Evidence map›Paper›PMID 35453186›Full record

ArticleAntibiotics (Basel, Switzerland)2022

In Silico Screen Identifies a New Family of Agonists for the Bacterial Mechanosensitive Channel MscL.

Robin Wray, Paul Blount, Junmei Wang, Irene Iscla

Abstract read
In one paragraph

Article in Antibiotics (Basel, Switzerland), 2022. 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.

Robin WrayDepartment of Physiology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX 75390, USA.
Paul BlountDepartment of Physiology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX 75390, USA.ORCID 0000-0001-5259-4881
Junmei WangComputational Chemical Genomics Screening Center, Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburg, PA 15261, USA.ORCID 0000-0002-9607-8229
Irene IsclaDepartment of Physiology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX 75390, USA.

Funding

Using Small Compounds as Probes for Studying Mechanosensitive Channel GatingR01GM121780 · NIGMS · UT SOUTHWESTERN MEDICAL CENTER · PI BLOUNT, PAUL · 2017 to 2020
$1.1M
National Science Foundation 1955260NIGMS NIH HHS GM121780NIGMS NIH HHS R01 GM121780Welch Foundation I-1420
6 · The paper itself

Abstract

MscL is a highly conserved mechanosensitive channel found in the majority of bacterial species, including pathogens. It functions as a biological emergency release valve, jettisoning solutes from the cytoplasm upon acute hypoosmotic stress. It opens the largest known gated pore and has been heralded as an antibacterial target. Although there are no known endogenous ligands, small compounds have recently been shown to specifically bind to and open the channel, leading to decreased cell growth and viability. Their binding site is at the cytoplasmic/membrane and subunit interfaces of the protein, which has been recently been proposed to play an essential role in channel gating. Here, we have targeted this pocket using in silico screening, resulting in the discovery of a new family of compounds, distinct from other known MscL-specific agonists. Our findings extended the study of this functional region, the progression of MscL as a viable drug target, and demonstrated the power of in silico screening for identifying and improving the design of MscL agonists.

Indexed as

antibiotic resistancebacterial channelsbacterial drug target

Identifiers

PMID35453186
PMCPMC9030384

What OpenQuestion holds

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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.