Coevolution based immunoinformatics approach considering variability of epitopes to combat different strains: A case study using spike protein of SARS-CoV-2.


Journal

Computers in biology and medicine
ISSN: 1879-0534
Titre abrégé: Comput Biol Med
Pays: United States
ID NLM: 1250250

Informations de publication

Date de publication:
09 2023
Historique:
received: 07 12 2022
revised: 03 06 2023
accepted: 01 07 2023
medline: 21 8 2023
pubmed: 9 7 2023
entrez: 9 7 2023
Statut: ppublish

Résumé

In the recent past several vaccines were developed to combat the COVID-19 disease. Unfortunately, the protective efficacy of the current vaccines has been reduced due to the high mutation rate in SARS-CoV-2. Here, we successfully implemented a coevolution based immunoinformatics approach to design an epitope-based peptide vaccine considering variability in spike protein of SARS-CoV-2. The spike glycoprotein was investigated for B- and T-cell epitope prediction. Identified T-cell epitopes were mapped on previously reported coevolving amino acids in the spike protein to introduce mutation. The non-mutated and mutated vaccine components were constructed by selecting epitopes showing overlapping with the predicted B-cell epitopes and highest antigenicity. Selected epitopes were linked with the help of a linker to construct a single vaccine component. Non-mutated and mutated vaccine component sequences were modelled and validated. The in-silico expression level of the vaccine constructs (non-mutated and mutated) in E. coli K12 shows promising results. The molecular docking analysis of vaccine components with toll-like receptor 5 (TLR5) demonstrated strong binding affinity. The time series calculations including root mean square deviation (RMSD), radius of gyration (RGYR), and energy of the system over 100 ns trajectory obtained from all atom molecular dynamics simulation showed stability of the system. The combined coevolutionary and immunoinformatics approach used in this study will certainly help to design an effective peptide vaccine that may work against different strains of SARS-CoV-2. Moreover, the strategy used in this study can be implemented on other pathogens.

Identifiants

pubmed: 37422941
pii: S0010-4825(23)00698-4
doi: 10.1016/j.compbiomed.2023.107233
pii:
doi:

Substances chimiques

COVID-19 Vaccines 0
spike protein, SARS-CoV-2 0
Spike Glycoprotein, Coronavirus 0
Viral Vaccines 0
Epitopes, T-Lymphocyte 0
Vaccines, Subunit 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

107233

Informations de copyright

Copyright © 2023 Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest All authors declare that they have no conflicts of interest in this paper. The authors also declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Saurav Kumar Mishra (SK)

Department of Bioinformatics, Central University of South Bihar, Gaya, Bihar, India.

Prerna Priya (P)

Department of Botany, Purnea Mahila College, Purnia, Bihar, India.

Gyan Prakash Rai (GP)

Department of Bioinformatics, Central University of South Bihar, Gaya, Bihar, India.

Rizwanul Haque (R)

Department of Biotechnology, Central University of South Bihar, Gaya, Bihar, India.

Asheesh Shanker (A)

Department of Bioinformatics, Central University of South Bihar, Gaya, Bihar, India. Electronic address: ashomics@gmail.com.

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Classifications MeSH