Immunoinformatics design of multivalent epitope vaccine against monkeypox virus and its variants using membrane-bound, enveloped, and extracellular proteins as targets

Abstract

Introduction: The current monkeypox (MPX) outbreak, caused by the monkeypox virus (MPXV), has turned into a global concern, with over 59,000 infection cases and 23 deaths worldwide.

Objectives: Herein, we aimed to exploit robust immunoinformatics approach, targeting membrane-bound, enveloped, and extracellular proteins of MPXV to formulate a chimeric antigen. Such a strategy could similarly be applied for identifying immunodominant epitopes and designing multi-epitope vaccine ensembles in other pathogens responsible for chronic pathologies that are difficult to intervene against.

Methods: A reverse vaccinology pipeline was used to select 11 potential vaccine candidates, which were screened and mapped to predict immunodominant B-cell and T-cell epitopes. The finalized epitopes were merged with the aid of suitable linkers, an adjuvant (Resuscitation-promoting factor), a PADRE sequence (13 aa), and an HIV TAT sequence (11 aa) to formulate a multivalent epitope vaccine. Bioinformatics tools were employed to carry out codon adaptation and computational cloning. The tertiary structure of the chimeric vaccine construct was modeled via I-TASSER, and its interaction with Toll-like receptor 4 (TLR4) was evaluated using molecular docking and molecular dynamics simulation. C-ImmSim server was implemented to examine the immune response against the designed multi-epitope antigen.

Results and discussion: The designed chimeric vaccine construct included 21 immunodominant epitopes (six B-cell, eight cytotoxic T lymphocyte, and seven helper T-lymphocyte) and is predicted non-allergen, antigenic, soluble, with suitable physicochemical features, that can promote cross-protection among the MPXV strains. The selected epitopes indicated a wide global population coverage (93.62%). Most finalized epitopes have 70%-100% sequence similarity with the experimentally validated immune epitopes of the vaccinia virus, which can be helpful in the speedy progression of vaccine design. Lastly, molecular docking and molecular dynamics simulation computed stable and energetically favourable interaction between the putative antigen and TLR4.

Conclusion: Our results show that the multi-epitope vaccine might elicit cellular and humoral immune responses and could be a potential vaccine candidate against the MPXV infection. Further experimental testing of the proposed vaccine is warranted to validate its safety and efficacy profile.

Keywords: T-and B-cell; immunoinformatics; monkeypox; monkeypox virus; multi-epitope vaccine; multivalent epitope vaccine; reverse vaccinology.

Figure 1

Schematic representation of the research pipeline implemented in this study.to design a multi-epitope vaccine construct for the MPXV.

Figure 2

The designed vaccine’s amino acid sequence and surface accessibility. N-terminal has HIV TAT sequence attached. RpFE adjuvant sequence is highlighted in yellow color. PADRE epitope is shown in dark blue color. CTL, HTL, and B-cell epitopes are highlighted in red, green, and orange. Surface accessibility (NetSurfP - 3.0 sever) of each amino acid is shown as either exposed (E) or buried (B) residue.

Figure 3

Population coverage analysis of combined CTL and HTL epitopes worldwide and across different regions. Coverage, projected population coverage; pc90, the minimum count of epitope hits/HLA combinations recognized by 90% of the population; Average hit/HLA combination, an average count of epitope hits/HLA combinations recognized by the population.

Figure 4

In silico immune simulation of an infection challenge, comprised of a virus responding to the sequence of MPXV proteins covered by the designed putative vaccine, was simulated for 35 days. (A) Immunoglobulin response against the antigen or vaccine. The development of immunoglobulin and immunocomplexes after the immunization signifies the induction of the humoral immune response with a change towards the diverse subtypes of immunoglobulins (immunoglobulin G (IgG), being more predominant). (B) The cell count of total and memory CD4+ T-helper (TH) lymphocytes. (C) The cell count of TH lymphocytes is shown in various forms, i.e., active, duplicating (in the mitotic cycle), resting (not active), and anergic. (D) The cell count of total and memory CD8+ T-cytotoxic (TC) lymphocytes. (E) The cell count of TC lymphocytes in various forms, i.e., active, duplicating (in the mitotic cycle), resting (not active), and anergic. (F) Levels of cytokines and interleukins. D in the inset plot is a danger signal and leukocyte growth factor IL-2.

Figure 5

Molecular docking of CTL peptides (grey) and HLA class I molecules (A) Peptide LSMITMSAF attached with the binding groove of the HLA-B*15:01 (B) Peptide CINNTIALK attached with the binding groove of the HLA-A*11:01 (C) Peptide MSIMPVLTY attached with the binding groove of the HLA–B*35:01 (D) Peptide IAYRNDTSF attached with the binding groove of the HLA–B*35:01 (E) Peptide KMRDTLPAK attached with the binding groove of the HLA–A*30:01 (F) Peptide YVLSTIHIYV attached with the binding groove of the HLA-B*15:02 (G) Peptide RSANMSAPF attached with the binding groove of the HLA-B*58:01 (H) Peptide KTFAIIAIV attached with the binding groove of the HLA-A*02:06. All H-bonds are represented in dotted lines and the interacting residues of HLA class I receptor is shown in stick.

Figure 6

Molecular docking of HTL peptides and HLA class II molecules (A) Peptide LIVIIYVFKKIKMNS attached with the binding pocket of HLA-DRB1*11:01 (B) Peptide FGVYSILTSRGGITE attached with the binding pocket of HLA-DRB1*01:01 (C) Peptide VEVRYIDITNILGGV attached with the binding pocket of HLA-DRB1*04:01 (D) Peptide MNFIPIIYSKAGKIL attached with the binding pocket of HLA-DRB1*01:01 (E) Peptide SPINIETKKAISDTR attached with the binding pocket of HLA-DRB1*11:01 (F) Peptide IRDQYITALNHLVLS attached with the binding pocket of HLA-DRB1*04:01 (G) Peptide SLPYKYLQVVKQRER attached with the binding pocket of HLA-DRB1*01:01. All H-bonds are represented in dotted lines and the interacting residues of HLA class II molecule is shown in stick.

Figure 7

Optimal binding mode of the modelled vaccine (red) with TLR4 dimer (light yellow) obtained via molecular docking. Atomic interactions between the putative vaccine–TLR4 interface are shown at the top right. Hydrogen bonds are depicted in blue lines. The residue type is shown with a distinctive colour.

Figure 8

Molecular dynamics simulations study of modelled vaccine (ligand) and TLR4 (receptor) complex. (A) Root Mean Square Deviation (RMSD) plot of ligand and receptor complex present no significant displacement, indicating stable molecular interaction between two molecules. (B) Root Mean Square Fluctuation (RMSF) plot of the ligand-receptor complex representing the mobility of individual amino acid side chains. Amino acids of TLR4 goes from 1 to 1494, while that of vaccine construct starts from 1495 till the end. (C) The radius of Gyration (Rg) plot of ligand-receptor complex showing the structural compactness over 100ns timescale. (D) Solvent Accessible Surface Area (SASA) plot of ligand-receptor complex indicating changes in the surface volume of the complex over time (100ns). (E) Native and non-native contacts between the modelled vaccine–TLR4 complex over the simulation timescale.