Evidence map›Paper›PMID 19651513›Full record

ReviewTrends in cell biology2009

Scaffolds: interaction platforms for cellular signalling circuits.

András Zeke, Melinda Lukács, Wendell A Lim, Attila Reményi

Abstract readReview
In one paragraph

Review in Trends in cell biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers.

0numbers the graph read from it
0cells of the map it votes in
85citing papers in PubMed
5.5field-weighted citation impact, top 3% 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

85 citing papers in PubMed, 162 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Coenzyme Q10 and Intracellular Signalling Pathways: Clinical Relevance.International journal of molecular sciences · 2025
    Review
  5. Exploring New Bioorthogonal Catalysts: Scaffold Diversity in Catalysis for Chemical Biology.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  6. Mechanically operated signalling scaffolds.Biochemical Society transactions · 2024
    Review
  7. Article
  8. Article
  9. Review
  10. Characteristics ofInternational journal of molecular sciences · 2023
    Article
  11. Review
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. bioRxiv : the preprint server for biology · 2021
    Article

25 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 2 countries.

András ZekeDepartment of Biochemistry, Eötvös Loránd University, Pázmány Péter sétány 1/C, H-1117 Budapest, Hungary.
Melinda Lukács
Wendell A Lim
Attila Reményi
Eötvös Loránd University · HUUniversity of California, San Francisco · US

Funding

PROTEIN RECOGNITION IN SIGNAL TRANSDUCTIONR01GM055040 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LIM, WENDELL A · 1997 to 2015
$3.5M
NIGMS NIH HHS R01 GM055040Wellcome Trust
6 · The paper itself

Abstract

Scaffold proteins influence cellular signalling by binding to multiple signalling enzymes, receptors or ion channels. Although normally devoid of catalytic activity, they have a big impact on controlling the flow of signalling information. By assembling signalling proteins into complexes, they play the part of signal processing hubs. As we learn more about the way signalling components are linked into natural signalling circuits, researchers are becoming interested in building non-natural signalling pathways to test our knowledge and/or to intentionally reprogram cellular behaviour. In this review, we discuss the role of scaffold proteins as efficient tools for assembling intracellular signalling complexes, both natural and artificial.

Indexed as

Signal TransductionCellsEnzymesHumansProtein EngineeringProteinsEnzymesProteins

Identifiers

PMID19651513
PMCPMC3073007
OpenAlexW2076931029

What OpenQuestion holds

Textmetadata
LicenceTDM
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.