A Computational Approach for Identification of Epitopes in Dengue
Virus Envelope Protein: A Step Towards Designing a Universal Dengue Vaccine
Targeting Endemic Regions
Affiliations: Bioinformatics and Stress Biology Unit, Department of
Biochemistry and Molecular Biology, University of Dhaka, Dhaka,
Bangladesh | Victoria Research Laboratory, Department of Electrical
and Electronic Engineering National ICT Australia (NICTA), Victoria,
Australia | Department of Biological Sciences, Brock University,
Ontario, Canada | Laboratory Sciences Division, International Centre for
Diarrhoeal Disease Research Bangladesh (ICDDR, B), Mohakhali, Dhaka,
Bangladesh
Note: [] Corresponding author: Sohel Shamsuzzaman, Department of
Biochemistry and Molecular Biology, University of Dhaka, Dhaka 1000,
Bangladesh. Tel.: +880 2 9661920-73, ext. 7664; Fax: +880 2 8615583; E-mail:
[email protected]
Abstract: A major problem in designing vaccine for the dengue virus has been
the high antigenic variability in the envelope protein of different virus
strains. In this study, a computational approach was adopted to identify a
multi-epitope vaccine candidate against dengue virus that may be suitable for
large populations in the dengue-endemic regions. Different bioinformatics tools
were exploited that helped the identification of a conserved immunological
hot-spot in the dengue envelope protein. The tools also rendered the prediction
of immunogenicity and population coverage to the proposed 'in silico' vaccine
candidate against dengue. A peptide region, spanning 19 amino acids, was
identified in the envelope protein which found to be conserved in all four
types of dengue viruses. Ten proteasomal cleavage sites were identified within
the 19-mer conserved peptide sequence and a total of 8 overlapping putative
cytotoxic T cell (CTL) epitopes were identified. The immunogenicity of these
epitopes was evaluated in terms of their binding affinities to and dissociation
half-time from respective human leukocyte antigen (HLA) molecules. The HLA
allele frequencies were studied among populations in the dengue endemic regions
and compared with respect to HLA restriction patterns of the overlapping
epitopes. The cumulative population coverage for these epitopes as vaccine
candidates was high ranging from approximately 80% to 92%. Structural analysis
suggested that a 9-mer epitope fitted well into the peptide-binding groove of
HLA-A*0201. In conclusion, the 19-mer epitope cluster was shown to have the
potential for use as a vaccine candidate against dengue.
Keywords: Dengue, epitope vaccine, bioinformatics, HLA, population coverage
