Evidence map›Paper›PMID 25482377›Full record

ArticleScientific reports2014

A tool set to map allosteric networks through the NMR chemical shift covariance analysis.

Stephen Boulton, Madoka Akimoto, Rajeevan Selvaratnam, Amir Bashiri, Giuseppe Melacini

Abstract read
In one paragraph

Article in Scientific reports, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing 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

41 citing papers in PubMed.

  1. Article
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  4. Virus-Glycan Interactions Studied by Solute NMR.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
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  6. Review
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  10. Article
  11. The dynamic nature of the Mre11-Rad50 DNA break repair complex.Progress in biophysics and molecular biology · 2021
    Review
  12. Article
  13. Article
  14. Article
  15. Mechanism of allosteric inhibition in theThe Journal of biological chemistry · 2020
    Article
  16. Integrated Computational Approaches and Tools forAllosteric Drug Discovery.International journal of molecular sciences · 2020
    Review
  17. Review
  18. Article
  19. Article
  20. 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.

Stephen BoultonDepartments of Biochemistry and Biomedical Sciences, McMaster University, 1280 Main Street West, Hamilton, Ontario, L8S 4M1, Canada.
Madoka AkimotoChemistry and Chemical Biology, McMaster University, 1280 Main Street West, Hamilton, Ontario, L8S 4M1, Canada.
Rajeevan SelvaratnamChemistry and Chemical Biology, McMaster University, 1280 Main Street West, Hamilton, Ontario, L8S 4M1, Canada.
Amir BashiriChemistry and Chemical Biology, McMaster University, 1280 Main Street West, Hamilton, Ontario, L8S 4M1, Canada.
Giuseppe Melacini1] Departments of Biochemistry and Biomedical Sciences, McMaster University, 1280 Main Street West, Hamilton, Ontario, L8S 4M1, Canada [2] Chemistry and Chemical Biology, McMaster University, 1280 Main Street West, Hamilton, Ontario, L8S 4M1, Canada.

Funding

Canadian Institutes of Health Research MOP-68897
6 · The paper itself

Abstract

Allostery is an essential regulatory mechanism of biological function. Allosteric sites are also pharmacologically relevant as they are often targeted with higher selectivity than orthosteric sites. However, a comprehensive map of allosteric sites poses experimental challenges because allostery is driven not only by structural changes, but also by modulations in dynamics that typically remain elusive to classical structure determination methods. An avenue to overcome these challenges is provided by the NMR chemical shift covariance analysis (CHESCA), as chemical shifts are exquisitely sensitive to redistributions in dynamic conformational ensembles. Here, we propose a set of complementary CHESCA algorithms designed to reliably detect allosteric networks with minimal occurrences of false positives or negatives. The proposed CHESCA toolset was tested for two allosteric proteins (PKA and EPAC) and is expected to complement traditional comparative structural analyses in the comprehensive identification of functionally relevant allosteric sites, including those in otherwise elusive partially unstructured regions.

Indexed as

Allosteric RegulationAllosteric SiteAlgorithmsModels, MolecularMolecular ConformationNuclear Magnetic Resonance, BiomolecularReproducibility of Results

Identifiers

PMID25482377
PMCPMC4258684

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.