Immunoinformatics design of a structural proteins driven multi-epitope candidate vaccine against different SARS-CoV-2 variants based on fynomer

Abstract

The ideal vaccines for combating diseases that may emerge in the future require more than simply inactivating a few pathogenic strains. This study aims to provide a peptide-based multi-epitope vaccine effective against various severe acute respiratory syndrome coronavirus 2 strains. To design the vaccine, a library of peptides from the spike, nucleocapsid, membrane, and envelope structural proteins of various strains was prepared. Then, the final vaccine structure was optimized using the fully protected epitopes and the fynomer scaffold. Using bioinformatics tools, the antigenicity, allergenicity, toxicity, physicochemical properties, population coverage, and secondary and three-dimensional structures of the vaccine candidate were evaluated. The bioinformatic analyses confirmed the high quality of the vaccine. According to further investigations, this structure is similar to native protein and there is a stable and strong interaction between vaccine and receptors. Based on molecular dynamics simulation, structural compactness and stability in binding were also observed. In addition, the immune simulation showed that the vaccine can stimulate immune responses similar to real conditions. Finally, codon optimization and in silico cloning confirmed efficient expression in Escherichia coli. In conclusion, the fynomer-based vaccine can be considered as a new style in designing and updating vaccines to protect against coronavirus disease.

Figure 1

Schematic workflow of in silico multi-epitope vaccine design process.

Figure 2

Multiple sequence alignment (MSA) for structural proteins of 32 SARS-CoV-2 variants using ClustalW. One predicted epitope was highlighted with a black box line in the conserved region.

Figure 3

(A) Schematic Presentation of the final multi-epitope vaccine construct. (B) The secondary structural prediction of the vaccine. (C) The three-dimensional refined vaccine model is visualized to represent the helical, sheet, and loop regions. (D) Validation of the vaccine structure by ERRAT with a score of 95.5036. (E) ProSA validation of predicted structure with Z-score of −9.78 and (F) plots the residues scores to check the local model quality. (G) Analysis of the Ramachandran plot utilizing the PROCHECK server showed 94.6%, 3.5%, 0.4%, and 1.5% residues laying in favored, additional allowed, allowed, and disallowed regions, respectively.

Figure 3

(A) Schematic Presentation of the final multi-epitope vaccine construct. (B) The secondary structural prediction of the vaccine. (C) The three-dimensional refined vaccine model is visualized to represent the helical, sheet, and loop regions. (D) Validation of the vaccine structure by ERRAT with a score of 95.5036. (E) ProSA validation of predicted structure with Z-score of −9.78 and (F) plots the residues scores to check the local model quality. (G) Analysis of the Ramachandran plot utilizing the PROCHECK server showed 94.6%, 3.5%, 0.4%, and 1.5% residues laying in favored, additional allowed, allowed, and disallowed regions, respectively.

Figure 4

(A) Visualization of docking results for the vaccine-TLR2 complex. The vaccine construct is shown in gold, while TLR2 is depicted in green. (B) Magnified residues and their atoms are shown as sticks and labeled with chain, code, and number. Hydrogen bonds, salt bridges, and other interactions were represented by colored dashed lines. (C) Map of total interacting residues and bonds between the vaccine and TLR2 protein chains.

Figure 5

(A) Visualization of docking results for the vaccine-TLR4 complex. The vaccine construct is shown in gold, while TLR4 is depicted in violet. (B) Magnified residues and their atoms are shown as sticks and labeled with chain, code, and number. Hydrogen bonds, salt bridges, and other interactions were represented by colored dashed lines. (C) Map of total interacting residues and bonds between the vaccine and TLR4 protein chains.

Figure 6

(A) Visualization of docking results for the vaccine-MHC-I complex. The vaccine construct is shown in gold, while MHC-I is depicted in navy. (B) Magnified residues and their atoms are shown as sticks and labeled with chain, code, and number. Hydrogen bonds, salt bridges, and other interactions were represented by colored dashed lines. (C) Map of total interacting residues and bonds between the vaccine and MHC-I protein chains.

Figure 7

(A) Visualization of docking results for the vaccine-MHC-II complex. The vaccine construct is shown in gold, while MHC-II is depicted in gray. (B) Magnified residues and their atoms are shown as sticks and labeled with chain, code, and number. Hydrogen bonds, salt bridges, and other interactions were represented by colored dashed lines. (C) Map of total interacting residues and bonds between the vaccine and MHC-II protein chains.

Figure 8

The results of molecular dynamics simulation of vaccine for analysis of structural stability. (A) Graph showing the equilibrated temperature during energy minimization. (B) Graphical presentation of density during simulation. (C) Graph showing the pressure of the system during simulation. (D) RMSD plot of the vaccine construct indicating stability. (E) RMSF plot illustrates high fluctuations, the peak-like regions with a higher degree of flexibility. (F) The Rg plot showing the vaccine construct stays compact around its axes, supporting its stability during simulation.

Figure 9

In silico restriction cloning of the designed vaccine into the pET-28a (+) expression vector. The red bar represents the codon-optimized gene of the vaccine, and the black circle represents the vector backbone.

Figure 10

In silico simulation of immune response triggered by the designed vaccine as an antigen after three subsequent injections. (A) Antigen and subtypes of immunoglobulin levels are represented as different colored peaks. The Immunoglobulin (IgG) production represents the proliferation of primary, secondary, and tertiary immune responses after the vaccine administration. (B,C) B lymphocytes by total count and population per entity state (active, presenting, internalized, duplicating, or anergic). (D) Cytotoxic T-cell population. (E) Cytotoxic T-cell population per state. (F) Helper T-cell population. (G) Macrophages population per state. (H) Dendritic cell population per state. (I) The concentration of cytokines and interleukins is at three different stages.