number of hydrogen bonds, RMSF, MM-PBSA, PCA, and DCCM from MD suggested that ATSRTLSYY is the most stable and promising epitope than KAYNVTQAF epitope. Moreover, we also identified B-cell epitopes for each of the antigenic proteins of SARS CoV-2. Findings of our work will be a good resource for wet lab experiments and will lessen the timeline for vaccine construction.Communicated by Ramaswamy H. Sarma.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Viral Vaccines
/
COVID-19
Type of study:
Prognostic study
Topics:
Vaccines
/
Variants
Limits:
Humans
Language:
English
Journal:
J Biomol Struct Dyn
Year:
2022
Document Type:
Article
Affiliation country:
07391102.2021.1886171
Similar
MEDLINE
...
LILACS
LIS