T-Cell Epitopes Based Vaccine Candidate’s Prediction for Treatment Against Burkholderia pseudomallei: Causative Agent of Melioidosis

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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T-Cell Epitopes Based Vaccine Candidate’s Prediction for Treatment Against Burkholderia pseudomallei: Causative Agent of Melioidosis

Cited by 2 publications

References 33 publications

An Immunoinformatic Study on Exploration of Membrane Proteins to Develop Epitope Based Vaccine Against Streptococcus pneumoniae

An Immunoinformatic Study on Exploration of Membrane Proteins to Develop Epitope Based Vaccine Against Streptococcus pneumoniae

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

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