Mining of Ebola virus genome for the construction of multi-epitope vaccine to combat its infection

Abstract

Ebola virus is the primary causative agent of viral hemorrhagic fever that is an epidemic disease and responsible for the massive premature deaths in humans. Despite knowing the molecular mechanism of its pathogenesis, to date, no commercial or FDA approved multiepitope vaccine is available against Ebola infection. The current study focuses on designing a multi-epitope subunit vaccine for Ebola using a novel immunoinformatic approach. The best predicted antigenic epitopes of Cytotoxic-T cell (CTL), Helper-T cells (HTL), and B-cell epitopes (BCL) joined by various linkers were selected for the multi-epitope vaccine designing. For the enhanced immune response, two adjuvants were also added to the construct. Further analysis showed the vaccine to be immunogenic and non-allergenic, forming a stable and energetically favorable structure. The stability of the unbound vaccine construct and vaccine/TLR4 was elucidated via atomistic molecular dynamics simulations. The binding free energy analysis (ΔG_Bind = −194.2 ± 0.5 kcal/mol) via the molecular mechanics Poisson-Boltzmann docking scheme revealed a strong association and thus can initiate the maximal immune response. Next, for the optimal expression of the vaccine construct, its gene construct was cloned in the pET28a + vector system. In summary, the Ebola viral proteome was screened to identify the most potential HTLs, CTLs, and BCL epitopes. Along with various linkers and adjuvants, a multi-epitope vaccine is constructed that showed a high binding affinity with the immune receptor, TLR4. Thus, the current study provides a highly immunogenic multi-epitope subunit vaccine construct that may induce humoral and cellular immune responses against the Ebola infection.

Communicated by Ramaswamy H. Sarma

Keywords:

• Ebola
• multi-epitope vaccine
• hemorrhagic fever
• immunoinformatics
• molecular dynamics simulation
• MM-PBSA
• reverse vaccinology

Acknowledgements

US would like to acknowledge the Ministry of Education, Govt. of India, New Delhi, NJ to the Council of Scientific & Industrial Research (CSIR), Govt. of India, New Delhi and MFS to Department of Sceince and Technology (DST/INSPIRE_FELLOWSHIP/2017/IF170145), Govt. of India, New Delhi for their individual fellowships.

Disclosure statement

The authors have declared no competing interest.