Evidence map›Paper›PMID 36504255›Full record

ReviewEssays in biochemistry2023

Structural mass spectrometry approaches to understand multidrug efflux systems.

Benjamin Russell Lewis, Ryan Lawrence, Dietmar Hammerschmid, Eamonn Reading

Abstract readReview
In one paragraph

Review in Essays in biochemistry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
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

4 authors.

Benjamin Russell LewisDepartment of Chemistry, King's College London, Britannia House, 7 Trinity Street, London SE1 1DB, U.K.
Ryan LawrenceDepartment of Chemistry, King's College London, Britannia House, 7 Trinity Street, London SE1 1DB, U.K.
Dietmar HammerschmidDepartment of Chemistry, King's College London, Britannia House, 7 Trinity Street, London SE1 1DB, U.K.
Eamonn ReadingDepartment of Chemistry, King's College London, Britannia House, 7 Trinity Street, London SE1 1DB, U.K.ORCID 0000-0001-8219-0052

Funding

Medical Research Council MR/S015426/1
6 · The paper itself

Abstract

Multidrug efflux pumps are ubiquitous across both eukaryotes and prokaryotes, and have major implications in antimicrobial and multidrug resistance. They reside within cellular membranes and have proven difficult to study owing to their hydrophobic character and relationship with their compositionally complex lipid environment. Advances in structural mass spectrometry (MS) techniques have made it possible to study these systems to elucidate critical information on their structure-function relationships. For example, MS techniques can report on protein structural dynamics, stoichiometry, connectivity, solvent accessibility, and binding interactions with ligands, lipids, and other proteins. This information proving powerful when used in conjunction with complementary structural biology methods and molecular dynamics (MD) simulations. In the present review, aimed at those not experts in MS techniques, we report on the current uses of MS in studying multidrug efflux systems, practical considerations to consider, and the future direction of the field. In the first section, we highlight the importance of studying multidrug efflux proteins, and introduce a range of different MS techniques and explain what information they yield. In the second section, we review recent studies that have utilised MS techniques to study and characterise a range of different multidrug efflux systems.

Indexed as

Anti-Bacterial AgentsDrug Resistance, Multiple, BacterialBiological TransportMass SpectrometryAnti-Bacterial Agentsantimicrobial resistancedrug effluxmass spectrometrymembrane proteins

Identifiers

PMID36504255
PMCPMC10070475

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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.