Development of conserved multi-epitopes based hybrid vaccine against SARS-CoV-2 variants: an immunoinformatic approach

Abstract

The world has faced unprecedented disruptions like global quarantine and the COVID-19 pandemic due to SARS-CoV-2. To combat these unsettling situations, several effective vaccines have been developed and are currently being used. However, the emergence of new variants due to the high mutation rate of SARS-CoV-2 challenges the efficacy of existing vaccines and has highlighted the need for novel vaccines that will be effective against various SARS-CoV-2 variants. In this study, we exploited the four structural proteins of SARS-CoV-2 to execute a potential multi-epitope vaccine against SARS-CoV-2 and its variants. The vaccine was designed by utilizing the antigenic, non-toxic, and non-allergenic B-cell and T-cell epitopes, which were selected from conserved regions of viral proteins. To build a vaccine construct, epitopes were connected through different linkers and an adjuvant was also attached at the start of the construct to enhance the immunogenicity and specificity of the epitopes. The vaccine construct was then screened through the aforementioned filters and it scored 0.6019 against the threshold of 0.4 on VexiJen 2.0 which validates its antigenicity. Toll-like receptors (i.e., TLR2, TLR3, TLR4, TLR5, and TLR8) and vaccine construct were docked by Cluspro 2.0, and TLR8 showed strong interaction with construct having a maximum negative binding energy of - 1577.1 kCal/mole. C-IMMSIM's immune simulations over three doses of the vaccine and iMODS' molecular dynamic simulations were executed to assess the reliability of the docked complexes. The stability of the vaccine construct was evaluated through the physicochemical analyses and the findings suggested that the manufactured vaccine is stable under a wide range of circumstances and can trigger immune responses against various SARS-CoV-2 variants (due to conserved epitopes). However, to strengthen the formulation of the vaccine and assess its safety and effectiveness, additional investigations and studies are required to support the computational data of this research at in-vitro and in-vivo levels.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-023-00156-2.

Keywords: Envelope protein; Immune simulation; Membrane protein; Molecular docking; Multi-epitope; Nucleocapsid; SARS-COV-2; Spike protein.

Fig. 1

The graphs indicating the peptide regions (Yellow) that could become the part of epitope as their score is above the threshold (0.5), while the peptide regions below the threshold (Green) are not eligible to become a part of B-cell-restricted epitopes

Fig. 2

The graph on the left and right represent the cumulative world population coverage of selected MHC-I and MHC-II epitopes respectively in correspondence to the recognized number of HLA hits

Fig. 3

Graphical representation of vaccine assembly in sequential arrangements i.e., 6 × His tag, followed by adjuvant, B-cell restricted epitopes, MHC-I restricted, MHC-II restricted epitopes and end with another 6 × His tag, and the complete amino acid sequence of the designed chimeric vaccine

Fig. 4

Secondary structure analysis of the construct: a PsiPred results showing the distribution of various elements of secondary structure throughout the chain, b Represent the SOPMA analysis for the calculation of residues in various elements (alpha helix, beta turns, coils, etc.), and c Showed the MEMSAT-SVM schematic of the vaccine construct

Fig. 5

Three-dimensional model of the vaccine construct: a Represent raw model with 78.3 residues in the most favored region, b Showed the refined model with 90.1% residues in the most favored region

Fig. 6

The Ramachandran plot (left) with 90.1% of the residues in the most favored region, 7.3% of the residues in the additional allowed region, 1.1% of the residues in the generously allowed region, and 1.6% of the residues in the disallowed region and ProSA web analysis (right) chart with − 4.8 Z-score to support the Ramachandran analysis for the validation of the 3D model

Fig. 7

The docked complexes between the vaccine construct and various TLRs (TLR2, TLR3, TLR4, TLR5, and TLR8) obtained from the ClusPro docking analysis

Fig. 8

The interacting residues between the TLR8 and vaccine construct within 5 Å, visualized by the analysis of TLR8 + Vaccine docked complex on PyMol software

Fig. 9

Graphical representation of various Normal mode Analyses (NMA) generated by iMODS for the docked complex (Vaccine + TLR8). A represents the deformability of the docked complex, B illustrates the B-factors and NMA predicted mobilities, C demonstrates the Eigenvalues plot evidences the relative modal stiffness, D displays the variance associated to the modes indicates their relative contribution to the equilibrium motions, E shows the covariance matrix indicates which parts of the macromolecule move in a correlated, uncorrelated or anti-correlated fashion, and F is representing the elastic network model illustrating the linking matrix

Fig. 10

Codon adaption/optimization results generated by JCAT for the vaccine construct, Codon Adaptation Index (CAI) was 0.97, and the GC content was 54.1% optimized for the expression system E. coli K-12 strain

Fig. 11

The cloned vector generated by SnapGene containing the vaccine sequence inserted (represented in red color) in pET28a ( +) plasmid. The vaccine was connected to the plasmid by introducing the EcoR1 (GAATTC) and BamH1 (GGATCC) adaptors (restriction sites) at the start and end of the construct respectively

Fig. 12

Immune simulation results: a The sudden rise in the production of various cytokines can be observed while the sub-graph of the straight Simpson index Danger (D) line ensures the safety of the vaccine, while b represents the production of various types of antibodies

Fig. 13

The immune simulation results, a present the production of B-cells isotypes (mm⁻³) in various forms, which are involved in the production of different antibodies (i.e., IgM, IgG1, and IgG2). Three different peaks can be seen representing three dosages of vaccine, while b represents the production B-cell population in various states (cells/mm³) including active, internalized, presenting-2, duplicating and anergic

Fig. 14

The immune simulation predictions by C-IMMSIMS, a illustrate the production of helper T-cells per state (cells/mm³), these states include Active, Duplicating, Resting, and Anergic T_H-cells, the purple peak is the highest representing the boost in the production of active helper T-cells upon inoculation, and b showed the Tc cell per state (cells/mm3), the curve of Active Cytotoxic T-cells (Purple) is rising at the start while the curve of Resting T-cells (Blue) is reducing which represents that upon inoculation the vaccine has triggered the production active T_C-cells