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Design of an epitope-based peptide vaccine against spike protein of human coronavirus: an in silico approach

Human coronavirus (HCoV), a member of Coronaviridae family, is the causative agent of upper respiratory tract infections and “atypical pneumonia”. Despite severe epidemic outbreaks on several occasions and lack of antiviral drug, not much progress has been made with regard to an epitope-based vaccin...

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Autores principales: Oany, Arafat Rahman, Emran, Abdullah-Al, Jyoti, Tahmina Pervin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4149408/
https://www.ncbi.nlm.nih.gov/pubmed/25187696
http://dx.doi.org/10.2147/DDDT.S67861
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author Oany, Arafat Rahman
Emran, Abdullah-Al
Jyoti, Tahmina Pervin
author_facet Oany, Arafat Rahman
Emran, Abdullah-Al
Jyoti, Tahmina Pervin
author_sort Oany, Arafat Rahman
collection PubMed
description Human coronavirus (HCoV), a member of Coronaviridae family, is the causative agent of upper respiratory tract infections and “atypical pneumonia”. Despite severe epidemic outbreaks on several occasions and lack of antiviral drug, not much progress has been made with regard to an epitope-based vaccine designed for HCoV. In this study, a computational approach was adopted to identify a multiepitope vaccine candidate against this virus that could be suitable to trigger a significant immune response. Sequences of the spike proteins were collected from a protein database and analyzed with an in silico tool, to identify the most immunogenic protein. Both T cell immunity and B cell immunity were checked for the peptides to ensure that they had the capacity to induce both humoral and cell-mediated immunity. The peptide sequence from 88–94 amino acids and the sequence KSSTGFVYF were found as the most potential B cell and T cell epitopes, respectively. Furthermore, conservancy analysis was also done using in silico tools and showed a conservancy of 64.29% for all epitopes. The peptide sequence could interact with as many as 16 human leukocyte antigens (HLAs) and showed high cumulative population coverage, ranging from 75.68% to 90.73%. The epitope was further tested for binding against the HLA molecules, using in silico docking techniques, to verify the binding cleft epitope interaction. The allergenicity of the epitopes was also evaluated. This computational study of design of an epitope-based peptide vaccine against HCoVs allows us to determine novel peptide antigen targets in spike proteins on intuitive grounds, albeit the preliminary results thereof require validation by in vitro and in vivo experiments.
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spelling pubmed-41494082014-09-03 Design of an epitope-based peptide vaccine against spike protein of human coronavirus: an in silico approach Oany, Arafat Rahman Emran, Abdullah-Al Jyoti, Tahmina Pervin Drug Des Devel Ther Original Research Human coronavirus (HCoV), a member of Coronaviridae family, is the causative agent of upper respiratory tract infections and “atypical pneumonia”. Despite severe epidemic outbreaks on several occasions and lack of antiviral drug, not much progress has been made with regard to an epitope-based vaccine designed for HCoV. In this study, a computational approach was adopted to identify a multiepitope vaccine candidate against this virus that could be suitable to trigger a significant immune response. Sequences of the spike proteins were collected from a protein database and analyzed with an in silico tool, to identify the most immunogenic protein. Both T cell immunity and B cell immunity were checked for the peptides to ensure that they had the capacity to induce both humoral and cell-mediated immunity. The peptide sequence from 88–94 amino acids and the sequence KSSTGFVYF were found as the most potential B cell and T cell epitopes, respectively. Furthermore, conservancy analysis was also done using in silico tools and showed a conservancy of 64.29% for all epitopes. The peptide sequence could interact with as many as 16 human leukocyte antigens (HLAs) and showed high cumulative population coverage, ranging from 75.68% to 90.73%. The epitope was further tested for binding against the HLA molecules, using in silico docking techniques, to verify the binding cleft epitope interaction. The allergenicity of the epitopes was also evaluated. This computational study of design of an epitope-based peptide vaccine against HCoVs allows us to determine novel peptide antigen targets in spike proteins on intuitive grounds, albeit the preliminary results thereof require validation by in vitro and in vivo experiments. Dove Medical Press 2014-08-21 /pmc/articles/PMC4149408/ /pubmed/25187696 http://dx.doi.org/10.2147/DDDT.S67861 Text en © 2014 Oany et al. This work is published by Dove Medical Press Limited, and licensed under Creative Commons Attribution – Non Commercial (unported, v3.0) License The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.
spellingShingle Original Research
Oany, Arafat Rahman
Emran, Abdullah-Al
Jyoti, Tahmina Pervin
Design of an epitope-based peptide vaccine against spike protein of human coronavirus: an in silico approach
title Design of an epitope-based peptide vaccine against spike protein of human coronavirus: an in silico approach
title_full Design of an epitope-based peptide vaccine against spike protein of human coronavirus: an in silico approach
title_fullStr Design of an epitope-based peptide vaccine against spike protein of human coronavirus: an in silico approach
title_full_unstemmed Design of an epitope-based peptide vaccine against spike protein of human coronavirus: an in silico approach
title_short Design of an epitope-based peptide vaccine against spike protein of human coronavirus: an in silico approach
title_sort design of an epitope-based peptide vaccine against spike protein of human coronavirus: an in silico approach
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4149408/
https://www.ncbi.nlm.nih.gov/pubmed/25187696
http://dx.doi.org/10.2147/DDDT.S67861
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