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Biomed Res Int ; 2020: 2683286, 2020.
Article in English | MEDLINE | ID: covidwho-400795

ABSTRACT

BACKGROUND: A new endemic disease has spread across Wuhan City, China, in December 2019. Within few weeks, the World Health Organization (WHO) announced a novel coronavirus designated as coronavirus disease 2019 (COVID-19). In late January 2020, WHO declared the outbreak of a "public-health emergency of international concern" due to the rapid and increasing spread of the disease worldwide. Currently, there is no vaccine or approved treatment for this emerging infection; thus, the objective of this study is to design a multiepitope peptide vaccine against COVID-19 using an immunoinformatics approach. METHOD: Several techniques facilitating the combination of the immunoinformatics approach and comparative genomic approach were used in order to determine the potential peptides for designing the T-cell epitope-based peptide vaccine using the envelope protein of 2019-nCoV as a target. RESULTS: Extensive mutations, insertion, and deletion were discovered with comparative sequencing in the COVID-19 strain. Additionally, ten peptides binding to MHC class I and MHC class II were found to be promising candidates for vaccine design with adequate world population coverage of 88.5% and 99.99%, respectively. CONCLUSION: The T-cell epitope-based peptide vaccine was designed for COVID-19 using the envelope protein as an immunogenic target. Nevertheless, the proposed vaccine rapidly needs to be validated clinically in order to ensure its safety and immunogenic profile to help stop this epidemic before it leads to devastating global outbreaks.


Subject(s)
Betacoronavirus/immunology , Computational Biology/methods , Coronavirus Infections/immunology , Epitopes/immunology , Pneumonia, Viral/immunology , Vaccines, Subunit/immunology , Viral Proteins/immunology , Viral Vaccines/immunology , Amino Acid Sequence , COVID-19 , COVID-19 Vaccines , Coronavirus Infections/prevention & control , Epitopes/chemistry , Epitopes, T-Lymphocyte/immunology , Evolution, Molecular , HLA Antigens/immunology , Humans , Models, Molecular , Pandemics , SARS-CoV-2 , Software , Viral Proteins/chemistry
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