Cargando…
Immunoinformatics prediction of overlapping CD8(+) T-cell, IFN-γ and IL-4 inducer CD4(+) T-cell and linear B-cell epitopes based vaccines against COVID-19 (SARS-CoV-2)
At the beginning of the year 2020, the world was struck with a global pandemic virus referred to as SARS-CoV-2 (COVID-19) which has left hundreds of thousands of people dead. To control this virus, vaccine design becomes imperative. In this study, potential epitopes-based vaccine candidates were exp...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7831457/ https://www.ncbi.nlm.nih.gov/pubmed/33478794 http://dx.doi.org/10.1016/j.vaccine.2021.01.003 |
_version_ | 1783641626274430976 |
---|---|
author | Fatoba, Abiodun J. Maharaj, Leah Adeleke, Victoria T. Okpeku, Moses Adeniyi, Adebayo A Adeleke, Matthew A. |
author_facet | Fatoba, Abiodun J. Maharaj, Leah Adeleke, Victoria T. Okpeku, Moses Adeniyi, Adebayo A Adeleke, Matthew A. |
author_sort | Fatoba, Abiodun J. |
collection | PubMed |
description | At the beginning of the year 2020, the world was struck with a global pandemic virus referred to as SARS-CoV-2 (COVID-19) which has left hundreds of thousands of people dead. To control this virus, vaccine design becomes imperative. In this study, potential epitopes-based vaccine candidates were explored. Six hundred (6 0 0) genomes of SARS-CoV-2 were retrieved from the viPR database to generate CD8(+) T-cell, CD4+ T-cell and linear B-cell epitopes which were screened for antigenicity, immunogenicity and non-allergenicity. The results of this study provide 19 promising candidate CD8(+) T-cell epitopes that strongly overlap with 8 promising B-cells epitopes. Another 19 CD4(+) T-cell epitopes were also identified that can induce IFN-γ and IL-4 cytokines. The most conserved MHC-I and MHC-II for both CD8(+) and CD4(+) T-cell epitopes are HLA-A*02:06 and HLA-DRB1*01:01 respectively. These epitopes also bound to Toll-like receptor 3 (TLR3). The population coverage of the conserved Major Histocompatibility Complex Human Leukocyte Antigen (HLA) for both CD8(+) T-cell and CD4(+) T-cell ranged from 65.6% to 100%. The detailed analysis of the potential epitope-based vaccine and their mapping to the complete COVID-19 genome reveals that they are predominantly found in the location of the surface (S) and membrane (M) glycoproteins suggesting the potential involvement of these structural proteins in the immunogenic response and antigenicity of the virus. Since the majority of the potential epitopes are located on M protein, the design of multi-epitope vaccine with the structural protein is highly promising though the whole M protein could also serve as a viable epitope for the development of an attenuated vaccine. Our findings provide a baseline for the experimental design of a suitable vaccine against SARS-CoV-2. |
format | Online Article Text |
id | pubmed-7831457 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-78314572021-01-26 Immunoinformatics prediction of overlapping CD8(+) T-cell, IFN-γ and IL-4 inducer CD4(+) T-cell and linear B-cell epitopes based vaccines against COVID-19 (SARS-CoV-2) Fatoba, Abiodun J. Maharaj, Leah Adeleke, Victoria T. Okpeku, Moses Adeniyi, Adebayo A Adeleke, Matthew A. Vaccine Article At the beginning of the year 2020, the world was struck with a global pandemic virus referred to as SARS-CoV-2 (COVID-19) which has left hundreds of thousands of people dead. To control this virus, vaccine design becomes imperative. In this study, potential epitopes-based vaccine candidates were explored. Six hundred (6 0 0) genomes of SARS-CoV-2 were retrieved from the viPR database to generate CD8(+) T-cell, CD4+ T-cell and linear B-cell epitopes which were screened for antigenicity, immunogenicity and non-allergenicity. The results of this study provide 19 promising candidate CD8(+) T-cell epitopes that strongly overlap with 8 promising B-cells epitopes. Another 19 CD4(+) T-cell epitopes were also identified that can induce IFN-γ and IL-4 cytokines. The most conserved MHC-I and MHC-II for both CD8(+) and CD4(+) T-cell epitopes are HLA-A*02:06 and HLA-DRB1*01:01 respectively. These epitopes also bound to Toll-like receptor 3 (TLR3). The population coverage of the conserved Major Histocompatibility Complex Human Leukocyte Antigen (HLA) for both CD8(+) T-cell and CD4(+) T-cell ranged from 65.6% to 100%. The detailed analysis of the potential epitope-based vaccine and their mapping to the complete COVID-19 genome reveals that they are predominantly found in the location of the surface (S) and membrane (M) glycoproteins suggesting the potential involvement of these structural proteins in the immunogenic response and antigenicity of the virus. Since the majority of the potential epitopes are located on M protein, the design of multi-epitope vaccine with the structural protein is highly promising though the whole M protein could also serve as a viable epitope for the development of an attenuated vaccine. Our findings provide a baseline for the experimental design of a suitable vaccine against SARS-CoV-2. Elsevier Ltd. 2021-02-12 2021-01-18 /pmc/articles/PMC7831457/ /pubmed/33478794 http://dx.doi.org/10.1016/j.vaccine.2021.01.003 Text en © 2021 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Fatoba, Abiodun J. Maharaj, Leah Adeleke, Victoria T. Okpeku, Moses Adeniyi, Adebayo A Adeleke, Matthew A. Immunoinformatics prediction of overlapping CD8(+) T-cell, IFN-γ and IL-4 inducer CD4(+) T-cell and linear B-cell epitopes based vaccines against COVID-19 (SARS-CoV-2) |
title | Immunoinformatics prediction of overlapping CD8(+) T-cell, IFN-γ and IL-4 inducer CD4(+) T-cell and linear B-cell epitopes based vaccines against COVID-19 (SARS-CoV-2) |
title_full | Immunoinformatics prediction of overlapping CD8(+) T-cell, IFN-γ and IL-4 inducer CD4(+) T-cell and linear B-cell epitopes based vaccines against COVID-19 (SARS-CoV-2) |
title_fullStr | Immunoinformatics prediction of overlapping CD8(+) T-cell, IFN-γ and IL-4 inducer CD4(+) T-cell and linear B-cell epitopes based vaccines against COVID-19 (SARS-CoV-2) |
title_full_unstemmed | Immunoinformatics prediction of overlapping CD8(+) T-cell, IFN-γ and IL-4 inducer CD4(+) T-cell and linear B-cell epitopes based vaccines against COVID-19 (SARS-CoV-2) |
title_short | Immunoinformatics prediction of overlapping CD8(+) T-cell, IFN-γ and IL-4 inducer CD4(+) T-cell and linear B-cell epitopes based vaccines against COVID-19 (SARS-CoV-2) |
title_sort | immunoinformatics prediction of overlapping cd8(+) t-cell, ifn-γ and il-4 inducer cd4(+) t-cell and linear b-cell epitopes based vaccines against covid-19 (sars-cov-2) |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7831457/ https://www.ncbi.nlm.nih.gov/pubmed/33478794 http://dx.doi.org/10.1016/j.vaccine.2021.01.003 |
work_keys_str_mv | AT fatobaabiodunj immunoinformaticspredictionofoverlappingcd8tcellifngandil4inducercd4tcellandlinearbcellepitopesbasedvaccinesagainstcovid19sarscov2 AT maharajleah immunoinformaticspredictionofoverlappingcd8tcellifngandil4inducercd4tcellandlinearbcellepitopesbasedvaccinesagainstcovid19sarscov2 AT adelekevictoriat immunoinformaticspredictionofoverlappingcd8tcellifngandil4inducercd4tcellandlinearbcellepitopesbasedvaccinesagainstcovid19sarscov2 AT okpekumoses immunoinformaticspredictionofoverlappingcd8tcellifngandil4inducercd4tcellandlinearbcellepitopesbasedvaccinesagainstcovid19sarscov2 AT adeniyiadebayoa immunoinformaticspredictionofoverlappingcd8tcellifngandil4inducercd4tcellandlinearbcellepitopesbasedvaccinesagainstcovid19sarscov2 AT adelekematthewa immunoinformaticspredictionofoverlappingcd8tcellifngandil4inducercd4tcellandlinearbcellepitopesbasedvaccinesagainstcovid19sarscov2 |