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Computer-Based Immunoinformatic Analysis to Predict Candidate T-Cell Epitopes for SARS-CoV-2 Vaccine Design

Since the first outbreak of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2019, its high infectivity led to its prevalence around the world in an exceptionally short time. Efforts have been made to control the ongoing outbreak, and amo...

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Autores principales: Mei, Xueyin, Gu, Pan, Shen, Chuanlai, Lin, Xue, Li, Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9006954/
https://www.ncbi.nlm.nih.gov/pubmed/35432316
http://dx.doi.org/10.3389/fimmu.2022.847617
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author Mei, Xueyin
Gu, Pan
Shen, Chuanlai
Lin, Xue
Li, Jian
author_facet Mei, Xueyin
Gu, Pan
Shen, Chuanlai
Lin, Xue
Li, Jian
author_sort Mei, Xueyin
collection PubMed
description Since the first outbreak of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2019, its high infectivity led to its prevalence around the world in an exceptionally short time. Efforts have been made to control the ongoing outbreak, and among them, vaccine developments are going on high priority. New clinical trials add to growing evidence that vaccines from many countries were highly effective at preventing SARS-CoV-2 virus infection. One of them is B cell-based vaccines, which were common during a pandemic. However, neutralizing antibody therapy becomes less effective when viruses mutate. In order to tackle the problem, we focused on T-cell immune mechanism. In this study, the mutated strains of the virus were selected globally from India (B.1.617.1 and B.1.617.2), United Kingdom (B.1.1.7), South Africa (B.1.351), and Brazil (P.1), and the overlapping peptides were collected based on mutation sites of S-protein. After that, residue scanning was used to predict the affinity between overlapping peptide and HLA-A*11:01, the most frequent human leukocyte antigen (HLA) allele among the Chinese population. Then, the binding free energy was evaluated with molecular docking to further verify the affinity changes after the mutations happen in the virus genomes. The affinity test results of three epitopes on spike protein from experimental validation were consistent with our predicted results, thereby supporting the inclusion of the epitope (374)FSTFKCYGL(382) in future vaccine design and providing a useful reference route to improve vaccine development.
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spelling pubmed-90069542022-04-14 Computer-Based Immunoinformatic Analysis to Predict Candidate T-Cell Epitopes for SARS-CoV-2 Vaccine Design Mei, Xueyin Gu, Pan Shen, Chuanlai Lin, Xue Li, Jian Front Immunol Immunology Since the first outbreak of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2019, its high infectivity led to its prevalence around the world in an exceptionally short time. Efforts have been made to control the ongoing outbreak, and among them, vaccine developments are going on high priority. New clinical trials add to growing evidence that vaccines from many countries were highly effective at preventing SARS-CoV-2 virus infection. One of them is B cell-based vaccines, which were common during a pandemic. However, neutralizing antibody therapy becomes less effective when viruses mutate. In order to tackle the problem, we focused on T-cell immune mechanism. In this study, the mutated strains of the virus were selected globally from India (B.1.617.1 and B.1.617.2), United Kingdom (B.1.1.7), South Africa (B.1.351), and Brazil (P.1), and the overlapping peptides were collected based on mutation sites of S-protein. After that, residue scanning was used to predict the affinity between overlapping peptide and HLA-A*11:01, the most frequent human leukocyte antigen (HLA) allele among the Chinese population. Then, the binding free energy was evaluated with molecular docking to further verify the affinity changes after the mutations happen in the virus genomes. The affinity test results of three epitopes on spike protein from experimental validation were consistent with our predicted results, thereby supporting the inclusion of the epitope (374)FSTFKCYGL(382) in future vaccine design and providing a useful reference route to improve vaccine development. Frontiers Media S.A. 2022-03-30 /pmc/articles/PMC9006954/ /pubmed/35432316 http://dx.doi.org/10.3389/fimmu.2022.847617 Text en Copyright © 2022 Mei, Gu, Shen, Lin and Li https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Immunology
Mei, Xueyin
Gu, Pan
Shen, Chuanlai
Lin, Xue
Li, Jian
Computer-Based Immunoinformatic Analysis to Predict Candidate T-Cell Epitopes for SARS-CoV-2 Vaccine Design
title Computer-Based Immunoinformatic Analysis to Predict Candidate T-Cell Epitopes for SARS-CoV-2 Vaccine Design
title_full Computer-Based Immunoinformatic Analysis to Predict Candidate T-Cell Epitopes for SARS-CoV-2 Vaccine Design
title_fullStr Computer-Based Immunoinformatic Analysis to Predict Candidate T-Cell Epitopes for SARS-CoV-2 Vaccine Design
title_full_unstemmed Computer-Based Immunoinformatic Analysis to Predict Candidate T-Cell Epitopes for SARS-CoV-2 Vaccine Design
title_short Computer-Based Immunoinformatic Analysis to Predict Candidate T-Cell Epitopes for SARS-CoV-2 Vaccine Design
title_sort computer-based immunoinformatic analysis to predict candidate t-cell epitopes for sars-cov-2 vaccine design
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9006954/
https://www.ncbi.nlm.nih.gov/pubmed/35432316
http://dx.doi.org/10.3389/fimmu.2022.847617
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