CoChat
Sign Up
Cited by 169Bioinformatics and Genomic NetworksGenomics and Phylogenetic StudiesComplex Network Analysis Techniques

Binding properties and evolution of homodimers in protein-protein interaction networks

Open access
Ispolatov, I.·2005·Nucleic Acids Research
DOI 10.1093/nar/gki678PMC PMC1160523
Open this paper in CoChat — free accountOpen PDF

Abstract

We demonstrate that protein-protein interaction networks in several eukaryotic organisms contain significantly more self-interacting proteins than expected if such homodimers randomly appeared in the course of the evolution. We also show that on average homodimers have twice as many interaction partners than non-self-interacting proteins. More specifically, the likelihood of a protein to physically interact with itself was found to be proportional to the total number of its binding partners. These properties of dimers are in agreement with a phenomenological model, in which individual proteins differ from each other by the degree of their 'stickiness' or general propensity toward interaction with other proteins including oneself. A duplication of self-interacting proteins creates a pair of paralogous proteins interacting with each other. We show that such pairs occur more frequently than could be explained by pure chance alone. Similar to homodimers, proteins involved in heterodimers with their paralogs on average have twice as many interacting partners than the rest of the network. The likelihood of a pair of paralogous proteins to interact with each other was also shown to decrease with their sequence similarity. This points to the conclusion that most of interactions between paralogs are inherited from ancestral homodimeric proteins, rather than established de novo after duplication. We finally discuss possible implications of our empirical observations from functional and evolutionary standpoints.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/nar/gki678

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • CNP and ATP5PO may be functionally related or operate together to mediate phenotypic features associated with UDN-P9's disease and hypomyelinating leukodystropy-20.

    “suggesting that they may be functionally related69–71 or operate together72,73 to mediate phenotypic features associated with UDN-P9’s disease and hypomyelinating leukodystropy-20”

    From Few shot learning for phenotype-driven diagnosis of patients with rare genetic diseases (2025) · cites this paper as [69]

    The Discussion proposes that interacting proteins can co-localize as functional modules, which supports the general possibility that proteins operate together. It does not discuss CNP, ATP5PO, UDN-P9, or hypomyelinating leukodystrophy-20, so it does not support the specific proposed link to those phenotypic features. (LLM, conf=0.78)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 26

  1. [1]Milligan G. Ramsay D. Pascal G. Carrillo J.J. GPCR dimerisation Life Sci. 2003 74 181 188 14607245
  2. [2]Ronnstrand L. Signal transduction via the stem cell factor receptor/c-Kit Cell Mol. Life. Sci. 2004 61 2535 2548 15526160 PMC11924424
  3. [3]Marianayagam N.J. Sunde M. Matthews J.M. The power of two: protein dimerization in biology Trends in Biochem. Sci. 2004 29 618 625 15501681
  4. [4]Simon A.M. Goodenough D.A. Diverse functions of vertebrate gap junctions Trends Cell Biol. 1998 12 477 483 9861669
  5. [5]Amoutzias G.D. Robertson D.L. Oliver S.G. Bornberg-Bauer E. Convergent evolution of gene networks by single-gene duplications in higher eukaryotes EMBO Rep. 2004 5 274 279 14968135 PMC1299007
  6. [6]Mellado M. Vila-Coro A.J. Martinez C. Rodriguez-Frade J.M. Receptor dimerization: a key step in chemokine signaling Cell Mol. Biol. 2001 47 575 582 11502066
  7. [7]Langer J.A. Cutrone E.C. Kotenko S. The Class II cytokine receptor (CRF2) family: overview and patterns of receptor–ligand interactions Cytokine Growth Factor Rev. 2004 15 33 48 14746812
  8. [8]Bochtler M. Ditzel L. Groll M. Hartmann C. Huber R. The proteasome Annu. Rev. Biophys. Biomol. Struct. 1999 28 295 317 10410804
  9. [9]Matadeen R. Patwardhan A. Gowen B. Orlova E.V. Pape T. Cuff M. Mueller F. Brimacombe R. van Heel M. The Escherichia coli large ribosomal subunit at 7.5 A resolution Structure Fold Des. 1999 7 1575 1583 10647188
  10. [10]Bentley G.A. Lewit-Bentley A. Finch J.T. Podjarny A.D. Roth M. Crystal structure of the nucleosome core particle at 16 A resolution J. Mol. Biol. 1984 176 55 75 6737479
  11. [11]Hattori T. Ohoka N. Inoue Y. Hayashi H. Onozaki K. C/EBP family transcription factors are degraded by the proteasome but stabilized by forming dimer Oncogene 2003 22 1273 1280 12618752
  12. [12]Dunbar A.Y. Kamada Y. Jenkins G.J. Lowe E.R. Billecke S.S. Osawa Y. Ubiquitination and degradation of neuronal nitric-oxide synthase in vitro: dimer stabilization protects the enzyme from proteolysis Mol. Pharmacol. 2004 66 964 969 15235101
  13. [13]Mura C. Cascio D. Sawaya M.R. Eisenberg D.S. The crystal structure of a heptameric archaeal Sm protein: implications for the eukaryotic snRNP core Proc. Natl Acad. Sci. USA 2001 98 5532 5537 11331747 PMC33247
  14. [14]Rubin I. Yarden Y. The basic biology of HER2 Ann. Oncol. 2001 12 Suppl. 1 S3 S8 11521719
  15. [15]Spirin V. Mirny L.A. Protein complexes and functional modules in molecular networks Proc. Natl Acad. Sci. USA 2003 100 12123 12128 14517352 PMC218723
  16. [16]Wagner A. How large protein interaction networks evolve Proc. R. Soc. Lond. B 2003 270 457 466 PMC1691265 12641899
  17. [17]Maslov S. Sneppen K. Specificity and stability in topology of protein networks Science 2002 296 910 913 11988575
  18. [18]Wuchty S. Oltvai Z.N. Barabasi A.-L. Evolutionary conservation of motif constituents within the yeast protein interaction network Nature Genet. 2003 35 176 179 12973352
  19. [19]Kim J. Krapivsky P.L. Kahng B. Redner S. Infinite-order percolation and giant fluctuations in a protein interaction network Phys. Rev. E. Stat Nonlin. Soft Matter Phys. 2002 66 055101 055105 12513542
  20. [21]Daraselia N. Yuryev A. Egorov S. Novichkova S. Nikitin A. Mazo I. Extracting human protein interactions from MEDLINE using a full-sentence parser Bioinformatics 2004 20 604 611 15033866
  21. [22]Giot L. Bader J.S. Brouwer C. Chaudhuri A. Kuang B. Li Y. Hao Y.L. Ooi C.E. Godwin B. Vitols E. A protein interaction map of Drosophila melanogaster Science 2003 302 1727 1736 14605208
  22. [23]Li S. Armstrong C.M. Bertin N. Ge H. Milstein S. Boxem M. Vidalain P.O. Han J.D. Chesneau A. Hao T. A map of the interactome network of the metazoan C.elegans Science 2004 303 540 543 14704431 PMC1698949
  23. [24]Ito T. Chiba T. Ozawa R. Yoshida M. Hattori M. Sakaki Y. A comprehensive two-hybrid analysis to explore the yeast protein interactome Proc. Natl Acad. Sci. USA 2001 98 4569 4574 11283351 PMC31875
  24. [25]Altschul S.F. Gish W. Miller W. Myers E.W. Lipman D.J. Basic local alignment search tool J. Mol. Biol. 1990 215 403 410 2231712
  25. [26]Thompson J.D. Higgins D.G. Gibson T.J. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice Nucleic Acids Res. 1994 22 4673 4680 7984417 PMC308517
  26. [27]Bennett M.J. Choe S. Eisenberg D. Domain swapping: entangling alliances between proteins Proc. Natl Acad. Sci. USA 1994 91 3127 3131 8159715 PMC43528

Cited by

Sorted by citations

Authors
Ispolatov, I.
Venue
Nucleic Acids Research
Publisher
Oxford University Press (OUP)
Published
2005-06-16
Volume
33
Issue
11
Pages
3629-3635
ISSN
  • 0305-1048 (ISSN-L)
  • 1362-4962
DOI
10.1093/nar/gki678
PMC
PMC1160523
OpenAlex
W2164071427
Cited by
169
References
1
Citations by year
2026: 3 · 2025: 5 · 2024: 5 · 2023: 4 · 2022: 8 · 2021: 4 · 2020: 5 · 2019: 12 · 2018: 9 · 2017: 5 · 2016: 6 · 2015: 8 · 2014: 9 · 2013: 4 · 2012: 18
FWCI
4.41
Type
journal article
Language
en
Open access
Licence
other-oa
Locations
  • Nucleic Acids Research (publishedVersion, other-oa)
  • Europe PMC (PubMed Central) (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University)
Funders
  • U.S. Department of Energy (DEAC-02-98CH10886, -AC02-98 CH 10886, DE-AC02-)
  • National Institute of General Medical Sciences (R01GM068954)
  • Brookhaven National Laboratory (AC-02-98CH10886, DE-AC02- 98CH10886)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
Keywords
protein-protein interaction network, homodimer, paralogous proteins, heterodimer, stickiness, sequence similarity, protein evolution, network topology, eukaryotic proteins
MeSH terms
Animals, Biological Evolution, Humans, Protein Binding, Dimerization, Two-Hybrid System Techniques, Multiprotein Complexes

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review