In silico SARS-CoV-2 vaccine development for Omicron strain using reverse vaccinology.

BACKGROUND: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic began in 2019 but it remains as a serious threat today. To reduce and prevent spread of the virus, multiple vaccines have been developed. Despite the efforts in developing vaccines, Omicron strain of the virus has recently been designated as a variant of concern (VOC) by the World Health Organization (WHO). OBJECTIVE: To develop a vaccine candidate against Omicron strain (B.1.1.529, BA.1) of the SARS-CoV-19. METHODS: We applied reverse vaccinology methods for BA.1 and BA.2 as the vaccine target and a control, respectively. First, we predicted MHC I, MHC II and B cell epitopes based on their viral genome sequences. Second, after estimation of antigenicity, allergenicity and toxicity, a vaccine construct was assembled and tested for physicochemical properties and solubility. Third, AlphaFold2, RaptorX and RoseTTAfold servers were used to predict secondary structures and 3D structures of the vaccine construct. Fourth, molecular docking analysis was performed to test binding of our construct with angiotensin converting enzyme 2 (ACE2). Lastly, we compared mutation profiles on the epitopes between BA.1, BA.2, and wild type to estimate the efficacy of the vaccine. RESULTS: We collected a total of 10 MHC I, 9 MHC II and 5 B cell epitopes for the final vaccine construct for Omicron strain. All epitopes were predicted to be antigenic, non-allergenic and non-toxic. The construct was estimated to have proper stability and solubility. The best modelled tertiary structures were selected for molecular docking analysis with ACE2 receptor. CONCLUSIONS: These results suggest the potential efficacy of our newly developed vaccine construct as a novel vaccine candidate against Omicron strain of the coronavirus.

Immunogenic Epitope-Based Vaccine Prediction from Surface Glycoprotein of MERS-CoV by Deploying Immunoinformatics Approach.

Middle East respiratory syndrome coronavirus (MERS-CoV) has caused a high mortality rate since its emergence in 2012 in the Middle East. Currently, no effective drug or vaccine is available for MERS-CoV. Supportive care and prevention are the only ways to manage infection. In this study, we identified an epitope-based vaccine that could be an optimal solution for the prevention of MERS-CoV infection. By deploying an immunoinformatics approach, we predicted a subunit vaccine based on the surface glycoprotein (S protein) of MERS-CoV. For this purpose, the proteome of the MERS-CoV spike protein was obtained from the NCBI GenBank database. Then, it was subjected to a check for allergenicity using the Allergen FP v.1.0 tool. The Vaxijen v.2.0 tool was used to conduct antigenicity tests for binding with major histocompatibility complex class I and II molecules. The solidity of the predicted epitope-allele docked complex was evaluated by a molecular dynamics simulation. After docking a total of eight epitopes from the MERS-CoV S protein, further analyses predicted their non-toxicity and therapeutic immunogenic properties. These epitopes have potential utility as vaccine candidates against MERS-CoV, to be validated by wet-lab testing. Supplementary Information: The online version contains supplementary material available at 10.1007/s10989-022-10382-5.