Immunoinformatics guided modeling of CCHF_GN728, an mRNA-based universal vaccine against Crimean-Congo hemorrhagic fever virus

Abstract

The Crimean-Congo hemorrhagic fever virus (CCHFV) is a lethal human pathogen belonging to the Nairoviridae family that causes Crimean-Congo hemorrhagic fever (CCHF), a tick-borne infection with an alarming mortality rate of up to 80%. CCHFV is the most widespread tick-borne virus with the potential to trigger a pandemic. To date, no vaccines or therapeutics for CCHF have been authorized. In this study, we implemented immunoinformatics approach for developing CCHF_GN728, a universal mRNA-based multi-epitope vaccine against CCHFV. Glycoprotein precursor (GPC) and nucleoprotein (NP) from the virus were selected and screened for potential immunogenic T- and B-cell epitopes. Our developed antigen exhibited the potential to generate 99.95% population coverage worldwide. Stable epitope-allele interaction was confirmed using molecular docking and dynamics simulation. In silico immune simulation corroborated immune cell response to antigen clearance rate. Optimized codons ensured efficient expression of the mRNA in the host cell. The vaccine exhibited stable and strong interactions with the Toll-like receptors. Our findings suggest that the CCHF_GN728 vaccine will trigger specific anti-CCHFV immune responses. Our model is ready for wet-lab experimentation to assess the efficacy of this putative vaccine candidate.