artificial intelligence folding of crimean-congo hemorrhagic fever virus proteins for establishing vaccine strategies

Crimean-congo hemorrhagic fever virus (cchfv) is a lethal and highly contagious zoonotic pathogenthat causes a fatal disease with hemorrhagic characteristics. the widespread virus possesses a tripartite, singlestranded rna genome in which, from the transcription and cleavage of the medium-sized segment, severalproteins are yielded, including glycoprotein n, glycoprotein c, and non-structural m protein (nsm).glycoproteins c and n are directly involved in the host cell entry, fusion, and virus pathogenesis, whereas therole of the nsm is yet to be discovered. in this study the 3d structures of n, c, and m proteins were acquired byusing colabfold, an artificial intelligence (ai) tool. the highest confidence rate was observed in the predictedstructure of n protein with 85% accuracy. the second-best structure is c protein with 70% accuracy. while them protein structure was predicted with very low confidence. the predicted 3d models with significant accuracyrates can benefit the future development of vaccines and drug design.