Evidence map›Paper›PMID 28613900›Full record

ArticleJournal of the American Chemical Society2017

Solid-State NMR Provides Evidence for Small-Amplitude Slow Domain Motions in a Multispanning Transmembrane α-Helical Protein.

Daryl Good, Charlie Pham, Jacob Jagas, Józef R Lewandowski, Vladimir Ladizhansky

Open access · hybridAbstract read
In one paragraph

Article in Journal of the American Chemical Society, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.2field-weighted citation impact, top 13% 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

18 citing papers in PubMed, 37 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Review
  8. Article
  9. Chemical reviews · 2022
    Review
  10. Article
  11. Article
  12. Solid-state NMR spectroscopy.Nature reviews. Methods primers · 2021
    Article
  13. High-sensitivity protein solid-state NMR spectroscopy.Current opinion in structural biology · 2019
    Review
  14. Article
  15. Refocusing CSA during magic angle spinning rotating-frame relaxation experiments.Journal of magnetic resonance (San Diego, Calif. : 1997) · 2018
    Article
  16. Review
  17. Article
  18. New applications of solid-state NMR in structural biology.Emerging topics in life sciences · 2018
    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

5 authors at 1 institution in 1 country.

Daryl Good
Charlie Pham
Jacob Jagas
Józef R LewandowskiDepartment of Chemistry, University of Warwick , Coventry CV4 7AL, United Kingdom.
Vladimir LadizhanskyORCID 0000-0003-1314-4014
University of Warwick · GB

Funding

Biotechnology and Biological Sciences Research Council BB/L022761/1European Research Council 639907
6 · The paper itself

Abstract

Proteins are dynamic entities and populate ensembles of conformations. Transitions between states within a conformational ensemble occur over a broad spectrum of amplitude and time scales, and are often related to biological function. Whereas solid-state NMR (SSNMR) spectroscopy has recently been used to characterize conformational ensembles of proteins in the microcrystalline states, its applications to membrane proteins remain limited. Here we use SSNMR to study conformational dynamics of a seven-helical transmembrane (TM) protein, Anabaena Sensory Rhodopsin (ASR) reconstituted in lipids. We report on site-specific measurements of the

Indexed as

Nuclear Magnetic Resonance, BiomolecularAnabaenaMolecular Dynamics SimulationProtein Conformation, alpha-HelicalSensory RhodopsinsSensory Rhodopsins

Identifiers

PMID28613900
PMCPMC5510093
OpenAlexW2625741831

What OpenQuestion holds

Textmetadata
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.