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Prediction and in silico identification of novel B-cells and T-cells epitopes in the S1-spike glycoprotein of M41 and CR88 (793/B) infectious bronchitis virus serotypes for applictaion in peptide vacc

Bioinformatic analysis was used to predict antigenic B-cell and T-cell epitopes within the S1 glycoprotein of M41 and CR88 IBV strains. A conserved linear B-cell epitope peptide, , was identified in M41 IBV strains while three such epitopes types namely, , , and , were predicted in CR88 IBV strains....

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Main Authors: Bande, Faruku, Arshad, Siti Suri, Bejo, Mohd Hair, Kadkhodaei, Saeid, Omar, Abdul Rahman
Format: Article
Language:English
Published: Hindawi Publishing Corporation 2016
Online Access:http://psasir.upm.edu.my/id/eprint/53633/1/Prediction%20and%20in%20silico.pdf
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spelling oai:psasir.upm.edu.my:53633 http://psasir.upm.edu.my/id/eprint/53633/ Prediction and in silico identification of novel B-cells and T-cells epitopes in the S1-spike glycoprotein of M41 and CR88 (793/B) infectious bronchitis virus serotypes for applictaion in peptide vacc Bande, Faruku Arshad, Siti Suri Bejo, Mohd Hair Kadkhodaei, Saeid Omar, Abdul Rahman Bioinformatic analysis was used to predict antigenic B-cell and T-cell epitopes within the S1 glycoprotein of M41 and CR88 IBV strains. A conserved linear B-cell epitope peptide, , was identified in M41 IBV strains while three such epitopes types namely, , , and , were predicted in CR88 IBV strains. Analysis of MHCI binding peptides in M41 IBV strains revealed the presence of 15 antigenic peptides out of which 12 were highly conserved in 96–100% of the total M41 strains analysed. Interestingly three of these peptides, GGPITYKVM208, WFNSLSVSI356, and YLADAGLAI472, relatively had high antigenicity index (>1.0). On the other hand, 11 MHCI binding epitope peptides were identified in CR88 IBV strains. Of these, five peptides were found to be highly conserved with a range between 90% and 97%. However, WFNSLSVSL358, SYNISAASV88, and YNISAASVA89 peptides comparably showed high antigenicity scores (>1.0). Combination of antigenic B-cells and T-cells peptides that are conserved across many strains as approach to evoke humoral and CTL immune response will potentially lead to a broad-based vaccine that could reduce the challenges in using live attenuated vaccine technology in the control of IBV infection in poultry. Hindawi Publishing Corporation 2016 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/53633/1/Prediction%20and%20in%20silico.pdf Bande, Faruku and Arshad, Siti Suri and Bejo, Mohd Hair and Kadkhodaei, Saeid and Omar, Abdul Rahman (2016) Prediction and in silico identification of novel B-cells and T-cells epitopes in the S1-spike glycoprotein of M41 and CR88 (793/B) infectious bronchitis virus serotypes for applictaion in peptide vacc. Advances in Bioinformatics, 2016. art. no. 5484972. pp. 1-5. ISSN 1687-8027; ESSN: 1687-8035 https://www.hindawi.com/journals/abi/2016/5484972/abs/ 10.1155/2016/5484972
institution UPM IR
collection UPM IR
language English
description Bioinformatic analysis was used to predict antigenic B-cell and T-cell epitopes within the S1 glycoprotein of M41 and CR88 IBV strains. A conserved linear B-cell epitope peptide, , was identified in M41 IBV strains while three such epitopes types namely, , , and , were predicted in CR88 IBV strains. Analysis of MHCI binding peptides in M41 IBV strains revealed the presence of 15 antigenic peptides out of which 12 were highly conserved in 96–100% of the total M41 strains analysed. Interestingly three of these peptides, GGPITYKVM208, WFNSLSVSI356, and YLADAGLAI472, relatively had high antigenicity index (>1.0). On the other hand, 11 MHCI binding epitope peptides were identified in CR88 IBV strains. Of these, five peptides were found to be highly conserved with a range between 90% and 97%. However, WFNSLSVSL358, SYNISAASV88, and YNISAASVA89 peptides comparably showed high antigenicity scores (>1.0). Combination of antigenic B-cells and T-cells peptides that are conserved across many strains as approach to evoke humoral and CTL immune response will potentially lead to a broad-based vaccine that could reduce the challenges in using live attenuated vaccine technology in the control of IBV infection in poultry.
format Article
author Bande, Faruku
Arshad, Siti Suri
Bejo, Mohd Hair
Kadkhodaei, Saeid
Omar, Abdul Rahman
spellingShingle Bande, Faruku
Arshad, Siti Suri
Bejo, Mohd Hair
Kadkhodaei, Saeid
Omar, Abdul Rahman
Prediction and in silico identification of novel B-cells and T-cells epitopes in the S1-spike glycoprotein of M41 and CR88 (793/B) infectious bronchitis virus serotypes for applictaion in peptide vacc
author_facet Bande, Faruku
Arshad, Siti Suri
Bejo, Mohd Hair
Kadkhodaei, Saeid
Omar, Abdul Rahman
author_sort Bande, Faruku
title Prediction and in silico identification of novel B-cells and T-cells epitopes in the S1-spike glycoprotein of M41 and CR88 (793/B) infectious bronchitis virus serotypes for applictaion in peptide vacc
title_short Prediction and in silico identification of novel B-cells and T-cells epitopes in the S1-spike glycoprotein of M41 and CR88 (793/B) infectious bronchitis virus serotypes for applictaion in peptide vacc
title_full Prediction and in silico identification of novel B-cells and T-cells epitopes in the S1-spike glycoprotein of M41 and CR88 (793/B) infectious bronchitis virus serotypes for applictaion in peptide vacc
title_fullStr Prediction and in silico identification of novel B-cells and T-cells epitopes in the S1-spike glycoprotein of M41 and CR88 (793/B) infectious bronchitis virus serotypes for applictaion in peptide vacc
title_full_unstemmed Prediction and in silico identification of novel B-cells and T-cells epitopes in the S1-spike glycoprotein of M41 and CR88 (793/B) infectious bronchitis virus serotypes for applictaion in peptide vacc
title_sort prediction and in silico identification of novel b-cells and t-cells epitopes in the s1-spike glycoprotein of m41 and cr88 (793/b) infectious bronchitis virus serotypes for applictaion in peptide vacc
publisher Hindawi Publishing Corporation
publishDate 2016
url http://psasir.upm.edu.my/id/eprint/53633/1/Prediction%20and%20in%20silico.pdf
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score 13.4562235

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