Evidence map›Paper›PMID 42871528›Full record

ReviewRSC advances2026

BamA as a next-generation antibacterial target: mechanistic insights, inhibitor landscape, and rational drug design strategies.

Ahmed A Al-Karmalawy, Arwa Omar Al Khatib, Samia S Hawas

Abstract readReview
In one paragraph

Review in RSC advances, 2026. 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

3 authors.

Ahmed A Al-KarmalawyDepartment of Pharmaceutical Chemistry, Faculty of Pharmacy, Horus University-Egypt New Damietta 34518 Egypt akarmalawy@horus.edu.eg.ORCID https://orcid.org/0000-0002-8173-6073
Arwa Omar Al KhatibFaculty of Pharmacy, Al-Ahliyya Amman University Amman Jordan.
Samia S HawasDepartment of Pharmaceutical Chemistry, Faculty of Pharmacy, Horus University-Egypt New Damietta 34518 Egypt akarmalawy@horus.edu.eg.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid emergence of antimicrobial resistance (AMR) among Gram-negative pathogens has intensified the need for novel therapeutic strategies targeting previously underexploited bacterial systems. The β-barrel assembly machinery (BAM) complex, and particularly its central component BamA, has emerged as a highly promising antibacterial target due to its essential role in outer membrane protein (OMP) biogenesis and its accessibility at the bacterial surface. This review provides a comprehensive analysis of BamA structure, function, and mechanism, with emphasis on the dynamic lateral gate and β-augmentation processes that drive OMP folding and insertion. Recent advances in structural biology have enabled detailed characterization of BamA conformational states, offering critical insights into its druggability. We further present an integrated overview of the current BamA inhibitor landscape, including macrocyclic peptides, peptidomimetics, and small molecules, highlighting key structure-activity relationships (SAR) and binding modes. In addition, mechanisms of resistance, challenges associated with outer membrane (OM) permeability, and pharmacokinetic limitations are critically discussed. Particular attention is given to emerging design strategies that integrate conformational targeting, β-strand mimicry, and permeability optimization. Collectively, this review underscores the potential of BamA as a next-generation antibacterial target and outlines future directions for the development of effective therapeutics against multidrug-resistant Gram-negative bacteria.

Identifiers

PMID42871528
PMCPMC13659652

What OpenQuestion holds

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Registered trials

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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.