Designing a Multi-Epitope Vaccine Against MPXV and HIV Based on an Immunoinformatic Approach.

Area of Science:

• Computational immunology
• Vaccine design
• Bioinformatics

Background:

• Monkeypox virus (MPXV) and human immunodeficiency virus (HIV) pose significant global health threats.
• Co-infection with MPXV and HIV is increasingly prevalent, necessitating novel preventive strategies.

Purpose of the Study:

• To design and computationally evaluate a multi-epitope vaccine targeting both MPXV and HIV co-infection.

Main Methods:

• Bioinformatics and immunoinformatics approaches were used to predict and select epitopes from MPXV and HIV proteins.
• Epitope selection criteria included non-allergenicity, high antigenicity, IFN-γ inducibility, and non-toxicity.
• Molecular docking, molecular dynamics simulations, and immune simulations were employed for vaccine construct evaluation.

Main Results:

• The designed vaccine construct exhibited favorable physicochemical properties, high antigenicity, and solubility.
• Stable interactions were observed between the vaccine construct and Toll-like receptors (TLR2, TLR3, TLR4).
• Immune simulations predicted a potent humoral and cell-mediated immune response.

Conclusions:

• The study presents a promising in silico vaccine candidate against MPXV and HIV co-infection.
• This work highlights the potential of computational approaches for developing innovative strategies against viral co-infections.