Computational insights in design of Crimean-Congo hemorrhagic fever virus conserved immunogenic nucleoprotein peptides containing multiple epitopes.

Abstract

Crimean-Congo hemorrhagic fever virus (CCHFV) belongs to Nairoviridae family and has tripartite RNA genome. It is endemic in various countries of Asia, Africa, and Europe and is primarily transmitted by Hyalomma ticks but nosocomial transmission also been reported. Vaccines for CCHF are in early phase of clinical trial; therefore, this work is centered on identification of potential immunogenic peptide as vaccine candidates with application of different immunoinformatics approaches. Eleven conserved (>90%) peptides of CCHFV nucleoprotein were selected for CD8⁺ T-cell (NetMHCpan 4.1b and NetCTLpan 1.1 server) and CD4⁺ T-cell (NetMHCIIpan-4.0 server and Tepitool) epitope prediction. Three peptides containing multiple CD8⁺ and CD4⁺ T-cell and B-cell epitopes were identified on basis of consensus prediction approach. Peptides displayed good antigenicity score of 0.45-0.68 and predicted to bind with diverse human leukocyte antigen (HLA) alleles. Molecular docking was performed with epitopes to HLA and HLA-epitopes complex to T-cell receptor (TCR). In most of the cases, docked complex of HLA-epitope and HLA-epitopes-TCR have the binding energy close to respective natural bound peptide complex with HLA and TCR. Molecular dynamic simulation also revealed that HLA-peptide complexes have minimum fluctuation and deviation than HLA-peptide-TCR docked over 50 ns simulation run. Considering these findings, identified peptides can serve as potential vaccine candidates for CCHFV disease.