Designing a multi-epitope vaccine against the Lassa virus through reverse vaccinology, subtractive proteomics, and immunoinformatics approaches

Abstract

Abstract Lassa virus, an arenavirus, represents the most prevalent human pathogen causing viral hemorrhagic 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 and reverse vaccinology pipeline was employed to predict a multi-epitope vaccine. Four fundamental virulent and proteogenic proteins (glycoprotein precursor, Viral matrix protein, viral RNA polymerase, and Nucleoprotein) were identified. Using various immunoinformatics tools, 12 CTL, 14 HTL, and six B-cell epitopes were predicted and connected via suitable linkers, together with an adjuvant to develop a 602 amino acids long vaccine construct (VC). The VC was assessed to be non-allergenic, non-toxic, stable, soluble, and highly antigenic. Molecular docking of VC with RIG-I, major histocompatibility complex class I and class II were carried out to validate the interactions with the receptors. The complex of VC-RIG-I was subjected to a dynamic stability test and the RMDS and RMSF results suggest that the complex is stable. Validation of the final vaccine construct was done through in silico cloning using E. coli as a host. A CAI value of 0.99 suggests that the vaccine construct expressed properly in the host. The immune simulation predicted significantly high levels of IgG1, T-helper, T-cytotoxic cells, INF-γ, and IL-2. This rigorous computational 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 potential of the proposed vaccine.