Design of a novel multi-epitope vaccine candidate against Yersinia pestis using advanced immunoinformatics approaches: An in silico study

Abstract

Yersinia pestis is the perilous pandemics that occurred in Asia and Europe. The bacterium has shown drug resistance that can cause the future pandemic and destroy the drug treatment against plague. As known, effective therapeutics such as designing potent vaccine that can aid world to protect against plague. The immunoinformatics approaches was implemented via different server. The 4 potent antigens (F1 capsule, LcrV, OmpA, and PH6) were listed as essential protein target for creating the multi-epitope vaccine. These targets were selected for designing multi-epitope vaccine that predicted the CTL and HTL epitopes. The vaccine construct included different linkers such as EAAAK, AAY, GPGPG, and SSL that an adjuvant (Beta defensin-3) inserted at N-terminal of vaccine. The computational physiochemical properties and other immunological analysis showed stable, soluble, antigen, non-allergen, and non-toxin. The molecular docking confirmed the stable binding and good interaction and the iMODS server showed the stable binding. Furthermore, computational immune simulation of multi-epitope vaccine showed that vaccine can stimulate adaptive and innate responses after second doses. In this study, the vaccine designed for Y. pestis that in future require immunological examination to unveil real efficiency.

Keywords

• Reverse vaccinology
• Computational immunology
• Immunoinformatics
• Multi-epitope vaccine