Identification of vaccine candidate against Omicron variant of SARS-CoV-2 using immunoinformatic approaches.

Abstract

Despite the availability of COVID-19 vaccines, additional more potent vaccines are still required against the emerging variations of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In the present investigation, we have identified a promising vaccine candidate against the Omicron (B.1.1.529) using immunoinformatics approaches. Various available tools like, the Immune Epitope Database server resource, and NetCTL-1.2, have been used for the identification of the promising T-cell and B-cell epitopes. The molecular docking was performed to check the interaction of TLR-3 receptors and validated 3D model of vaccine candidate. The codon optimization was done followed by cloning using SnapGene. Finally, In-silico immune simulation profile was also checked. The identified T-cell and B-cell epitopes have been selected based on their antigenicity (VaxiJen v2.0) and, allergenicity (AllerTOP v2.0). The identified epitopes with antigenic and non-allergenic properties were fused with the specific peptide linkers. In addition, the 3D model was constructed by the PHYRE2 server and validated using ProSA-web. The validated 3D model was further docked with the Toll-like receptor 3 (TLR3) and showed good interaction with the amino acids which indicate a promising vaccine candidate against the Omicron variant of SARS-CoV-2. Finally, the codon optimization, In-silico cloning and immune simulation profile was found to be satisfactory. Overall, the designed vaccine candidate has a potential against variant of SARS-Cov-2. However, further experimental studies are required to confirm.