Open Access
Open access
volume 2020 pages 1-12

Design of a Multiepitope-Based Peptide Vaccine against the E Protein of Human COVID-19: An Immunoinformatics Approach

Miyssa I Abdelmageed 1
Abdelrahman H Abdelmoneim 2
Mujahed I Mustafa 3
Nafisa M Elfadol 4
Naseem S Murshed 5
Shaza W. Shantier 6
Abdelrafie M Makhawi 3
Publication typeJournal Article
Publication date2020-05-11
scimago Q2
wos Q3
SJR0.744
CiteScore7.9
Impact factor2.3
ISSN23146133, 23146141
PubMed ID:  32461973
General Biochemistry, Genetics and Molecular Biology
General Medicine
General Immunology and Microbiology
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.

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GOST Copy
Abdelmageed M. I. et al. Design of a Multiepitope-Based Peptide Vaccine against the E Protein of Human COVID-19: An Immunoinformatics Approach // BioMed Research International. 2020. Vol. 2020. pp. 1-12.
GOST all authors (up to 50) Copy
Abdelmageed M. I., Abdelmoneim A. H., Mustafa M. I., Elfadol N. M., Murshed N. S., Shantier S. W., Makhawi A. M. Design of a Multiepitope-Based Peptide Vaccine against the E Protein of Human COVID-19: An Immunoinformatics Approach // BioMed Research International. 2020. Vol. 2020. pp. 1-12.
RIS |
Cite this
RIS Copy
TY - JOUR
DO - 10.1155/2020/2683286
UR - https://doi.org/10.1155/2020/2683286
TI - Design of a Multiepitope-Based Peptide Vaccine against the E Protein of Human COVID-19: An Immunoinformatics Approach
T2 - BioMed Research International
AU - Abdelmageed, Miyssa I
AU - Abdelmoneim, Abdelrahman H
AU - Mustafa, Mujahed I
AU - Elfadol, Nafisa M
AU - Murshed, Naseem S
AU - Shantier, Shaza W.
AU - Makhawi, Abdelrafie M
PY - 2020
DA - 2020/05/11
PB - Hindawi Limited
SP - 1-12
VL - 2020
PMID - 32461973
SN - 2314-6133
SN - 2314-6141
ER -
BibTex
Cite this
BibTex (up to 50 authors) Copy
@article{2020_Abdelmageed,
author = {Miyssa I Abdelmageed and Abdelrahman H Abdelmoneim and Mujahed I Mustafa and Nafisa M Elfadol and Naseem S Murshed and Shaza W. Shantier and Abdelrafie M Makhawi},
title = {Design of a Multiepitope-Based Peptide Vaccine against the E Protein of Human COVID-19: An Immunoinformatics Approach},
journal = {BioMed Research International},
year = {2020},
volume = {2020},
publisher = {Hindawi Limited},
month = {may},
url = {https://doi.org/10.1155/2020/2683286},
pages = {1--12},
doi = {10.1155/2020/2683286}
}