Evidence map›Paper›PMID 36906819›Full record

ArticleProtein science : a publication of the Protein Society2023

Allosteric inhibition of TEM-1 β lactamase: Microsecond molecular dynamics simulations provide mechanistic insights.

Erich Hellemann, Amrita Nallathambi, Jacob D Durrant

Open access · hybridFull text read
In one paragraph

Article in Protein science : a publication of the Protein Society, 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
0.5field-weighted citation impact, top 46% of its field
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, 5 citations in OpenAlex.

  1. Review
  2. Review
  3. 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

3 authors at 1 institution in 1 country.

Erich HellemannDepartment of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, 15260, USA.
Amrita NallathambiDepartment of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, 15260, USA.
Jacob D DurrantDepartment of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, 15260, USA.ORCID 0000-0002-5808-4097
University of Pittsburgh · US

Funding

Advancing drug-lead and chemical-probe discovery using weighted-ensemble simulations and biophysical validationR01GM132353 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI DURRANT, JACOB D · 2019 to 2023
$1.7M
NIGMS NIH HHS R01 GM132353NIGMS NIH HHS R01GM132353
6 · The paper itself

Abstract

β-lactam antibiotics target DD-transpeptidases, enzymes that perform the last step of bacterial cell-wall synthesis. To block the antimicrobial activity of these antibiotics, bacteria have evolved lactamases that render them inert. Among these, TEM-1, a class A lactamase, has been extensively studied. In 2004, Horn et al. described a novel allosteric TEM-1 inhibitor, FTA, that binds distant from the TEM-1 orthosteric (penicillin-binding) pocket. TEM-1 has subsequently become a model for the study of allostery. In the present work, we perform molecular dynamics simulations of FTA-bound and FTA-absent TEM-1, totaling ~3 μS, that provide new insight into TEM-1 inhibition. In one of the simulations, bound FTA assumed a conformation different than that observed crystallographically. We provide evidence that the alternate pose is physiologically plausible and describe how it impacts our understanding of TEM-1 allostery.

Indexed as

beta-LactamasesMolecular Dynamics SimulationAnti-Bacterial AgentsBacteriaPenicillinsAnti-Bacterial Agentsbeta-LactamasesPenicillinsallosteryantibioticsmolecular dynamics simulationsTEM-1

Identifiers

PMID36906819
PMCPMC10044111
OpenAlexW4323971982

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read18
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.