Evidence map›Paper›PMID 40913648›Full record

ArticleMolecular genetics and genomics : MGG2025

Computational identification of membrane proteins for vaccine design against drug-resistant Moraxella catarrhalis.

Fizza Arshad, Rania Pervaiz, Asifa Sarfraz, Hasan Ejaz, Amal Alotaibi, Riaz Ullah, Umar Nishan, Abid Ali, Muhammad Umer Khan, Mohibullah Shah

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Article in Molecular genetics and genomics : MGG, 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

10 authors.

Fizza Arshad *Department of Biochemistry, Bahauddin Zakariya University, Multan, Multan, 66000, Punjab, Pakistan.
Rania Pervaiz *Department of Biochemistry, Bahauddin Zakariya University, Multan, Multan, 66000, Punjab, Pakistan.
Asifa Sarfraz *Department of Biochemistry, Bahauddin Zakariya University, Multan, Multan, 66000, Punjab, Pakistan.
Hasan EjazDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, 72388, Sakaka, Saudi Arabia.
Amal AlotaibiDepartment of Basic Sciences, College of Medicine, Princess Nourah bint Abdulrahman University, 11671, Riyadh, Saudi Arabia.
Riaz UllahMedicinal Aromatic and Poisonous Plants Research Center, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.
Umar NishanDepartment of Chemistry, Kohat University of Science & Technology, Kohat, Pakistan.
Abid AliDepartment of Zoology, Abdul Wali Khan University, Mardan, 23200, Khyber Pakhtunkhwa, Pakistan.
Muhammad Umer KhanInstitute of Molecular Biology and Biotechnology, The University of Lahore, Lahore, Pakistan. muhammad.umer4@mlt.uol.edu.pk.ORCID http://orcid.org/0000-0001-6289-5207
Mohibullah ShahDepartment of Biochemistry, Bahauddin Zakariya University, Multan, Multan, 66000, Punjab, Pakistan. mohib@bzu.edu.pk.ORCID http://orcid.org/0000-0001-6126-7102

Funding

Deanship of Scientific Research, Princess Nourah Bint Abdulrahman University PNURSP2025R33
6 · The paper itself

Abstract

Moraxella catarrhalis is a Gram-negative diplococcus bacterium and a common respiratory pathogen, implicated in 15-20% of otitis media (OM) cases in children and chronic obstructive pulmonary disease (COPD) in adults. The rise of drug-resistant Moraxella catarrhalis has highlighted the urgent need for the potent vaccine strategies to reduce its clinical burden. Despite a mortality rate of 13%, there is no FDA-approved vaccine for this pathogen. The aim of this study was to computationally identify novel antigens and design a multi-epitope peptide-based vaccine candidate against M. catarrhalis using an immunoinformatics-driven subtractive proteomics and reverse vaccinology approaches. The core proteome of 12 M. catarrhalis genomes were analyzed, identifying 360 host non-homologous proteins. Subsequent screening revealed 30 metabolic pathway-dependent and 7 independent drug targets, along with 7 membrane and extracellular proteins as potential vaccine candidates. A prioritized protein target (WP_081569984.1) was selected for vaccine design. The predicted B-cell, MHC-I, and MHC-II epitopes were linked using adjuvants and linkers to construct four vaccine candidates (V1-V4). These constructs were assessed for physicochemical properties, allergenicity, antigenicity, secondary structures, and immune receptor interactions. As a result, V1 emerged as the most promising candidate. Molecular docking and molecular dynamics (MD) simulations evaluated the interactions of V1 with human toll-like receptors (TLR2 and TLR3). MD trajectories including RMSD, RMSF, Radius of gyration (Rg), SASA, binding free energy (MM-PBSA), PCA, free energy landscapes, and DCCM, showed a strong interaction of vaccine with the TLR recptors. Immune simulations predicted significant immune responses against the proposed vaccine. Additionally, the vaccine construct was in-silico tested in an E. coli plasmid vector (pET-28a(+) for its cloning potential. These findings highlight the potential of the proposed multi-epitope vaccine V1 as a safe and effective preventive strategy against M. catarrhalis-associated infections, and additionally laid the groundwork for future in vitro, in vivo, and clinical studies to validate its immunogenicity and protective efficacy.

Indexed as

Bacterial VaccinesMembrane ProteinsMoraxella catarrhalisMoraxellaceae InfectionsBacterial ProteinsComputational BiologyDrug Resistance, BacterialHumansMolecular Docking SimulationMolecular Dynamics SimulationToll-Like Receptor 2Vaccine DevelopmentBacterial ProteinsBacterial VaccinesMembrane ProteinsToll-Like Receptor 2AntibioticsBacterial infectionBinding energyBioinformaticsMulti-drug resistance

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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.