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Computational Design of a Multi-epitope Vaccine Against Clostridium chauvoei: An Immunoinformatics Approach

Blackleg is an infectious disease of animals that is commonly caused by Clostridium chauvoei and characterized by localized muscle necrosis. In this study, proteome-mining and immunoinformatics approaches were applied to identify novel antigenic proteins and to construct a multi-epitope vaccine agai...

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Autor principal: Yılmaz Çolak, Çiğdem
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8414032/
https://www.ncbi.nlm.nih.gov/pubmed/34493934
http://dx.doi.org/10.1007/s10989-021-10279-9
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author Yılmaz Çolak, Çiğdem
author_facet Yılmaz Çolak, Çiğdem
author_sort Yılmaz Çolak, Çiğdem
collection PubMed
description Blackleg is an infectious disease of animals that is commonly caused by Clostridium chauvoei and characterized by localized muscle necrosis. In this study, proteome-mining and immunoinformatics approaches were applied to identify novel antigenic proteins and to construct a multi-epitope vaccine against C. chauvoei. All proteins of C. chauvoei strains were retrieved from the NCBI Microbial Genome Database containing both genomic and proteomic data of prokaryotes. The proteins were analyzed to exclude non-redundant sequences and to determine antigenic, virulent, and non-allergenic vaccine candidates through several online tools, resulting in seven protein candidates. Cytotoxic T and B cell epitopes of these proteins were evaluated through the tools present in the immune epitope database and the prioritized antigenic epitopes were then conjugated via appropriate linkers to construct the vaccine candidate. After the evaluation of physicochemical properties of the construct, the tertiary structure was modeled and refined through trRosetta and GalaxyRefine, respectively. The quality of the 3D structure was validated by ERRAT score, z-score, and Ramachandran plot and the construct was then docked with bovine Toll-like receptor 4 (TLR 4) using ClusPro. The docked complex was subjected to Molecular Mechanics/Generalized Born Surface Area in the HawkDock server and normal mode analysis in the iMODS simulation suite to assess the binding energy and stability of the complex, respectively. Overall, the vaccine construct was found stable and energetically feasible for bovine TLR 4 binding. Therefore, it can be used as a multi-epitope vaccine construct in clostridial vaccines to control the blackleg disease. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10989-021-10279-9.
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spelling pubmed-84140322021-09-03 Computational Design of a Multi-epitope Vaccine Against Clostridium chauvoei: An Immunoinformatics Approach Yılmaz Çolak, Çiğdem Int J Pept Res Ther Article Blackleg is an infectious disease of animals that is commonly caused by Clostridium chauvoei and characterized by localized muscle necrosis. In this study, proteome-mining and immunoinformatics approaches were applied to identify novel antigenic proteins and to construct a multi-epitope vaccine against C. chauvoei. All proteins of C. chauvoei strains were retrieved from the NCBI Microbial Genome Database containing both genomic and proteomic data of prokaryotes. The proteins were analyzed to exclude non-redundant sequences and to determine antigenic, virulent, and non-allergenic vaccine candidates through several online tools, resulting in seven protein candidates. Cytotoxic T and B cell epitopes of these proteins were evaluated through the tools present in the immune epitope database and the prioritized antigenic epitopes were then conjugated via appropriate linkers to construct the vaccine candidate. After the evaluation of physicochemical properties of the construct, the tertiary structure was modeled and refined through trRosetta and GalaxyRefine, respectively. The quality of the 3D structure was validated by ERRAT score, z-score, and Ramachandran plot and the construct was then docked with bovine Toll-like receptor 4 (TLR 4) using ClusPro. The docked complex was subjected to Molecular Mechanics/Generalized Born Surface Area in the HawkDock server and normal mode analysis in the iMODS simulation suite to assess the binding energy and stability of the complex, respectively. Overall, the vaccine construct was found stable and energetically feasible for bovine TLR 4 binding. Therefore, it can be used as a multi-epitope vaccine construct in clostridial vaccines to control the blackleg disease. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10989-021-10279-9. Springer Netherlands 2021-09-03 2021 /pmc/articles/PMC8414032/ /pubmed/34493934 http://dx.doi.org/10.1007/s10989-021-10279-9 Text en © The Author(s), under exclusive licence to Springer Nature B.V. 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Yılmaz Çolak, Çiğdem
Computational Design of a Multi-epitope Vaccine Against Clostridium chauvoei: An Immunoinformatics Approach
title Computational Design of a Multi-epitope Vaccine Against Clostridium chauvoei: An Immunoinformatics Approach
title_full Computational Design of a Multi-epitope Vaccine Against Clostridium chauvoei: An Immunoinformatics Approach
title_fullStr Computational Design of a Multi-epitope Vaccine Against Clostridium chauvoei: An Immunoinformatics Approach
title_full_unstemmed Computational Design of a Multi-epitope Vaccine Against Clostridium chauvoei: An Immunoinformatics Approach
title_short Computational Design of a Multi-epitope Vaccine Against Clostridium chauvoei: An Immunoinformatics Approach
title_sort computational design of a multi-epitope vaccine against clostridium chauvoei: an immunoinformatics approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8414032/
https://www.ncbi.nlm.nih.gov/pubmed/34493934
http://dx.doi.org/10.1007/s10989-021-10279-9
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