Immunoinformatics-guided design of an epitope-based vaccine against severe acute respiratory syndrome coronavirus 2 spike glycoprotein.
Comput Biol Med
; 124: 103967, 2020 09.
Article
in English
| MEDLINE | ID: covidwho-709480
ABSTRACT
AIMS:
With a large number of fatalities, coronavirus disease-2019 (COVID-19) has greatly affected human health worldwide. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus that causes COVID-19. The World Health Organization has declared a global pandemic of this contagious disease. Researchers across the world are collaborating in a quest for remedies to combat this deadly virus. It has recently been demonstrated that the spike glycoprotein (SGP) of SARS-CoV-2 is the mediator by which the virus enters host cells. MAINMETHODS:
Our group comprehensibly analyzed the SGP of SARS-CoV-2 through multiple sequence analysis and a phylogenetic analysis. We predicted the strongest immunogenic epitopes of the SGP for both B cells and T cells. KEYFINDINGS:
We focused on predicting peptides that would bind major histocompatibility complex class I. Two optimal epitopes were identified, WTAGAAAYY and GAAAYYVGY. They interact with the HLA-B*1501 allele, which was further validated by molecular docking simulation. This study also found that the selected epitopes are able to be recognized in a large percentage of the world's population. Furthermore, we predicted CD4+ T-cell epitopes and B-cell epitopes.SIGNIFICANCE:
Our study provides a strong basis for designing vaccine candidates against SARS-CoV-2. However, laboratory work is required to validate our theoretical results, which would lay the foundation for the appropriate vaccine manufacturing and testing processes.Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Pneumonia, Viral
/
Viral Vaccines
/
Coronavirus Infections
/
Pandemics
/
Spike Glycoprotein, Coronavirus
/
Betacoronavirus
Type of study:
Observational study
/
Prognostic study
Topics:
Vaccines
Limits:
Humans
Language:
English
Journal:
Comput Biol Med
Year:
2020
Document Type:
Article
Affiliation country:
J.compbiomed.2020.103967
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