Immunoinformatics mapping of potential epitopes in SARS-CoV-2 structural proteins.
PLoS One
; 16(11): e0258645, 2021.
Article
in English
| MEDLINE | ID: covidwho-1518355
ABSTRACT
All approved coronavirus disease 2019 (COVID-19) vaccines in current use are safe, effective, and reduce the risk of severe illness. Although data on the immunological presentation of patients with COVID-19 is limited, increasing experimental evidence supports the significant contribution of B and T cells towards the resolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Despite the availability of several COVID-19 vaccines with high efficacy, more effective vaccines are still needed to protect against the new variants of SARS-CoV-2. Employing a comprehensive immunoinformatic prediction algorithm and leveraging the genetic closeness with SARS-CoV, we have predicted potential immune epitopes in the structural proteins of SARS-CoV-2. The S and N proteins of SARS-CoV-2 and SARS-CoVs are main targets of antibody detection and have motivated us to design four multi-epitope vaccines which were based on our predicted B- and T-cell epitopes of SARS-CoV-2 structural proteins. The cardinal epitopes selected for the vaccine constructs are predicted to possess antigenic, non-allergenic, and cytokine-inducing properties. Additionally, some of the predicted epitopes have been experimentally validated in published papers. Furthermore, we used the C-ImmSim server to predict effective immune responses induced by the epitope-based vaccines. Taken together, the immune epitopes predicted in this study provide a platform for future experimental validations which may facilitate the development of effective vaccine candidates and epitope-based serological diagnostic assays.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Viral Structural Proteins
/
Epitope Mapping
/
Computational Biology
/
SARS-CoV-2
Type of study:
Diagnostic study
/
Prognostic study
Topics:
Vaccines
/
Variants
Limits:
Humans
Language:
English
Journal:
PLoS One
Journal subject:
Science
/
Medicine
Year:
2021
Document Type:
Article
Affiliation country:
Journal.pone.0258645
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