Evidence map›Paper›PMID 19837592›Full record

ReviewTrends in biochemical sciences2009

Protein-protein interaction networks: how can a hub protein bind so many different partners?

Chung-Jung Tsai, Buyong Ma, Ruth Nussinov

Abstract readReview
In one paragraph

Review in Trends in biochemical sciences, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
72citing papers in PubMed, 1 pooled it
–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

72 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Predicting Protein-Protein Interactions from Machine-Learned Representations.Advances in experimental medicine and biology · 2026
    Review
  5. Review
  6. Article
  7. A tethering mechanism underlies Pin1-catalyzed prolineProceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Alterations in Immune-Related Defensin Alpha 4 (International journal of inflammation · 2022
    Review
  13. Review
  14. Article
  15. Article
  16. Review
  17. Review
  18. Review
  19. Article
  20. Protein ensembles link genotype to phenotype.PLoS computational biology · 2019
    Review

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

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.

Chung-Jung TsaiCenter for Cancer Research Nanobiology Program, SAIC-Frederick, Inc., NCI-Frederick, Frederick, MD 21702, USA.
Buyong Ma
Ruth Nussinov

Funding

Protein Structure, Stability, and Amyloid FormationZIABC010440 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI NUSSINOV, RUTH · 2009 to 2025
$11.8M
Biomolecular Recognition and Binding MechanismsZIABC010441 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI NUSSINOV, RUTH · 2009 to 2025
$9.4M
Protein Structure, Stability, and Amyloid FormationZ01BC010440 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI NUSSINOV, RUTH · 2002 to 2008
$1.4M
CCR NIH HHS HHSN261200800001CIntramural NIH HHS Z01 BC010440NCI NIH HHS HHSN261200800001E
6 · The paper itself

Abstract

How can a single hub protein bind so many different partners? Numerous studies have sought differences between hubs and non-hubs to explain what makes a protein a hub and how a shared hub-binding site can be promiscuous, yet at the same time be specific. Here, we suggest that the problem is largely non-existent and resides in the popular representation of protein interaction networks: protein products derived from a single gene, even if different, are clustered in maps into a single node. This leads to the impression that a single protein binds to a very large number of partners. In reality, it does not; rather, protein networks reflect the combination of multiple proteins, each with a distinct conformation.

Indexed as

Models, BiologicalProtein BindingProteinsProteins

Identifiers

PMID19837592
PMCPMC7292551

What OpenQuestion holds

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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.