Applying high throughput and comprehensive immunoinformatics approaches to design a trivalent subunit vaccine for induction of immune response against emerging human coronaviruses SARS-CoV, MERS-CoV and SARS-CoV-2

Abstract

Coronaviruses (CoVs) cause diseases such as severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and coronavirus disease 2019 (COVID-19). Therefore, this study was conducted to combat major CoVs via a trivalent subunit vaccine, which was engineered by implementing sequences of spike (S) protein, nucleocapsid (N), envelope (E), membrane (M) protein, non-structural protein (nsp) 3, and nsp8 antigens. The CTL, HTL, MHC I, and IFN-γ epitopes were predicted via CTLPRED, IEDB, and IFN epitope servers, respectively. Also, to stimulate strong helper T lymphocytes (HTLs) responses, Pan HLA DR-binding epitope (PADRE) was used. Also, for boosting the immune response, β-defensin 2 was added to the construct as an adjuvant. Furthermore, TAT was applied to the vaccine to facilitate the intracellular delivery. Finally, TAT, adjuvant, PADRE, and selected epitopes were appropriately assembled. Based on the predicted epitopes, a trivalent multi-epitope vaccine with a molecular weight of 74.8 kDa was constructed. Further analyses predicted the molecule to be a strong antigen, and a non-allergenic and soluble protein. Secondary and tertiary structures were predicted. Additionally, analyses validated the stability of the proposed vaccine. Molecular docking and molecular dynamics simulation (MDS) showed binding affinity and stability of the vaccine-TLR3 complex was favorable. The predicted epitopes demonstrated a strong potential to stimulate T and B-cell mediated immune responses. Furthermore, codon optimization and in silico cloning guaranteed increased expression. In summary, investigations demonstrated that this next-generation approach might provide a new horizon for the development of a highly immunogenic vaccine against SARS-CoV, MERS-CoV, and SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Keywords: Immunoinformatics; MERS‐CoV; SARS-CoV-2; SARS‐CoV; Subunit vaccine.

Graphical abstract

Figure 1.

Flowchart summarizing the different steps of a trivalent subunit vaccine CoV design.

Figure 2.

Schematic representation of the trivalent subunit SARS-CoV vaccine construct. This vaccine construct covering of TAT sequence, β-defencin and PADRE at N-terminal that linked to HTL and CTL epitopes with appropriate linker, and terminated with His tag in C-terminal.

Figure 3.

Worldwide population coverage of selected epitopes based on (A) MHC-I and (B) MHC-II binding alleles.

Figure 4.

Analysis of RNA structures. (A) Graphical view of codon usage in the optimized gene. (B) The energy dot plot for the predicted mRNA. (C) The predicted of RNA secondary structure has no hairpin and pseudo knot at 5′site of mRNA. (D) A circle graph is one way to display base pairs of RNA structure.

Figure 5.

PSIPRED graphical results from secondary structure prediction of vaccine. The PSIPRED results indicated that constructed vaccine included 43.76% alpha helix (H), 16.93% extended strand, and 39.31% random coil.

Figure 6.

Predicted 3D structure of constructed vaccine.

Figure 7.

Validation of 3D modeled structure. (A) Ramachandran plot of the initial model showed 92%, 6.3%, and 1.5% of residues were located in favored, allowed and outlier regions, respectively. (B) In the refined model 93.7%, 4.4% and 1.2% of residues were located in favored, allowed and outlier regions, respectively.

Figure 8.

Intrinsically disorder regions. Amino acids in the input sequence were considered disordered when the red line is above the confidence score is higher than 0.5.

Figure 9.

The B-cell epitopes. (A-G) Linear and (H-L) discontinuous B cell epitopes on the 3 D structure.

Figure 10.

Disulfide engineering to improve protein stability. Two pairs of mutated residues were selected based on their energy, chi3 value, and B-factor.

Figure 11.

Docking complex of vaccine construct with TLRs. (A) The result was obtained from protein-protein docking with the help of the Hdock for TLR3, (B) TLR4, and (C) TLR8.

Figure 12.

Molecular dynamics simulation of the TLR-vaccine complex. (A) Potential progression curve of TLR3 and vaccine construct. (B) Temperature progression curve of TLR3- vaccine complex. (C) Density curve and (D) pressure progression curve of TLR3-vaccine indicating pressure fluctuation reached equilibration phase over 100 ps. (E) RMSF representation of the docked complex protein side chains. (F) RMSD representation of the docked complex protein backbone consists of TLR3as a receptor and vaccine as a ligand.

Figure 13.

In silico cloning to express final vaccine construct in E. coli. The vaccine construct gene (red) was inserted into the pET21b (+) vector (black) between Not I and Xho I restriction sites to create a recombinant vector.

Figure 14.

In silico immune simulation with the trivalent subunit vaccine. (A) Immunoglobulin production in response to antigen, (B) B-cell populations after exposure to antigen (C), The evolution of T-helper, (D) T-cytotoxic, and (E) T-regulatory cell populations per state after antigen injection. (F) Level of cytokines induced by the vaccine. The insert plot shows the IL-2 level with the Simpson index, D indicated by the dotted line.