Evidence map›Paper›PMID 27272395›Full record

ArticleProtein science : a publication of the Protein Society2016

Network representation of protein interactions-Experimental results.

Dennis Kurzbach, Andrea G Flamm, Tomáš Sára

Abstract read
In one paragraph

Article in Protein science : a publication of the Protein Society, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Dennis KurzbachDepartement de Chimie, Ecole Normale Superieure, PSL Research University, UPMC Univ Paris 06, CNRS, Laboratoire des Biomolecules (LBM), 24 rue Lhomond, 75005, Paris, France.
Andrea G FlammDepartment for Structural and Computational Biology, University of Vienna, Campus Vienna BioCenter 5, Vienna, 1030, Austria.
Tomáš SáraDepartment for Structural and Computational Biology, University of Vienna, Campus Vienna BioCenter 5, Vienna, 1030, Austria.

Funding

Austrian Science Fund FWF P 26317
6 · The paper itself

Abstract

A graph theoretical analysis of nuclear magnetic resonance (NMR) data of six different protein interactions has been presented. The representation of the protein interaction data as a graph or network reveals that all of the studied interactions are based on a common functional concept. They all involve a single densely packed hub of functionally correlated residues that mediate the ligand binding events. This is found independent of the kind of protein (folded or unfolded) or ligand (protein, polymer or small molecule). Furthermore, the power of the graph analysis is demonstrated at the examples of the Calmodulin (CaM)/Calcium and the Cold Shock Protein A (CspA)/RNA interaction. The presented approach enables the precise determination of multiple binding sites for the respective ligand molecules.

Indexed as

Models, MolecularNuclear Magnetic Resonance, BiomolecularCalciumCalmodulinCold Shock Proteins and PeptidesHumansCalciumCalmodulinCold Shock Proteins and Peptideschemical shiftgraph theorynetwork descriptionnuclear magnetic resonanceprotein interactionsrelaxation

Identifiers

PMID27272395
PMCPMC5338234

What OpenQuestion holds

Textmetadata
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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.