Evidence map›Paper›PMID 27910948›Full record

ArticleScientific reports2016

Improved in-cell structure determination of proteins at near-physiological concentration.

Teppei Ikeya, Tomomi Hanashima, Saori Hosoya, Manato Shimazaki, Shiro Ikeda, Masaki Mishima, Peter Güntert, Yutaka Ito

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
3.8field-weighted citation impact, top 6% 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

22 citing papers in PubMed, 51 citations in OpenAlex.

  1. Article
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  6. Review
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  9. Article
  10. Visualizing Proteins in Mammalian Cells byAngewandte Chemie (International ed. in English) · 2022
    Article
  11. Review
  12. Review
  13. Article
  14. Review
  15. Article
  16. Protein Structure Determination in Living Cells.International journal of molecular sciences · 2019
    Review
  17. Review
  18. Article
  19. Review
  20. 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

8 authors at 3 institutions in 2 countries.

Teppei IkeyaDepartment of Chemistry, Graduate School of Science and Engineering, Tokyo Metropolitan University, Tokyo, 192-0397, Japan.
Tomomi HanashimaDepartment of Chemistry, Graduate School of Science and Engineering, Tokyo Metropolitan University, Tokyo, 192-0397, Japan.
Saori HosoyaDepartment of Chemistry, Graduate School of Science and Engineering, Tokyo Metropolitan University, Tokyo, 192-0397, Japan.
Manato ShimazakiDepartment of Chemistry, Graduate School of Science and Engineering, Tokyo Metropolitan University, Tokyo, 192-0397, Japan.
Shiro IkedaThe Institute of Statistical Mathematics, 10-3 Midori-cho, Tachikawa, Tokyo, 190-8562, Japan.
Masaki MishimaDepartment of Chemistry, Graduate School of Science and Engineering, Tokyo Metropolitan University, Tokyo, 192-0397, Japan.
Peter GüntertDepartment of Chemistry, Graduate School of Science and Engineering, Tokyo Metropolitan University, Tokyo, 192-0397, Japan.
Yutaka ItoDepartment of Chemistry, Graduate School of Science and Engineering, Tokyo Metropolitan University, Tokyo, 192-0397, Japan.
Tokyo Metropolitan University · JPJapan Science and Technology Agency · JPThe Institute of Statistical Mathematics · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Investigating three-dimensional (3D) structures of proteins in living cells by in-cell nuclear magnetic resonance (NMR) spectroscopy opens an avenue towards understanding the structural basis of their functions and physical properties under physiological conditions inside cells. In-cell NMR provides data at atomic resolution non-invasively, and has been used to detect protein-protein interactions, thermodynamics of protein stability, the behavior of intrinsically disordered proteins, etc. in cells. However, so far only a single de novo 3D protein structure could be determined based on data derived only from in-cell NMR. Here we introduce methods that enable in-cell NMR protein structure determination for a larger number of proteins at concentrations that approach physiological ones. The new methods comprise (1) advances in the processing of non-uniformly sampled NMR data, which reduces the measurement time for the intrinsically short-lived in-cell NMR samples, (2) automatic chemical shift assignment for obtaining an optimal resonance assignment, and (3) structure refinement with Bayesian inference, which makes it possible to calculate accurate 3D protein structures from sparse data sets of conformational restraints. As an example application we determined the structure of the B1 domain of protein G at about 250 μM concentration in living E. coli cells.

Indexed as

Bacterial ProteinsBayes TheoremCloning, MolecularEscherichia coliGene ExpressionModels, MolecularNuclear Magnetic Resonance, BiomolecularPlasmidsProtein Conformation, alpha-HelicalProtein Conformation, beta-StrandProtein Interaction Domains and MotifsReceptors, IgGRecombinant ProteinsStreptococcusThermodynamicsThermus thermophilusBacterial ProteinsReceptors, IgGRecombinant Proteins

Identifiers

PMID27910948
PMCPMC5133543
OpenAlexW2558321833

What OpenQuestion holds

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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.