Evidence map›Paper›PMID 40989609›Full record

ReviewOpen veterinary journal2025

Computational modeling approach to identify potential anti-Campylobacter peptides from

Maryam Saleh Alhumaidi

Abstract readReview
In one paragraph

Review in Open veterinary journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Maryam Saleh AlhumaidiDepartment of Biology, College of Science, University of Hafr Al Batin, Hafr Al Batin, Kingdom of Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Campylobacteriosis is a common bacterial diarrheal illness frequently associated with poultry consumption and represents a significant problem for public health and the economy. The increasing drug resistance associated with Aim: This study investigated the potential of ginger-derived peptides to target key bacterial components involved in antibiotic resistance and virulence. Methods: Using computational modeling approaches for modeling ginger-derived peptides and different parameters and targeting efflux pumps (CmeABC and CmeC proteins) and beta-1,3-galactosyltransferase and Beta-1,3 galactosyltransferase (CgtE) involved in lipooligosaccharide (LOS) biosynthesis. Results: Physicochemical analysis revealed varied properties for targeting peptides. The results suggest that ginger-derived peptides, particularly AtpH-2, could interact with components of the efflux pump, disrupting bacterial membrane function and enhancing antimicrobial efficacy. Furthermore, the interaction between AtpH-2 and LOS biosynthesis enzymes suggests a possible disruption of LOS production. Conclusion: These findings indicate that ginger-derived peptides, especially AtpH-2, could synergistically weaken Campylobacter defenses by interfering with both efflux pump activity and LOS biosynthesis, offering a promising approach for developing novel antibacterial strategies against this zoonotic pathogen. Further research is warranted to elucidate the precise mechanisms of action and validate these

Indexed as

Anti-Bacterial AgentsCampylobacter jejuniLipopolysaccharidesPeptidesZingiber officinaleBacterial ProteinsComputer SimulationAnti-Bacterial AgentsBacterial Proteinslipid-linked oligosaccharidesLipopolysaccharidesPeptidesAntimicrobial peptidesComputational modelingEfflux pumpLipooligosaccharideZingiber officinaleZoonotic pathogen

Identifiers

PMID40989609
PMCPMC12451139

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.