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. 2022 Oct 27;14(11):2374.
doi: 10.3390/v14112374.

Immunoinformatics-Aided Design of a Peptide Based Multiepitope Vaccine Targeting Glycoproteins and Membrane Proteins against Monkeypox Virus

Nahid Akhtar  1 , Vikas Kaushik  1 , Ravneet Kaur Grewal  2 , Atif Khurshid Wani  1 , Chonticha Suwattanasophon  3 , Kiattawee Choowongkomon  3 , Romina Oliva  4 , Abdul Rajjak Shaikh  2   3 , Luigi Cavallo  5 , Mohit Chawla  5
Affiliations

Immunoinformatics-Aided Design of a Peptide Based Multiepitope Vaccine Targeting Glycoproteins and Membrane Proteins against Monkeypox Virus

Nahid Akhtar et al. Viruses. .

Abstract

Monkeypox is a self-limiting zoonotic viral disease and causes smallpox-like symptoms. The disease has a case fatality ratio of 3-6% and, recently, a multi-country outbreak of the disease has occurred. The currently available vaccines that have provided immunization against monkeypox are classified as live attenuated vaccinia virus-based vaccines, which pose challenges of safety and efficacy in chronic infections. In this study, we have used an immunoinformatics-aided design of a multi-epitope vaccine (MEV) candidate by targeting monkeypox virus (MPXV) glycoproteins and membrane proteins. From these proteins, seven epitopes (two T-helper cell epitopes, four T-cytotoxic cell epitopes and one linear B cell epitopes) were finally selected and predicted as antigenic, non-allergic, interferon-γ activating and non-toxic. These epitopes were linked to adjuvants to design a non-allergic and antigenic candidate MPXV-MEV. Further, molecular docking and molecular dynamics simulations predicted stable interactions between predicted MEV and human receptor TLR5. Finally, the immune-simulation analysis showed that the candidate MPXV-MEV could elicit a human immune response. The results obtained from these in silico experiments are promising but require further validation through additional in vivo experiments.

Keywords: epitope-based vaccine; immunoinformatics; monkeypox; monkeypox virus; orthopoxvirus; reverse vaccinology.

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Conflict of interest statement

The authors declare the following competing financial interest(s): Authors R.K.G. and A.R.S. were employed by the company STEMskills Research and Education Lab Private Limited, Faridabad, Haryana, India. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Scheme of the predicted monkeypox multi-epitope vaccine (MPXV-MEV) construct.
Figure 2
Figure 2
(A) Modeled 3D structures of (A) TLR5 and MPXY-MEV construct. Ramachandran plots and Z-scores calculated by Pro-SA webserver below the predicted structures. (B) Docked structure of MPXV-MEV and TLR5 as blue and red cartoons. The hotspot residues used for information-driven docking illustrated as spheres in green and magenta colors for the MEV construct and TLR5 receptor, respectively. Distance contact maps are also plotted, indicating the residues in contact between MPXV-MEV and the TLR5 receptor along with two representative molecular interactions between amino acid residues of TLR5 and the MPXV-MEV construct.
Figure 3
Figure 3
(A) Backbone RMSD plots of the docked complex and the individual chains of TLR5 and MPXV-MEV construct; (B) RMSF plots; (C) Hydrogen bonds analysis between TLR5 and MPXV-MEV during MD simulations; (D) Buried area of TLR5 and MPXV-MEV construct; (E) Superimposition of snapshots at every 20 ns of the TLR5 and MPXV-MEV constructs with their respective RMSD; (F) Contact maps showing inter-molecular contacts where the dots at the crossover of two amino acids have been colored in red, yellow, green and blue if any pair of atoms between two amino acids is closer than 7, 10, 13 and 16 Å.
Figure 4
Figure 4
(A) Consensus map of 1000 MD snapshots obtained from MDcons tool. The flagellin N- and C-terminal and the region of epitope/linkers on MPXV-MEV interacting with TLR5 are highlighted in blue boxes; (B) Time evolution of conserved contacts (dark blue dots as in A) between TLR5 and the MPXV-MEV.
Figure 5
Figure 5
The immune response predicted using C-IMMSIM (A) antigen count and antibody titer with specific subclass; (B) B cell; (C) CD4+ T cell; (D) CD4+ T cell population per state; (E) cytokines and interleukins.
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Grants and funding

The research carried out was supported by King Abdullah University of Science and Technology: BAS funding to L.C. R.O. would like to thank MIUR-FFABR “Fondo per il Finanziamento Attività Base di Ricerca” for funding.

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