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Vaccine Design for H5N1 Based on B- and T-cell Epitope Predictions.

Authors :
Tambunan US
Sipahutar FR
Parikesit AA
Kerami D
Source :
Bioinformatics and biology insights [Bioinform Biol Insights] 2016 Apr 28; Vol. 10, pp. 27-35. Date of Electronic Publication: 2016 Apr 28 (Print Publication: 2016).
Publication Year :
2016

Abstract

From 2003 to 2013, Indonesia had the highest number of avian influenza A cases in humans, with 192 cases and 160 fatalities. Avian influenza is caused by influenza virus type A, such as subtype H5N1. This virus has two glycoproteins: hemagglutinin and neuraminidase, which will become the primary target to be neutralized by vaccine. Vaccine is the most effective immunologic intervention. In this study, we use the epitope-based vaccine design from hemagglutinin and neuraminidase of H5N1 Indonesian strain virus by using immunoinformatics approach in order to predict the binding of B-cell and T-cell epitopes (class I and class II human leukocyte antigen [HLA]). BCPREDS was used to predict the B-cell epitope. Propred, Propred I, netMHCpan, and netMHCIIpan were used to predict the T-cell epitope. Two B-cell epitopes of hemagglutinin candidates and one B-cell epitope of neuraminidase candidates were obtained to bind T-cell CD4(+) (class II HLA), and also five T-cell epitope hemagglutinin and four T-cell epitope neuraminidase were obtained to bind T-cell CD8(+) (class I HLA). The visualization of epitopes was done using MOE 2008.10. It shows that the binding affinity of epitope-HLA was based on minimum binding free energy (ΔG binding). Based on this result, visualization, and dynamic simulation, four hemagglutinin epitopes (MEKIVLLLA, CPYLGSPSF, KCQTPMGAI, and IGTSTLNQR) and two neuraminidase epitopes (NPNQKIITI and CYPDAGEIT) were computed as having the best binding affinity from HLA ligand. The results mentioned above are from in silico experiments and need to be validated using wet experiment.

Details

Language :
English
ISSN :
1177-9322
Volume :
10
Database :
MEDLINE
Journal :
Bioinformatics and biology insights
Publication Type :
Academic Journal
Accession number :
27147821
Full Text :
https://doi.org/10.4137/BBI.S38378