Skip to main content

Topological and Dynamical Properties of Protein Interaction Networks

  • Chapter
Book cover Protein-protein Interactions and Networks

Part of the book series: Computational Biology ((COBO,volume 9))

  • 1351 Accesses

Abstract

This chapter reviews some of the recent research on topological and dynamical properties of Protein-protein Interaction (PPI) networks. In its first part we describe the set of numerical algorithms aimed at: 1) constructing a null-model random network with a desired set of low-level topological properties; 2) detection of over- or under-represented topological patterns such as degree-degree correlations between interacting nodes. In the second part of the chapter we describe a recently developed set of computational tools and analytical methods which allow one to go beyond purely topological studies of PPI networks and efficiently calculate the mass-action equilibrium of protein concentrations and its response to systematic perturbations. In particular, we explore how large (several-fold) changes in total abundance of a small number of proteins shift the equilibrium between free and bound concentrations of proteins throughout the PPI network. Our primary conclusion is that, on average, the effects of such perturbations exponentially decay with the network distance away from the perturbed node. This explains why, despite globally connected topology, individual functional modules in such networks are able to operate fairly independently. Under specific favorable conditions, realized in a significant number of paths in the yeast PPI network, concentration perturbations can selectively propagate over considerable network distances (up to four steps). Such “action-at-a-distance” requires high concentrations of heterodimers along the path as well as low free (unbound) concentration of intermediate proteins.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 119.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 159.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Uetz P, Giot L, Cagney G, Mansfield TA, Judson RS, et al. (2000) A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisiae. Nature 403:623–7.

    Article  Google Scholar 

  2. Ito T, Chiba T, Ozawa R, Yoshida M, Hattori M, Sakaki Y (2001) A comprehensive two-hybrid analysis to explore the yeast protein interactome. Proc Natl Acad Sci U S A 98:4569–74

    Article  Google Scholar 

  3. Rain JC, Selig L, De Reuse H, Battaglia V, Reverdy C, et al. (2001) The protein-protein interaction map of Helicobacter pylori. Nature 409:211–5.

    Article  Google Scholar 

  4. Giot L, Bader JS, Brouwer C, Chaudhuri A, Kuang B, et al. (2003) A protein interaction map of Drosophila melanogaster. Science 302:1727–36.

    Article  Google Scholar 

  5. Li S, Armstrong CM, Bertin N, Ge H, Milstein S, et al. (2004) A map of the interactome network of the metazoan C. elegans. Science 303:540–3.

    Article  Google Scholar 

  6. LaCount DJ, Vignali M, Chettier R, Phansalkar A, Bell R, et al. (2005) A protein interaction network of the malaria parasite Plasmodium falciparum. Nature 438:103–7.

    Article  Google Scholar 

  7. Rual JF, Venkatesan K, Hao T, Hirozane-Kishikawa T, Dricot A, et al. (2005) Towards a proteome-scale map of the human protein-protein interaction network. Nature 437:1173–8.

    Article  Google Scholar 

  8. Stelzl U, Worm U, Lalowski M, Haenig C, Brembeck FH, et al. (2005) A human protein-protein interaction network: a resource for annotating the proteome. Cell 122:957–68.

    Article  Google Scholar 

  9. Gavin AC, Bosche M, Krause R, Grandi P, Marzioch M, et al. (2002) Functional organization of the yeast proteome by systematic analysis of protein complexes. Nature 415:141–7.

    Article  Google Scholar 

  10. Ho Y, Gruhler A, Heilbut A, Bader GD, Moore L, et al. (2002) Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry. Nature 415:180–3.

    Article  Google Scholar 

  11. Rual JF, Venkatesan K, Hao T, Hirozane-Kishikawa T, Dricot A, et al. (2005) Towards a proteome-scale map of the human protein-protein interaction network. Nature 437:1173–8.

    Article  Google Scholar 

  12. Krogan NJ, Cagney G, Yu H, Zhong G, Guo X, et al. (2006) Global landscape of protein complexes in the yeast Saccharomyces cerevisiae. Nature 440:637–43.

    Article  Google Scholar 

  13. Gavin AC, Aloy P, Grandi P, Krause R, Boesche M, et al. (2006) Proteome survey reveals modularity of the yeast cell machinery. Nature 440:631–6.

    Article  Google Scholar 

  14. Barabasi AL and Albert R (1999) Emergence of scaling in random networks. Science 286:509–12.

    Article  MathSciNet  Google Scholar 

  15. Jeong H, Mason SP, Barabasi AL and Oltvai ZN (2001) Lethality and centrality in protein networks. Nature 411:41–2.

    Article  Google Scholar 

  16. Maslov S and Sneppen K (2002) Specificity and stability in topology of protein networks. Science 296:910–3.

    Article  Google Scholar 

  17. Wagner A (2001) The yeast protein interaction network evolves rapidly and contains few redundant duplicate genes. Mol Biol Evol 18:1283–92.

    Google Scholar 

  18. Spirin V and Mirny LA (2003) Protein complexes and functional modules in molecular networks. Proc Natl Acad Sci U S A 100:12123–8.

    Article  Google Scholar 

  19. Shi YY, Miller GA, Qian H, and Bomsztyk K (2006) Free-energy distribution of binary protein-protein binding suggests cross-species interactome differences. Proc Nat Acad of Sci U S A 103:11527–32.

    Article  Google Scholar 

  20. Evlampiev K and Isambert H 2006. Asymptotic Evolution of Protein-protein Interaction Networks for General Duplication-Divergence Models. Preprint q-bio.MN/0611070 at arxiv.org.

    Google Scholar 

  21. Vazquez A, Flammini A, Maritan A, and Vespignani A (2001) Modelling of protein interaction networks. Preprint cond-mat/0108043 at arxiv.org. Published in (2003) ComPlexUs 1:38.

    Google Scholar 

  22. Sole R V, Pastor-Satorras R, Smith E, and Kepler TB (2002) A model of large-scale proteome evolution, Preprint cond-mat/0207311 at arxiv.org. Published in (2002) Advances in Complex Systems 5:43.

    Google Scholar 

  23. Ispolatov I, Krapivsky PL, and Yuryev A (2005) Duplication-divergence model of protein interaction network. Phys Rev E 71:061911.

    Article  Google Scholar 

  24. Caldarelli G, Capocci A, De Los Rios P, and Munoz MA (2002) Scale-free networks from varying vertex intrinsic fitness. Phys Rev Lett 89:258702.

    Article  Google Scholar 

  25. Deeds EJ, Ashenberg O, and Shakhnovich EI (2006) A simple physical model for scaling in protein-protein interaction networks. Proc Nat Acad Sci U S A 103(2):311–6.

    Article  Google Scholar 

  26. Maslov S and Ispolatov I (2007) Propagation of large concentration changes in reversible protein-binding networks. Proc Natl Acad Sci U S A 104:13655–60.

    Article  Google Scholar 

  27. Kannan R, Tetali P, and Vempala S. (1999) Simple Markov-chain algorithms for generating bipartite graphs and tournaments. Random Structures and Algorithms 14:293–308.

    Article  MATH  MathSciNet  Google Scholar 

  28. The set of MATLAB programs can be downloaded at http://www.cmth.bnl.gov/maslov/ matlab.htm

  29. Maslov S, Sneppen K, and Zaliznyak A (2002) Pattern Detection in Complex Networks: Correlation Profile of the Internet. Preprint cond-mat/0205379 at arxiv.org; published in Physica A 333:529–540.

    Google Scholar 

  30. Watts D and Strogatz, S (1998) Collective dynamics of small world networks. Nature 293: 400–403.

    Google Scholar 

  31. Shen-Orr S, Milo R, Mangan S, and Alon U (2002) Network motifs in the transcriptional regulation of Escherichia coli. Nature Genetics, 31:64–68.

    Article  Google Scholar 

  32. Milo R, Shen-Orr S, Itzkovitz S, et al. (2002) Network motifs: simple building blocks of complex networks. Science 298:824–7.

    Article  Google Scholar 

  33. Maslov S and Sneppen K (2002) Protein interaction networks beyond artifacts. FEBS Letters 530:255–6.

    Article  Google Scholar 

  34. Maslov S, Sneppen K, Ispolatov I (2007) Spreading out of perturbations in reversible reaction networks. New Journal of Physics 9:273(11 pages).

    Article  Google Scholar 

  35. Albert R, Jeong H, and Barabasi AL (2000) Error and attack tolerance of complex networks. Nature 406:378–82.

    Article  Google Scholar 

  36. Stark C, Breitkreutz BJ, Reguly T, Boucher L, Breitkreutz A, and Tyers M (2006) BioGRID: a general repository for interaction datasets. Nucleic Acids Res 34:D535–9.

    Article  Google Scholar 

  37. Ghaemmaghami S, Huh WK, Bower K, Howson RW, Belle A, Dephoure N, O’Shea EK, and Weissman, JS (2003) Global analysis of protein expression in yeast. Nature 425:737–41.

    Article  Google Scholar 

  38. Piehler J (2005) New methodologies for measuring protein interactions in vivo and in vitro. Curr Opin in Struct Biol 15:4–14.

    Article  Google Scholar 

  39. Kumar MD and Gromiha MM (2006) PINT: Protein-protein Interactions Thermodynamic Database. Nucleic Acids Res 34:D195–8.

    Article  Google Scholar 

  40. Lancet D, Sadovsky E, and Seidemann E (1993) Probability model for molecular recognition in biological receptor repertoires: significance to the olfactory system. Proc Natl Acad Sci U S A 90(8):3715–9.

    Article  Google Scholar 

  41. Newman JRS, Ghaemmaghami S, Ihmels J, Breslow DK, Noble M, DeRisi JL, and Weissman JS (2006) Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise. Nature 441:840–6.

    Article  Google Scholar 

  42. Toroczkai Z and Bassler KE (2004) Jamming is limited in scale-free systems. Nature 428:170.

    Article  Google Scholar 

  43. vonDassow G, Meir E, Munro EM, and Odell GM (2000) The segment polarity network is a robust developmental module. Nature 406:188–92.

    Article  Google Scholar 

  44. Elowitz MB, Levine AJ, Siggia ED, and Swain PS (2002) Stochastic gene expression in a single cell. Science 297:1183.

    Article  Google Scholar 

  45. Raser JM and O’Shea EK (2005) Noise in gene expression: origins, consequences, and control. Science 309:2010–3.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sergei Maslov .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag London Limited

About this chapter

Cite this chapter

Maslov, S. (2008). Topological and Dynamical Properties of Protein Interaction Networks. In: Panchenko, A., Przytycka, T. (eds) Protein-protein Interactions and Networks. Computational Biology, vol 9. Springer, London. https://doi.org/10.1007/978-1-84800-125-1_7

Download citation

  • DOI: https://doi.org/10.1007/978-1-84800-125-1_7

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84800-124-4

  • Online ISBN: 978-1-84800-125-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics