Evidence map›Paper›PMID 31128785›Full record

ArticleMethods in enzymology2019

Improved sensitivity and resolution of in-cell NMR spectra.

David S Burz, Leonard Breindel, Alexander Shekhtman

Abstract read
In one paragraph

Article in Methods in enzymology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Ligand-Based Competition Binding by Real-TimeJournal of medicinal chemistry · 2024
    Article
  9. Article
  10. Article
  11. Article
  12. 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.

David S BurzDepartment of Chemistry, University at Albany, State University of New York, Albany, NY, United States.
Leonard BreindelDepartment of Chemistry, University at Albany, State University of New York, Albany, NY, United States.
Alexander ShekhtmanDepartment of Chemistry, University at Albany, State University of New York, Albany, NY, United States. Electronic address: ashekhtman@albany.edu.

Funding

Real Time (RT) In-cell NMR technology to study protein interactions in live cellsR01GM085006 · NIGMS · STATE UNIVERSITY OF NEW YORK AT ALBANY · PI SHEKHTMAN, ALEXANDER · 2010 to 2021
$2.4M
NIGMS NIH HHS R01 GM085006
6 · The paper itself

Abstract

In-cell NMR spectroscopy is a powerful tool to study protein structures and interactions under near physiological conditions in both prokaryotic and eukaryotic living cells. The low sensitivity and resolution of in-cell NMR spectra and limited lifetime of cells over the course of an in-cell experiment have presented major hurdles to wide acceptance of the technique, limiting it to a few select systems. These issues are addressed by introducing the use of the CRINEPT pulse sequence to increase the sensitivity and resolution of in-cell NMR spectra and the use of a bioreactor to maintain cell viability for up to 24h. Application of advanced pulse sequences and bioreactor during in-cell NMR experiments will facilitate the exploration of a wide range of biological processes.

Indexed as

BioreactorsCell SurvivalDrug Evaluation, PreclinicalEquipment DesignEscherichia coliEscherichia coli ProteinsHeLa CellsHumansMicrobial ViabilityModels, MolecularNuclear Magnetic Resonance, BiomolecularProtein Interaction MappingProteinsSoftwareEscherichia coli ProteinsProteinsAntibioticsAtomic resolution structureIn-cell biochemistryIn vivo biochemistryNucleic acidsProtein-drug interactionsProtein interactionsProtein structureRibosomeRNAThioredoxin

Identifiers

PMID31128785
PMCPMC6988085

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.