Skip to main content

Modeling Structural Protein Interaction Networks for Betweenness Analysis

  • Conference paper
  • First Online:
Information Sciences and Systems 2014

Abstract

Protein–protein interactions are usually represented as interaction networks (graphs), where the proteins are represented as nodes and the connections between the interacting proteins are shown as edges. Proteins or interactions with high betweenness are considered as key connector members of the network. The interactions of a protein are dictated by its structure. In this study, we propose a new protein interaction network model taking structures of proteins into consideration. With this model, it is possible to reveal simultaneous and mutually exclusive interactions of a protein. Effect of mutually exclusive interactions on information flow in a network is studied with weighted edge betweenness analysis and it is observed that a total of 68 % of bottlenecks found in p53 pathway network differed from bottlenecks found via regular edge betweenness analysis. The new network model favored the proteins which have regulatory roles and take part in cell cycle and molecular functions like protein binding, transcription factor binding, and kinase activity.

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 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
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. A.L. Barabási, Z.N. Oltvai, Network biology: understanding the cell’s functional organization. Nat. Rev. Genet. 5(2), 101–113 (2004)

    Article  Google Scholar 

  2. H. Yu, D. Greenbaum, H. Xin Lu, X. Zhu, M. Gerstein, Genomic analysis of essentiality within protein networks. Trends Genet. 20(6), 227–231 (2004)

    Article  Google Scholar 

  3. A.L. Barabási, R. Albert, Emergence of scaling in random networks. Science 286(5439), 509–512 (1999)

    Article  MathSciNet  Google Scholar 

  4. R. Albert, H. Jeong, A.L. Barabási, Error and attack tolerance of complex networks. Nature 406(6794), 378–382 (2000)

    Article  Google Scholar 

  5. H. Jeong, S.P. Mason, A.-L. Barabási, Z.N. Oltvai, Lethality and centrality in protein networks. Nature 411(6833), 41–42 (2001)

    Article  Google Scholar 

  6. A.X. Valente, M.E. Cusick, Yeast Protein Interactome topology provides framework for coordinated-functionality. Nucleic. Acids Res. 34(9), 2812–2819 (2006)

    Article  Google Scholar 

  7. A. Gursoy, O. Keskin, R. Nussinov, Topological properties of protein interaction networks from a structural perspective. Biochem. Soc. Trans. 36(Pt 6), 1398–1403 (2008)

    Article  Google Scholar 

  8. N. Tuncbag, G. Kar, A. Gursoy, O. Keskin, R. Nussinov, Towards inferring time dimensionality in protein–protein interaction networks by integrating structures: the p53 example. Mol. Biosyst. 5(12), 1770–1778 (2009)

    Article  Google Scholar 

  9. H.T.T. Phan, M.J.E. Stemberg, E. Gelenbe: Aligning protein-protein interaction networks using random neural networks. in: Proceedings of the Bioinformatics and Biomedicine (BIBM), 2012 IEEE International Conference on, 1–6 (2012)

    Google Scholar 

  10. H.M. Berman, J. Westbrook, Z. Feng, G. Gilliland, T.N. Bhat, H. Weissig, I.N. Shindyalov, P.E. Bourne, The protein data bank. Nucleic Acids Res. 28(1), 235–242 (2000)

    Article  Google Scholar 

  11. N. Tuncbag, A. Gursoy, R. Nussinov, O. Keskin, Predicting protein–protein interactions on a proteome scale by matching evolutionary and structural similarities at interfaces using PRISM. Nat. Protoc. 6(9), 1341–1354 (2011)

    Article  Google Scholar 

  12. K.W. Kohn, Molecular interaction map of the mammalian cell cycle control and DNA repair systems. Mol. Biol. Cell. 10(8), 2703–2734 (1999)

    Article  Google Scholar 

  13. P. Shannon, A. Markiel, O. Ozier, N.S. Baliga, J.T. Wang, D. Ramage, N. Amin, B. Schwikowski, T. Ideker, Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome. Res. 13(11), 2498–2504 (2003)

    Article  Google Scholar 

  14. H. Yu, P.M. Kim, E. Sprecher, V. Trifonov, M. Gerstein, The importance of bottlenecks in protein networks: correlation with gene essentiality and expression dynamics. PLoS Comput. Biol. 3(4), e59 (2007)

    Article  MathSciNet  Google Scholar 

  15. A.A. Hagberg, D.A. Schult, P.J. Swart: Exploring network structure, dynamics, and function using NetworkX. in: Proceedings of the 7th Python in Science Conference (SciPy2008), 11–15 (2008)

    Google Scholar 

  16. U. Brandes, On variants of shortest-path betweenness centrality and their generic computation. Social Netw. 30(2), 136–145 (2008)

    Article  MathSciNet  Google Scholar 

  17. A.L. Murphree, W.F. Benedict, Retinoblastoma: clues to human oncogenesis. Science 223(4640), 1028–1033 (1984)

    Article  Google Scholar 

  18. S. Maere, K. Heymans, M. Kuiper, BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks. Bioinformatics 21(16), 3448–3449 (2005)

    Article  Google Scholar 

  19. E.F. Pettersen, T.D. Goddard, C.C. Huang, G.S. Couch, D.M. Greenblatt, E.C. Meng, T.E. Ferrin, UCSF Chimera-a visualization system for exploratory research and analysis. J. Comput. Chem. 25(13), 1605–1612 (2004)

    Article  Google Scholar 

Download references

Acknowledgments

Deniz Demircioğlu is supported by a TÜBİTAK (The Scientific and Technological Research Council of Turkey) fellowship. This work has been partially supported by TÜBİTAK, Research Grant Number: 113E164.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Attila Gursoy .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Demircioğlu, D., Keskin, Ö., Gursoy, A. (2014). Modeling Structural Protein Interaction Networks for Betweenness Analysis. In: Czachórski, T., Gelenbe, E., Lent, R. (eds) Information Sciences and Systems 2014. Springer, Cham. https://doi.org/10.1007/978-3-319-09465-6_38

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-09465-6_38

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09464-9

  • Online ISBN: 978-3-319-09465-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics