Immunoinformatic Analysis of Crimean Congo Hemorrhagic Fever Virus Glycoproteins and Epitope Prediction for Synthetic Peptide Vaccine

To determine the Crimean Congo Hemorrhagic Fever (CCHF) virus M segement glycoprotein's immunoinformatic parameters, and identify Human Leukocyte Antigen (HLA) class I binders as candidates for synthetic peptide vaccines. Cross-sectional study. Combined Military Hospital, Khuzdar Cantt, in May 2015. Data acquisition, antigenicity prediction, secondary and tertiary structure prediction, residue analysis were done using immunoinformatics tools. HLAclass I binders in glycoprotein's sequence were identified at nanomer length using NetMHC 3.4 and mapped onto tertiary structure. Docking was done for strongest binder against its corresponding allele with CABS-dock. HLAA*0101, 0201, 0301, 2402, 2601 and B*0702, 0801, 2705, 3901, 4001, 5801, 1501 were analyzed against two glycoprotein components of the virus. Atotal of 35 nanomers from GP1, and 3 from GP2 were identified. HLAB*0702 bound maximum number of peptides (6), while HLAB*4001 showed strongest binding affinity. HLAspecific glycoproteins epitope prediction can help identify synthetic peptide vaccine candidates.