Abstract
The inability of existing vaccines to cope with the mutation rate has highlighted the need for effective preventative strategies for COVID-19. Through the secretion of immunoglobulin A, mucosal delivery of vaccines can effectively stimulate mucosal immunity for better protection against SARS-CoV-2 infection. In this study, various immunoinformatic tools were used to design a multi-epitope oral vaccine against SARS-CoV-2 based on its receptor-binding domain (RBD) and heptad repeat (HR) domains. T and B lymphocyte epitopes were initially predicted from the RBD and HR domains of SARS-CoV-2, and potential antigenic, immunogenic, non-allergenic, and non-toxic epitopes were identified. Epitopes that are highly conserved and have no significant similarity to human proteome were selected. The epitopes were joined with appropriate linkers, and an adjuvant was added to enhance the vaccine efficacy. The vaccine 3D structure constructs were docked with toll-like receptor 4 (TLR-4) and TLR1-TLR2, and the binding affinity was calculated. The designed multi-epitope vaccine construct (MEVC) consisted of 33 antigenic T and B lymphocyte epitopes. The results of molecular dockings and free binding energies confirmed that the MEVC effectively binds to TLR molecules, and the complexes were stable. The results suggested that the designed MEVC is a potentially safe and effective oral vaccine against SARS-CoV-2. This in silico study presents a novel approach for creating an oral multi-epitope vaccine against the rapidly evolving SARS-CoV-2 variants. These findings offer valuable insights for developing an effective strategy to combat COVID-19. Further preclinical and clinical studies are required to confirm the efficacy of the MEVC vaccine.