Skip to main content

A Review on Protein-Protein Interaction Network Databases

  • Conference paper
  • First Online:
Modeling, Dynamics, Optimization and Bioeconomics I

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 73))

  • 1346 Accesses

Abstract

Protein-protein interaction networks (PPI) are one of the vital resources that are available for understanding the processes in a living cell. Protein associations are studied in different perspectives, including biochemistry, quantum chemistry, molecular dynamics, metabolic or genetic/epigenetic networks and so on. There are several experimental methods designed to probe these interactions, such as co-immunoprecipitation or affinity chromatography, mass spectrometry, yeast to hybrid and so on. These experimental techniques can be further categorized into low-throughput and high-throughput methods. All these techniques are labor-intensive methods. However, there are several computational tools developed to predict the protein-protein interaction network from experiment verified protein-protein interactions. There are several complementing efforts made to centralize protein-protein interaction data through the construction of databases which play a vital role in the prediction of protein-protein interactions from sequence and structural features. These PPI databases can be grouped under general databases (contains wide variety of organisms) and specialized databases (meant for specific organism). In this paper, we attempt to provide a summary of these recent and most widely used protein-protein interactions databases. However, computational approaches developed for PPI and their performance is out of the scope of this paper.

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 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 169.99
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. Aloy, P., Russell, R.B.: InterPreTS: protein interaction prediction through tertiary structure. Bioinformatics 19(1), 161–162 (2003)

    Article  Google Scholar 

  2. Anderson, N.L., Anderson, N.G.: Proteome and proteomics: new technologies, new concepts, and new words. Electrophoresis 19(11), 1853–1861 (1998)

    Article  Google Scholar 

  3. Aranda, B., Achuthan P., Alam-Faruque, Y., Armean, I., Bridge, A., Derow, C., Feuermann, M., Ghanbarian, A.T., Kerrien, S., Khadake, J., Kerssemakers, J., Leroy, C., Menden, M., Michaut, M., Montecchi-Palazzi, L., Neuhauser, S.N., Orchard, S., Perreau, V., Roechert, B., van Eijk, K., Hermjakob, H.: The IntAct molecular interaction database in 2010. Nucleic Acids Res. 38(Database issue), D525–D531 (2010)

    Article  Google Scholar 

  4. Aytuna, A.S., Keskin, O., Gursoy, A.: Prediction of protein-protein interactions by combining structure and sequence conservation in protein interfaces. Bioinformatics 21(12), 2850–2855 (2005)

    Article  Google Scholar 

  5. Blackstock, W.P., Weir, M.P.: Proteomics: quantitative and physical mapping of cellular proteins. Trends Biotechnol. 17(3), 121–127 (1999)

    Article  Google Scholar 

  6. Bogdanove, A.J.: Protein-protein interactions in pathogen recognition by plants. Plant Mol. Biol. 50(6), 981–989 (2002)

    Article  Google Scholar 

  7. Ceol, A., Chatr Aryamontri, A., Licata, L., Peluso, D., Briganti, L., Perfetto, L., Castagnoli, L., Cesareni, G.: MINT, the molecular interaction database: 2009 update. Nucleic Acids Res. 38(Database issue), D532–D539 (2010)

    Article  Google Scholar 

  8. Chen, J.Y., Mamidipalli, S., Huan, T.: HAPPI: an online database of comprehensive human annotated and predicted protein interactions. BMC Genomics 10(Suppl 1), S16 (2009)

    Article  Google Scholar 

  9. Croft, D., O’Kelly, G., Wu, G., Haw, R., Gillespie, M., Matthews, L., Caudy, M., Garapati, P., Gopinath, G., Jassal, B., Jupe, S., Kalatskaya, I., Mahajan, S., May, B., Ndegwa, N., Schmidt, E., Shamovsky, V., Yung, C., Birney, E., Hermjakob, H., D’Eustachio, P., Stein, L.: Reactome: a database of reactions, pathways and biological processes. Nucleic Acids Res. 39(Database issue), D691–D697 (2011)

    Article  Google Scholar 

  10. Drews, J.: Drug discovery: a historical perspective. Science 287(5460), 1960–1964 (2000)

    Article  Google Scholar 

  11. Figeys, D., McBroom, L.D., Moran, M.F.: Mass spectrometry for the study of protein-protein interactions. Methods 24(3), 230–239 (2001)

    Article  Google Scholar 

  12. Hermjakob, H., D’Eustachio, P., Stein, L.: Reactome: a database of reactions, pathways and biological processes. Nucleic Acids Res. 39(Database issue), D691–D697 (2011)

    Google Scholar 

  13. Jansen, R., Yu, H., Greenbaum, D., Kluger, Y., Krogan, N.J., Chung, S., Emili, A., Snyder, M., Greenblatt, J.F., Gerstein, M.: A Bayesian networks approach for predicting protein-protein interactions from genomic data. Science 302(5644), 449–453 (2003)

    Article  Google Scholar 

  14. Keshava Prasad, T.S., Goel, R., Kandasamy, K., Keerthikumar, S., Kumar, S., Mathivanan, S., Telikicherla, D., Raju, R., Shafreen, B., Venugopal, A., Balakrishnan, L., Marimuthu, A., Banerjee, S., Somanathan, D.S., Sebastian, A., Rani, S., Ray, S., Harrys Kishore, C.J., Kanth, S., Ahmed, M., Kashyap, M.K., Mohmood, R., Ramachandra, Y.L., Krishna, V., Rahiman, B.A., Mohan, S., Ranganathan, P., Ramabadran, S., Chaerkady, R., Pandey, A.: Human protein reference database–2009 update. Nucleic Acids Res. 37(Database issue), D767–D772 (2009)

    Article  Google Scholar 

  15. Keskin, O., Ma, B., Nussinov, R.: Hot regions int protein-protein interactions: The organization and contribution of structurally conserved hot spot residues. J. Mol. Biol. 345 1281–1294 (2004)

    Article  Google Scholar 

  16. Lee, S.A., Chan, C.H., Chen, T.C., Yang, C.Y., Huangm K.C., Tsai, C.H., Lai, J.M., Wang, F.S., Kao, C.Y., Huang, C.Y.: POINeT: protein interactome with sub-network analysis and hub prioritization. BMC Bioinformatics 21(10), 114 (2009)

    Article  Google Scholar 

  17. Marcotte, E.M., Pellegrini, M., Ng H.,-L., Rice, D.W., Yeates, T.O., Eisenberg, D.: Detecting protein function and protein-protein interactions from genome sequences. Science 285(5428), 751–753 (1999)

    Google Scholar 

  18. McDowall, M.D., Scott, M. S., Barton, G.J.: PIPs: human protein-protein interaction prediction database. Nucleic Acids Res. 37(Database issue), D651–D656 (2009)

    Article  Google Scholar 

  19. Ogmen, U., Keskin, O., Aytuna, A.S., Nussinov, R., Gursoy, A.: PRISM: protein interactions by structural matching. Nucleic Acids Res. 33 (Web Server issue), W331–W336 (2005)

    Google Scholar 

  20. Paradesi, M.S.R., Caragea, D., Hsu, W.H.: Incorporating graph features for predicting protein-protein interactions. In: Li, X.-L., Ng, S.-K. (eds.) Biological Data Mining in Protein Interaction Networks. IGI Publishers, USA (2008)

    Google Scholar 

  21. Pellegrini, M., Marcotte, E.M., Thompson, M.J., Eisenberg, D., Yeates, T.O.: Assigning protein functions by comparative genome analysis: protein phylogenetic profiles. Proc. Natl. Acad. Sci. USA 96, 4285–4288 (1999)

    Article  Google Scholar 

  22. Peng, L., Weidong, Z., Yuhua, L., Feng, X., Jigang, W., Tieliu, S.: AtPID: the overall hierarchical functional protein interaction network interface and analytic platform for Arabidopsis. Nucleic Acids Res. 39(suppl 1), D1130–D1133 (2011)

    Google Scholar 

  23. Pitre, S., Alamgir, M., Green, J.R., Dumontier, M., Dehne, F., Golshani, A.: Computational methods for predicting protein-protein interactions. Adv. Biochem. Eng. Biotechnol. 110, 247–267 (2008)

    Google Scholar 

  24. Ruepp, A., Waegele, B., Lechner, M., Brauner, B., Dunger-Kaltenbach, I., Fobo, G., Frishman, G., Montrone, C., Mewes, H.W.: CORUM: the comprehensive resource of mammalian protein complexes–2009. Nucleic Acids Res. 38(Database issue), D497–D501 (2010)

    Article  Google Scholar 

  25. Salwinski, L., Miller, C.S., Smith, A.J., Pettit, F.K., Bowie, J.U., Eisenberg, D.: The database of interacting proteins: 2004 update. Nucleic Acids Res. 32(Database issue), D449–D451 (2004)

    Article  Google Scholar 

  26. Skrabanek, L., Saini, H.K., Bader, G.D., Enright, A.J.: Computational prediction of protein-protein interactions. Mol. Biotechnol. 38(1), 1–17 (2008)

    Article  Google Scholar 

  27. Stark, C., Breitkreutz, B.J., Chatr-Aryamontri, A., Boucher, L., Oughtred, R., Livstone, M.S., Nixon, J., Van Auken, K., Wang, X., Shi, X., Reguly, T., Rust, J.M., Winter, A., Dolinski, K., Tyers, M.: The BioGRID interaction database: 2011 update. Nucleic Acids Res. 39(Database issue), D698–D704 (2011)

    Article  Google Scholar 

  28. Sun, J., Xu J., Liu, Z., Liu, Q., Zhao, A., Shi, T., Li, Y.: Refined phylogenetic profiles method for predicting protein-protein interactions. Bioinformatics 21(16),3409–3415 (2005 )

    Article  Google Scholar 

  29. Szklarczyk, D., Franceschini, A., Kuhn, M., Simonovic, M., Roth, A., Minguez, P., Doerks, T., Stark, M., Muller, J., Bork, P., Jensen, L.J., von Mering, C.: The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored. Nucleic Acids Res. 39(Database issue), D561–D568 (2011)

    Article  Google Scholar 

  30. Turner, B., Razick, S., Turinsky, A.L., Vlasblom, J., Crowdy, E.K., Cho, E., Morrison, K., Donaldson, I.M.,Wodak, S.J.: iRefWeb: Interactive analysis of consolidated protein interaction data and their supporting evidence. Database. 2010: baq023 (2010)

    Google Scholar 

  31. Valencia, A., Pazos, F.: Computational methods for the prediction of protein interactions. Curr. Opin. Struct. Biol. 12(3), 368–373 (2002)

    Article  Google Scholar 

  32. Valkov E., Sharpe T., Marsh M., Greive S., Hyvnen M.: Targeting protein-protein interactions and fragment-based drug discovery. Top Curr. Chem. 317, 145–179 (2012)

    Article  Google Scholar 

  33. Vazquez, A., Flammini, A., Maritan, A., Vespignani, A.: Global protein function prediction from protein-protein interaction networks. Nat. Biotechnol. 21, 697–700 (2003)

    Article  Google Scholar 

  34. Young, K.H.: Yeast two-hybrid: so many interactions, (in) so little time …. Biol. Reprod. 58, 302–311 (1998)

    Google Scholar 

  35. Zhao, X.M., Zhang, X.W., Tang, W.H., Chen, L.: FPPI: fusarium graminearum protein-protein interaction database. J. Proteome Res. 8(10), 4714–4721 (2009)

    Article  Google Scholar 

  36. Zhou, D., He, Y.: Extracting interactions between proteins from the literature. J. Biomed. Inform. 14(2), 393–407 (2008)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chandra Sekhar Pedamallu .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Pedamallu, C.S., Ozdamar, L. (2014). A Review on Protein-Protein Interaction Network Databases. In: Pinto, A., Zilberman, D. (eds) Modeling, Dynamics, Optimization and Bioeconomics I. Springer Proceedings in Mathematics & Statistics, vol 73. Springer, Cham. https://doi.org/10.1007/978-3-319-04849-9_30

Download citation

Publish with us

Policies and ethics