Introduction: The ongoing life-threatening pandemic of coronavirus disease 2019 (COVID-19) has extensively affected the world. During this global health crisis, it is fundamentally crucial to find strategies to combat SARS-CoV-2. Despite several efforts in this direction and continuing clinical trials, no vaccine has been approved for it yet. Methods: To find a preventive measure, we have computationally designed a multi-epitopic subunit vaccine using immuno-informatic approaches. Results: The structural proteins of SARS-CoV-2 involved in its survival and pathogenicity were used to predict antigenic epitopes. The antigenic epitopes were capable of eliciting a strong humoral as well as cellmediated immune response, our predictions suggest. The final vaccine was constructed by joining the all epitopes with specific linkers and to enhance their stability and immunogenicity. The physicochemical property of the vaccine was assessed. The vaccine 3D structure prediction and validation were done and docked with the human TLR-3 receptor. Furthermore, molecular dynamics simulations of the vaccine-TLR-3 receptor complex are employed to assess its dynamic motions and binding stability in-silico. Conclusion: Based on this study, we strongly suggest synthesizing this vaccine, which further can be tested in-vitro and in-vivo to check its potency in a cure for COVID-19.
Japanese encephalitis virus (JEV) is one of the major causes of viral encephalitis all around the globe. Approximately 3 billion people in endemic areas are at risk of Japanese encephalitis. To develop a wholistic understanding of the viral proteome, it is important to investigate both its ordered and disordered proteins. However, the functional and structural significance of disordered regions in the JEV proteome has not been systematically investigated as of yet. To fill this gap, we used here a set of bioinformatics tools to analyze the JEV proteome for the predisposition of its proteins for intrinsic disorder and for the presence of the disorder‐based binding regions (also known as molecular recognition features, MoRFs). We also analyzed all JEV proteins for the presence of the probable nucleic acid‐binding (DNA and RNA) sites. The results of these computational studies are experimentally validated using JEV capsid protein as an illustrative example. In agreement with bioinformatic analysis, we found that the N‐terminal region of the JEV capsid (residues 1–30) is intrinsically disordered. We showed that this region is characterized by the temperature response typical for highly disordered proteins. Furthermore, we have experimentally shown that this disordered N‐terminal domain of a capsid protein has a noticeable ‘gain‐of‐structure’ potential. In addition, using DOPS liposomes, we demonstrated the presence of pronounced membrane‐mediated conformational changes in the N‐terminal region of JEV capsid. In our view, this disorder‐centric analysis would be helpful for a better understanding of the JEV pathogenesis.
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