Designing, characterization, and immune stimulation of a novel multi-epitopic peptide-based potential vaccine candidate against monkeypox virus through screening its whole genome encoded proteins: An immunoinformatics approach

Abstract

Background: The current monkeypox virus (MPXV) spread in the non-epidemic regions raises global concern. Presently, the smallpox vaccine is used against monkeypox with several difficulties. Conversely, no next-generation vaccine is available against MPXV. Here, we proposed a novel multi-epitopic peptide-based in-silico potential vaccine candidate against the monkeypox virus.

Methods: The multi-epitopic potential vaccine construct was developed from antigen screening through whole genome-encoded 176 proteins of MPXV. Afterward, ten common B and T cell epitopes (9-mer) having the highest antigenicity and high population coverage were chosen, and a vaccine construct was developed using peptide linkers. The vaccine was characterized through bioinformatics to understand antigenicity, non-allergenicity, physicochemical properties, and binding affinity to immune receptors (TLR4/MD2-complex). Finally, the immune system simulation of the vaccine was performed through immunoinformatics and machine learning approaches.

Results: The highest antigenic epitopes were used to design the vaccine. The docked complex of the vaccine and TLR4/MD2 had shown significant free binding energy (-98.37 kcal/mol) with a definite binding affinity. Likewise, the eigenvalue (2.428517e-05) from NMA analysis of this docked complex reflects greater flexibility, adequate molecular motion, and reduced protein deformability, and it can provoke a robust immune response.

Conclusions: The designed vaccine has shown the required effectiveness against MPXV without any side effects, a significant milestone against the neglected disease.

Keywords: Immunoinformatics; Molecular docking; Monkeypox virus (MPXV); Multi-epitope; Peptide-based vaccine.