Crimean Congo Hemorrhagic Fever virus (CCHFV) is a deadly human pathogen that causes an emerging zoonotic disease with a broad geographic spread, especially in Africa, Asia, and Europe, and the second most common viral hemorrhagic fever and widely transmitted tick-borne viral disease. Following infection, the patients are presented with a variety of clinical manifestations and a fatality rate of 40%. Despite the high fatality rate, there are unmet clinical interventions, as no antiviral drugs or vaccines for CCHF have been approved. Immunoinformatics pipeline and reverse vaccinology were used in this study to design a multi-epitope vaccine that may elicit a protective humoral and cellular immune response against Crimean-Congo hemorrhagic fever virus infection. Three essential virulent and antigenic proteins (S, M, and L) were used to predict seven CTL and 18 HTL epitopes that were non-allergenic, antigenic, IFN-γ inducing, and non-toxic. The epitopes were connected using linkers and 50S ribosomal protein L7/L12 was used as an adjuvant and raised a multi-epitope vaccine (MEV) that is 567 amino acids long. Molecular docking and simulation of the predicted 3D structure of the MEV with the toll-like (TLR2, TLR3, and TLR4) receptors and major histocompatibility complex (MCH-I and MCH-II) indicate high interactions and stability of the complexes, MM-GBSA free binding energy calculation revealed a favourable protein–protein complex. Maximum MEV expression was achieved with a CAI value of 0.98 through in silico cloning in the Drosophila melanogaster host. According to the immune simulation, IgG1, T-helper cells, T-cytotoxic cells, INF-γ, and IL-2 were predicted to be significantly elevated. These robust computational analyses demonstrated that the proposed MEV is effective in preventing CCHFV infections. However, it is still necessary to conduct both in vitro and in vivo experiments to validate the potential of the vaccine.
Lassa virus, an arenavirus, represents the most prevalent human pathogen causing viral haemorrhagic fever. It is endemic in Nigeria and other West African countries. Despite the high burden of the disease, limited treatments are available and no approved vaccine for the prevention of this disease is available. In this study, an immunoinformatics approach was used to predict response of B and T cells from the Lassa virus proteome (GPC, NP, L and Z). The designed chimeric vaccine was modeled, refined, validated and docked with the RIG-I receptor. The docked complex of vaccine-RIG-I was subjected to dynamic stability test and the results suggest that the complex is stable. Validation of the final vaccine construct was done through in silico cloning using E. coli as host. A CAI value of 0.99 suggests that the vaccine construct expressed properly in the host. Immune simulation predicted significantly high levels of IgG1, T-helper, T-cytotoxic cells, INF-γ and IL-2. This theoretical study suggests infection control by creating an effective immunological memory against Lassa virus infections. However, both in vitro and in vivo experiments are needed to validate the immunogenicity and safety of the chimeric vaccine.
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