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Bioinformatic prediction of the epitopes of Echinococcus granulosus antigen 5
The aim of the present study was to predict and analyze the secondary structure, and B and T cell epitopes of Echinococcus granulosus antigen 5 (Ag5) using online software in order to investigate its immunogenicity and preliminarily evaluate its potential as an effective antigen peptide vaccine for...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5351307/ https://www.ncbi.nlm.nih.gov/pubmed/28357070 http://dx.doi.org/10.3892/br.2016.827 |
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author | Pan, Wei Chen, De-Sheng Lu, Yun-Juan Sun, Fen-Fen Xu, Hui-Wen Zhang, Ya-Wen Yan, Chao Fu, Lin-Lin Zheng, Kui-Yang Tang, Ren-Xian |
author_facet | Pan, Wei Chen, De-Sheng Lu, Yun-Juan Sun, Fen-Fen Xu, Hui-Wen Zhang, Ya-Wen Yan, Chao Fu, Lin-Lin Zheng, Kui-Yang Tang, Ren-Xian |
author_sort | Pan, Wei |
collection | PubMed |
description | The aim of the present study was to predict and analyze the secondary structure, and B and T cell epitopes of Echinococcus granulosus antigen 5 (Ag5) using online software in order to investigate its immunogenicity and preliminarily evaluate its potential as an effective antigen peptide vaccine for cystic echinococcosis. The PortParam program was used to analyze molecular weight, the theoretical isoelectric point, instability index and other physicochemical properties. The secondary structure of the Ag5 protein was predicted using Self-Optimized Prediction method With Alignment and the tertiary structure of the Ag5 protein was predicted using 3DLigandSite together with Center for Biological Sequence Analysis Prediction Servers. Furthermore, the Immune Epitope Database software was used to predict B cell epitopes, and T cell epitopes were predicted with the BioInformatics and Molecular Analysis Section and SYFPEITHI programs. The results demonstrated that α-helixes, β-turns, random coils and extended strands account for 23.35, 10.95, 41.32, and 24.38% of the secondary structure of the Ag5 protein, respectively. Ten potential B cell epitopes of Ag5 were identified as the amino acids sequences 27–39, 70–80, 117–130, 146–168, 250–262, 284–293, 339–349, 359–371, 403–412 and 454–462, and seven potential T cell epitopes were identified as the amino acid sequences 52–60, 57–65, 182–190, 231–239, 273–281, 318–326 and 467–475. Thus, ten B cell epitopes and seven T cell epitopes were identified on Ag5, suggesting the strong immunogenicity of this protein, which could be applied to design antigen peptide vaccines for echinococcosis. |
format | Online Article Text |
id | pubmed-5351307 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-53513072017-03-29 Bioinformatic prediction of the epitopes of Echinococcus granulosus antigen 5 Pan, Wei Chen, De-Sheng Lu, Yun-Juan Sun, Fen-Fen Xu, Hui-Wen Zhang, Ya-Wen Yan, Chao Fu, Lin-Lin Zheng, Kui-Yang Tang, Ren-Xian Biomed Rep Articles The aim of the present study was to predict and analyze the secondary structure, and B and T cell epitopes of Echinococcus granulosus antigen 5 (Ag5) using online software in order to investigate its immunogenicity and preliminarily evaluate its potential as an effective antigen peptide vaccine for cystic echinococcosis. The PortParam program was used to analyze molecular weight, the theoretical isoelectric point, instability index and other physicochemical properties. The secondary structure of the Ag5 protein was predicted using Self-Optimized Prediction method With Alignment and the tertiary structure of the Ag5 protein was predicted using 3DLigandSite together with Center for Biological Sequence Analysis Prediction Servers. Furthermore, the Immune Epitope Database software was used to predict B cell epitopes, and T cell epitopes were predicted with the BioInformatics and Molecular Analysis Section and SYFPEITHI programs. The results demonstrated that α-helixes, β-turns, random coils and extended strands account for 23.35, 10.95, 41.32, and 24.38% of the secondary structure of the Ag5 protein, respectively. Ten potential B cell epitopes of Ag5 were identified as the amino acids sequences 27–39, 70–80, 117–130, 146–168, 250–262, 284–293, 339–349, 359–371, 403–412 and 454–462, and seven potential T cell epitopes were identified as the amino acid sequences 52–60, 57–65, 182–190, 231–239, 273–281, 318–326 and 467–475. Thus, ten B cell epitopes and seven T cell epitopes were identified on Ag5, suggesting the strong immunogenicity of this protein, which could be applied to design antigen peptide vaccines for echinococcosis. D.A. Spandidos 2017-02 2016-12-09 /pmc/articles/PMC5351307/ /pubmed/28357070 http://dx.doi.org/10.3892/br.2016.827 Text en Copyright: © Pan et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. |
spellingShingle | Articles Pan, Wei Chen, De-Sheng Lu, Yun-Juan Sun, Fen-Fen Xu, Hui-Wen Zhang, Ya-Wen Yan, Chao Fu, Lin-Lin Zheng, Kui-Yang Tang, Ren-Xian Bioinformatic prediction of the epitopes of Echinococcus granulosus antigen 5 |
title | Bioinformatic prediction of the epitopes of Echinococcus granulosus antigen 5 |
title_full | Bioinformatic prediction of the epitopes of Echinococcus granulosus antigen 5 |
title_fullStr | Bioinformatic prediction of the epitopes of Echinococcus granulosus antigen 5 |
title_full_unstemmed | Bioinformatic prediction of the epitopes of Echinococcus granulosus antigen 5 |
title_short | Bioinformatic prediction of the epitopes of Echinococcus granulosus antigen 5 |
title_sort | bioinformatic prediction of the epitopes of echinococcus granulosus antigen 5 |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5351307/ https://www.ncbi.nlm.nih.gov/pubmed/28357070 http://dx.doi.org/10.3892/br.2016.827 |
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