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.

Keywords: B-cell; Docking; Immunoinformatics; Immunology; Omicron; T-cell; Vaccine.

Fig. 1

Schematic representation of final construct

Fig. 2

Population coverage for T-cell epitopes. a Binding of MHC class I molecules to the world population coverage. b Binding of MHC class II molecules to the world population coverage

Fig. 3

Ramachandran Plot a) 65.14% residues in the favored region (initial model) b) 86.62% of residues in the favored region (refined model)

Fig. 4

a The z-score of the initial model was − 4.19. b The z-score of the refined model is − 4.47

Fig. 5

Protein–protein docking top-ranked pose interaction: Participating residues from MEV are shown in yellow color

Fig. 6

Sitemap analysis study: highlighted residues lie in active sites of the TLR3 protein

Fig. 7

In-silico cloning of the final designed vaccine candidate. The vector was shown in black color, while the red color provided the gene coding

Fig. 8

Immune simulation profile. a Antigen and immunoglobulins. Antibodies are sub-divided per isotype. b B lymphocytes population per entity-state (i.e., showing counts for active, presenting on class-II, internalized the Ag, duplicating and anergic. c CD4 T-helper lymphocytes count sub-divided per entity-state (i.e., acctive, resting, anergic and duplicating). d CD8 T-cytotoxic lymphocytes count per entity-state. e Cytokines. Concentration of cytokines and interleukins. D in the inset plot is danger signal. f Natural Killer cells (total count)