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


Citation

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).

Abstract / Synopsis

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.


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Additional Metadata

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculty of Biotechnology and Biomolecular Sciences
Faculty of Veterinary Medicine
Institute of Bioscience
Publisher: Faculty of Veterinary Medicine, Universiti Putra Malaysia
Keywords: IBDV; IBD; Bioinformatics; Prediction; Epitope
Depositing User: Nabilah Mustapa
Date Deposited: 03 Sep 2018 12:49
Last Modified: 03 Sep 2018 12:49
URI: http://psasir.upm.edu.my/id/eprint/65043
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