Contriving multi-epitope vaccine ensemble for monkeypox disease using an immunoinformatics approach

Area of Science:

• Computational vaccinology
• Infectious disease research
• Immunoinformatics

Background:

• The global monkeypox (MPX) outbreak poses a significant public health threat, declared a global health emergency.
• Existing vaccine safety concerns necessitate the development of new, effective MPX prevention strategies.
• Multi-epitope vaccines offer a promising approach to address MPX infection and symptom onset.

Purpose of the Study:

• To design and computationally evaluate novel multi-epitope vaccines against the Monkeypox virus (MPXV).
• To identify and prioritize MPXV immune epitopes with favorable immunological and physicochemical properties.
• To assess the potential immunogenicity and safety profile of the designed vaccine constructs.

Main Methods:

• Bioinformatic analysis of MPXV antigens to identify CD8+ T-cell and B-cell epitopes.
• Computational construction of three multi-epitope vaccines (MPXV-1-3) with linkers and adjuvants.
• In silico structural prediction, molecular docking with Toll-like receptors (TLR2, TLR3, TLR4), molecular dynamics simulations, and immune simulations.

Main Results:

• Prioritization of 10 CD8+ T-cell and 4 B-cell epitopes based on sequence conservation and non-human homology.
• High binding affinities observed between vaccine constructs and TLRs (e.g., MPXV-1-TLR3: -99.09 kcal/mol).
• In silico immune simulation predicted robust innate, adaptive, and humoral immune responses.

Conclusions:

• The designed multi-epitope vaccine constructs (MPXV-1-3) exhibit favorable antigenic, non-allergenic, non-toxic, and physicochemical properties.
• Computational analyses suggest these constructs can effectively bind to immune receptors and elicit potent immune responses.
• These findings provide a strong foundation for the experimental development of a novel MPX vaccine.