In silico polyepitope vaccine design against SARS-COV-۲ infection

Backgrounds: The COVID-۱۹ pandemic caused by the SARS-COV-۲ virus has unexpectedlyaffected global health and it is accelerated mortality rates since SARS-COV-۲ outbreak inDecember ۲۰۱۹ in Wuhan, China. In this pandemic situation, an immunoinformatics approachcould be a fast and reliable option for quicker vaccine development. This study aimed to predictthe protective epitopes with In silico tools for vaccine development against SARS-COV-۲ virus.Materials and Methods: The liner B-cell epitopes, cytotoxic T lymphocytes (CTL) and helper Tlymphocytes (HTL) epitopes from Membrane, Nucleoprotein, Spike, Envelope, non-structuralprotein ۱۳ and papain-like protease of SARS-COV-۲ were predicted. The epitopes wereanalyzed and selected for their immunogenicity, antigenicity scores, allergenicity and toxicitycorrespondence to their ability to trigger immune response. After molecular docking, the vaccinecandidate was constructed by fusing best epitopes by linkers.Results: The constructed vaccine sequence was found to be a good vaccine candidate withproper stability and antigenicity, non- allergenicity and non-toxicity to human body. Moleculardocking showed a stable and high binding affinity of epitopes from M, N, S, E, nsp۱۳ and PLproproteins with human pathogenic toll-like receptors-۳ (TLR۳).Conclusion: Altogether, our results indicated that the designed vaccine candidate not onlyproved effective in various computer-based immune response analysis but also showed goodpopulation coverage. So, the construct may be considered for clinical validation to fight againstthis global threat, Covid-۱۹.

کلیدواژه ها:

In silico ، Epitope prediction ، SARS-Cov-۲ ، Vaccine design