Evidence map›Paper›PMID 41315981›Full record

ArticleBMC infectious diseases2025

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

Ayesha Kanwal, Mohibullah Shah, Muhammad Umer Khan, Muneeba Latif, Hira Anum, Sonia Younas, Alanoud T Aljasham, Suvash Chandra Ojha

Abstract read
In one paragraph

Article in BMC infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Ayesha Kanwal *Department of Biochemistry, Bahauddin Zakariya University, Multan, Punjab, 66000, Pakistan.
Mohibullah Shah *Department of Biochemistry, Bahauddin Zakariya University, Multan, Punjab, 66000, Pakistan. mohib@bzu.edu.pk.ORCID http://orcid.org/0000-0001-6126-7102
Muhammad Umer KhanInstitute of Molecular Biology and Biotechnology, The University of Lahore, Lahore, Pakistan.
Muneeba LatifDepartment of Biochemistry, Bahauddin Zakariya University, Multan, Punjab, 66000, Pakistan.
Hira AnumDepartment of Biochemistry, Bahauddin Zakariya University, Multan, Punjab, 66000, Pakistan.
Sonia YounasCentre for Immunology and Infection (C2i), Hong Kong Science and Technology Park, Hong Kong, China.
Alanoud T AljashamDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia.
Suvash Chandra OjhaDepartment of Infectious Diseases, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China. suvash_ojha@swmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Adaptive ImmunityBacterial VaccinesBacteroidaceae InfectionsDrug Resistance, Multiple, BacterialEpitopesPrevotella intermediaVaccine DevelopmentComputational BiologyHumansMolecular Docking SimulationMolecular Dynamics SimulationToll-Like Receptor 4Bacterial VaccinesEpitopesToll-Like Receptor 4AntibacterialBinding energyComputational vaccineGenomeImmunology

Identifiers

PMID41315981
PMCPMC12664192

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.