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 pathogen that 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, several proteins 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 the role of the Nsm is yet to be discovered. In this study the 3D structures of N, C, and M proteins were acquired by using Colabfold, an artificial intelligence (AI) tool. The highest confidence rate was observed in the predicted structure of N protein with 85% accuracy. The second-best structure is C protein with 70% accuracy. While the M protein structure was predicted with very low confidence. The predicted 3D models with significant accuracy rates can benefit the future development of vaccines and drug design.