Computational development of multi-epitope vaccine to induce adaptive immunity against multi-drug resistant Prevotella intermedia

Prevotella intermedia is a gram-negative, anaerobic, multidrug-resistant bacterium known to cause oral infections. Given its clinical significance as an opportunistic pathogen, developing effective preventive and therapeutic measures is crucial. This study employed an integrated approach, combining subtractive proteomics and immunoinformatics, to identify novel therapeutic targets. We analyzed the core genome of P. intermedia, revealing five essential proteins as potential drug targets and three as potential candidates for a vaccine. The selected vaccine candidate proteins underwent additional evaluation to determine their immunogenic epitopes (B-cell, MHC-I, and MHC-II) and the design multi-epitope vaccine incorporating suitable linkers and adjuvants. Structural validation, including the identification of globular regions and post-translational modifications (PTMs), was performed. Molecular docking with the TLR4 receptor demonstrated strong interactions, and molecular dynamics (MD) simulations, dynamic cross-correlation matrix (DCCM) analysis, binding free energy calculations, and principal component analysis (PCA) confirmed stable binding between the vaccine prototypes and TLR4. Among the four proposed vaccines, we identified HBHA-PiMEV, L7/12-PiMEV, and GMCSF-PiMEV as most effective, with sustained interactions to human immune receptors and docking scores of -1110·2cal/mol, -1016·1 kcal/mol, and -1149·6 kcal/mol, as well as 15, 27, and 16 hydrogen bonds respectively. Based on different evaluation parameters, HBHA-PiMEV was identified as the most effective vaccine construct. Additionally, the novel drug targets were annotated for their roles in key biological processes, underscoring their therapeutic value. In summary, our investigation identified novel therapeutic targets and designed potent vaccine constructs against P. intermedia for further experimental validation to combat this multidrug-resistant pathogen.

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Journal
BMC Infectious Diseases
Published
2025-11-28
DOI
https://doi.org/10.1186/s12879-025-12105-9
Primary Topic
vaccines and immunoinformatics approaches
Type
article
Field-Weighted Citation Impact
0.00

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article

Computational development of multi-epitope vaccine to induce adaptive immunity against multi-drug resistant Prevotella intermedia

Suvash Chandra Ojha, Alanoud T. Aljasham, Sonia Younas, Ayesha Kanwal et al.
BMC Infectious Diseases
vaccines and immunoinformatics approaches
article

Computational development of multi-epitope vaccine to induce adaptive immunity against multi-drug resistant Prevotella intermedia

Suvash Chandra Ojha, Alanoud T. Aljasham, Sonia Younas, Ayesha Kanwal, Mohibullah Shah, Muhammad Umer Khan, Muhammad A. Latif, Hira Anum
article en

Abstract

Prevotella intermedia is a gram-negative, anaerobic, multidrug-resistant bacterium known to cause oral infections. Given its clinical significance as an opportunistic pathogen, developing effective preventive and therapeutic measures is crucial. This study employed an integrated approach, combining subtractive proteomics and immunoinformatics, to identify novel therapeutic targets. We analyzed the core genome of P. intermedia, revealing five essential proteins as potential drug targets and three as potential candidates for a vaccine. The selected vaccine candidate proteins underwent additional evaluation to determine their immunogenic epitopes (B-cell, MHC-I, and MHC-II) and the design multi-epitope vaccine incorporating suitable linkers and adjuvants. Structural validation, including the identification of globular regions and post-translational modifications (PTMs), was performed. Molecular docking with the TLR4 receptor demonstrated strong interactions, and molecular dynamics (MD) simulations, dynamic cross-correlation matrix (DCCM) analysis, binding free energy calculations, and principal component analysis (PCA) confirmed stable binding between the vaccine prototypes and TLR4. Among the four proposed vaccines, we identified HBHA-PiMEV, L7/12-PiMEV, and GMCSF-PiMEV as most effective, with sustained interactions to human immune receptors and docking scores of -1110·2cal/mol, -1016·1 kcal/mol, and -1149·6 kcal/mol, as well as 15, 27, and 16 hydrogen bonds respectively. Based on different evaluation parameters, HBHA-PiMEV was identified as the most effective vaccine construct. Additionally, the novel drug targets were annotated for their roles in key biological processes, underscoring their therapeutic value. In summary, our investigation identified novel therapeutic targets and designed potent vaccine constructs against P. intermedia for further experimental validation to combat this multidrug-resistant pathogen.

BMC Infectious DiseasesVol. 25(1)
Bahauddin Zakariya University (PK), University of Lahore (PK), Universidade Federal do Ceará (BR), Hong Kong Science and Technology Parks Corporation (HK), King Saud University (SA), Affiliated Hospital of Southwest Medical University (CN), HKU-Pasteur Research Pole (HK), University of Hong Kong (HK)
King Saud University
Openalex Percentile: Top 66%
vaccines and immunoinformatics approaches
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