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Computational approach in predicting infectious bursal disease virus (IBDV) epitopes

Infectious bursal disease (IBD) causes immunosuppression and mortality in chickens from 3- 6 weeks of age. Its aetiological agent, infectious bursal disease virus (IBDV) originates from the family Birnaviridae. It was first detected circa 1962 in Gumboro, Texas and has made its way to Europe, Russia...

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Main Authors: Awang Keri, Awang Ilham, Mat Isa, Nurulfiza, Omar, Abdul Rahman, Bejo, Mohd Hair
Format: Conference or Workshop Item
Language:English
Published: Faculty of Veterinary Medicine, Universiti Putra Malaysia 2015
Online Access:http://psasir.upm.edu.my/id/eprint/65043/1/PA-42.pdf
http://psasir.upm.edu.my/id/eprint/65043/
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spelling my.upm.eprints.650432018-09-03T04:49:33Z http://psasir.upm.edu.my/id/eprint/65043/ Computational approach in predicting infectious bursal disease virus (IBDV) epitopes Awang Keri, Awang Ilham Mat Isa, Nurulfiza Omar, Abdul Rahman Bejo, Mohd Hair Infectious bursal disease (IBD) causes immunosuppression and mortality in chickens from 3- 6 weeks of age. Its aetiological agent, infectious bursal disease virus (IBDV) originates from the family Birnaviridae. It was first detected circa 1962 in Gumboro, Texas and has made its way to Europe, Russia and Asia. Currently, IBD outbreaks are controlled by vaccinating chicken flocks. VP2 protein of IBDV is known to possess the antigenic region responsible for eliciting neutralizing antibodies. Computational approach in epitope prediction allows researchers to narrow down the proteins of interest and reducing the number of wet experiments. This approach have been applied to predict epitopes from various viruses for instance the human avian H5N1, foot-and-mouth disease (FMD) virus and dengue virus (DENV). Thus, the study aims to predict the linear B-cell epitopes of local IBDV strains using bioinformatics approach. Fifty-six local IBDV protein sequences were retrieved and 38 sequences have been determined as very virulent (VV) strain by multiple sequence alignment based on the amino acid markers. Twenty-one sequences scored above threshold for antigenic scoring and followed by linear B-cell epitope prediction using four different prediction servers which produced 126, 15, 37 and 79 epitopes respectively. Two common epitopes sequences were determined by Venn diagram. Conservancy degrees of the common epitopes were deduced. These results suggest that the epitopes predicted by computational approach could be further studied to develop vaccines against IBD outbreaks. Faculty of Veterinary Medicine, Universiti Putra Malaysia 2015 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/65043/1/PA-42.pdf Awang Keri, Awang Ilham and Mat Isa, Nurulfiza and Omar, Abdul Rahman and Bejo, Mohd Hair (2015) Computational approach in predicting infectious bursal disease virus (IBDV) epitopes. In: World Veterinary Poultry Association (Malaysia Branch) and World's Poultry Science Association (Malaysia Branch) Scientific Conference 2015, 21-22 Sept. 2015, Kuala Lumpur Convention Centre, Kuala Lumpur, Malaysia. (pp. 200-202).
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Infectious bursal disease (IBD) causes immunosuppression and mortality in chickens from 3- 6 weeks of age. Its aetiological agent, infectious bursal disease virus (IBDV) originates from the family Birnaviridae. It was first detected circa 1962 in Gumboro, Texas and has made its way to Europe, Russia and Asia. Currently, IBD outbreaks are controlled by vaccinating chicken flocks. VP2 protein of IBDV is known to possess the antigenic region responsible for eliciting neutralizing antibodies. Computational approach in epitope prediction allows researchers to narrow down the proteins of interest and reducing the number of wet experiments. This approach have been applied to predict epitopes from various viruses for instance the human avian H5N1, foot-and-mouth disease (FMD) virus and dengue virus (DENV). Thus, the study aims to predict the linear B-cell epitopes of local IBDV strains using bioinformatics approach. Fifty-six local IBDV protein sequences were retrieved and 38 sequences have been determined as very virulent (VV) strain by multiple sequence alignment based on the amino acid markers. Twenty-one sequences scored above threshold for antigenic scoring and followed by linear B-cell epitope prediction using four different prediction servers which produced 126, 15, 37 and 79 epitopes respectively. Two common epitopes sequences were determined by Venn diagram. Conservancy degrees of the common epitopes were deduced. These results suggest that the epitopes predicted by computational approach could be further studied to develop vaccines against IBD outbreaks.
format Conference or Workshop Item
author Awang Keri, Awang Ilham
Mat Isa, Nurulfiza
Omar, Abdul Rahman
Bejo, Mohd Hair
spellingShingle Awang Keri, Awang Ilham
Mat Isa, Nurulfiza
Omar, Abdul Rahman
Bejo, Mohd Hair
Computational approach in predicting infectious bursal disease virus (IBDV) epitopes
author_facet Awang Keri, Awang Ilham
Mat Isa, Nurulfiza
Omar, Abdul Rahman
Bejo, Mohd Hair
author_sort Awang Keri, Awang Ilham
title Computational approach in predicting infectious bursal disease virus (IBDV) epitopes
title_short Computational approach in predicting infectious bursal disease virus (IBDV) epitopes
title_full Computational approach in predicting infectious bursal disease virus (IBDV) epitopes
title_fullStr Computational approach in predicting infectious bursal disease virus (IBDV) epitopes
title_full_unstemmed Computational approach in predicting infectious bursal disease virus (IBDV) epitopes
title_sort computational approach in predicting infectious bursal disease virus (ibdv) epitopes
publisher Faculty of Veterinary Medicine, Universiti Putra Malaysia
publishDate 2015
url http://psasir.upm.edu.my/id/eprint/65043/1/PA-42.pdf
http://psasir.upm.edu.my/id/eprint/65043/
_version_ 1643838202499301376
score 13.211869

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