| Abstract: | Since the outbreak of severe acute respiratory syndrome‐coronavirus 2 (SARS‐CoV‐2) in December 2019 in China, there has been an upsurge in the number of deaths and infected individuals throughout the world, thereby leading to the World Health Organization declaration of a pandemic. Since no specific therapy is currently available for the same, the present study was aimed to explore the SARS‐CoV‐2 genome for the identification of immunogenic regions using immunoinformatics approach. A series of computational tools were applied in a systematic way to identify the epitopes that could be utilized in vaccine development. The screened‐out epitopes were passed through several immune filters, such as promiscuousity, conservancy, antigenicity, nonallergenicity, population coverage, nonhomologous to human proteins, and affinity with human leukocyte antigen alleles, to screen out the best possible ones. Further, a construct comprising 11 CD4, 12 CD8, 3 B cell, and 3 interferon‐γ epitopes, along with an adjuvant β‐defensin, was designed in silico, resulting in the formation of a multiepitope vaccine. The in silico immune simulation and population coverage analysis of the vaccine sequence showed its capacity to elicit cellular, humoral, and innate immune cells and to cover up a worldwide population of more than 97%. Further, the interaction analysis of the vaccine construct with Toll‐like receptor 3 (immune receptor) was carried out by docking and dynamics simulations, revealing high affinity, constancy, and pliability between the two. The overall findings suggest that the vaccine may be highly effective, and is therefore required to be tested in the lab settings to evaluate its efficacy. |
