Harnessing Bioinformatic Approaches to Designing a Multi-epitope Peptide Vaccine Against COVID-۱۹

Introduction: SARS-CoV-۲ is the causative agent of Coronavirus ۲۰۱۹ or COVID-۱۹ in the world. Novelcoronavirus disease is a respiratory disease. To date, there have been challenges in the treatment for COVID-۱۹ and emerged new variants. Accordingly, an effective prevention regime is needed for this infection, whichcovers most variants. The purpose of this research was to predict the conserved epitopes of Spike andNucleocapsid proteins from SARS-CoV-۲ for the design of a novel coronavirus ۲۰۱۹ multi-epitope vaccineusing in silico tools.Methods: Computational analysis and immunoinformatics approaches include identification of potentialconserve epitopes and selection of epitopes based on allergenicity, toxicity, antigenicity, and moleculardocking were used for epitope prediction and screening. In the next step, selected segments of the epitopeswere attached by the suitable linkers. Finally, Maltese-bound protein (MBP) as an adjuvant was added to thenovel vaccine structure. The secondary and third structures of the designed multi-epitope vaccine werepredicted via immunoinformatics algorithms. Predicted structure refined and validated for attaining beststability. In the end, immunoinformatics evaluation, molecular docking, and molecular dynamics wereperformed to confirm vaccine efficiency. Codon optimization and in silico cloning were done to ensure theexpression yield of the novel multi-epitope vaccine in the target host.Results: This study showed that our data support the suggestion that the designed vaccine could induceimmune responses against SARS-CoV-۲ variants.Conclusion: The Structure designed had acceptable quality with software reviews. Further in vitro and invivo experiments.

Keywords:

COVID-۱۹ , Immunoinformatics , SARS-CoV-۲ , multi-epitope vaccine , bioinformatics