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The COVID-19 disease is caused by SARS-CoV-2 and spreading rapidly worldwide with extremely high infection rate. Since effective and specific vaccine is not available to combat the deadly COVID-19, the objective of our study was to design a multi-epitope vaccine using immunoinformatics approach with translational implications. Nucleocapsid (N) protein of SARS-CoV-2 is stable, conserved and highly immunogenic along with being less prone to mutations during infection, which makes it a suitable candidate for designing vaccine. In our study, B- and T-cells epitopes were identified from N protein and screened based on crucial parameters to design the multi-epitope vaccine construct. Additionally, human beta-defensin-2 was incorporated into the vaccine construct as an adjuvant along with suitable linkers followed by its further evaluation based on crucial parameters including allergenicity, antigenicity, stability etc. Combined major histocompatibility complexes (MHC-I and MHC-II) binding epitopes presented broader population coverage of the vaccine throughout the world. The three-dimensional structure of vaccine candidate implied strong interaction with toll-like receptor 3 (TLR3) using molecular docking. The vaccine-TLR3 complex was observed to be highly stable during simulation and electrostatic free energy was foremost contributor for stabilization of the structure. Subsequently, in silico cloning of vaccine candidate was carried out to generate the construct into pET-28a(+) expression vector succeeded by its virtual confirmation. Altogether, our results advocate that the designed vaccine candidate could be an effective and promising weapon to fight with COVID-19 infection worldwide.

Designing of Nucleocapsid Protein Based Novel Multi-epitope Vaccine Against SARS-COV-2 Using Immunoinformatics Approach