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article · Journal of Computational Biophysics and Chemistry

Computational Design of a Multi-Epitope Vaccine against <i>Prevotella copri</i>: Molecular Dynamics and Immunoinformatics Study

Abstract

Prevotella copri is a prominent constituent of the human gastrointestinal microbiome, and its fluctuating abundance has been linked with positive and negative influences on diseases such as Parkinson’s disease and rheumatoid arthritis. Prevotella copri demonstrates flexibility against drugs. There is presently no vaccine approved by the FDA against prevotella copri, and treatment options are restricted. Hence, this research work was designed to create an in silico-based vaccine for prevotella copri.The protein sequences of two distinct strains of prevotella copri were retrieved from NCBI. The T-cell and B-cell epitopes were obtained and then analyzed for antigenicity, allergenicity, docking and simulation. The peptide comprises linear B-cell and T-cell epitopes from proteins identified as potential novel vaccine candidates. The molecular dynamics (MD) simulations and protein-protein docking results revealed that the vaccine exhibits strong and Sustained interaction with Toll-like receptor 4 (TLR4). The constructed sequence was integrated into the pET-30a (+) biological vehicle (vector) for subsequent analysis expression in E. coli through the SnapGene server. The constructed multi-epitopic vaccine candidate was assessed for its structural, physicochemical and immunological properties. The results demonstrated solubility, stability, antigenicity and nonallergenicity and showed a strong affinity for its target receptors. The in silico study represents a significant step forward in designing a vaccine that could effectively eliminate Prevotella copri globally.

Research topics

  • vaccines and immunoinformatics approaches
  • SARS-CoV-2 and COVID-19 Research
  • Microbial infections and disease research

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DOI: 10.1142/s2737416524500728

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