A novel strategy for developing a tetravalent vaccine (dvac) against dengue utilizing conserved regions from all DENV proteins

Background Immunoinformatics is an emerging interdisciplinary field which integrates immunology, bioinformatics, and computational biology to study the immune system. In this study, we apply immunoinformatics approaches to explore the dengue proteome in order to design a multi-epitope vaccine construct. Methods We used existing databases and algorithms to predict potential epitopes on dengue proteins and used a bioinformatics approach to identify the most promising epitopes. We then used molecular modelling to develop a multi-epitope construct which could be used as a potential vaccine. The results of this study demonstrate that immunoinformatics is a powerful tool for exploring and designing potential vaccines for infectious diseases like dengue. Results Here, we found four CD4+ epitopes NLKYSVIVTVHTGDQ, ANPIVTDKEKPVNIE, LDPVVYDAKFEKQL, and VGAIALDFKPGTSGS that were used to design vaccine construct. The vaccine construct docked with TLR5. RMSD values suggest that docked complex of TLR5 and vaccine construct have putative stable interaction to induce immunogenic effects on host. Conclusions Furthermore, our study provides a proof of concept for the use of immunoinformatics approaches in DENV vaccine design. This vaccine can be effective in treating patients infected with DENV virus.

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A novel strategy for developing a tetravalent vaccine (dvac) against dengue utilizing conserved regions from all DENV proteins

Cited by 4 publications

References 36 publications

In silico strategies for predicting therapeutic peptides targeting the capsid protein of the dengue virus

In silico strategies for predicting therapeutic peptides targeting the capsid protein of the dengue virus

Computational modeling of drugs for neglected diseases

Immunoinformatics study to explore dengue (DENV-1) proteome to design multi-epitope vaccine construct by using CD4+ epitopes

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