Skip to main content

Towards Inferring Protein Interactions: Challenges and Solutions


Discovering interacting proteins has been an essential part of functional genomics. However, existing experimental techniques only uncover a small portion of any interactome. Furthermore, these data often have a very high false rate. By conceptualizing the interactions at domain level, we provide a more abstract representation of interactome, which also facilitates the discovery of unobserved protein-protein interactions. Although several domain-based approaches have been proposed to predict protein-protein interactions, they usually assume that domain interactions are independent on each other for the convenience of computational modeling. A new framework to predict protein interactions is proposed in this paper, where no assumption is made about domain interactions. Protein interactions may be the result of multiple domain interactions which are dependent on each other. A conjunctive norm form representation is used to capture the relationships between protein interactions and domain interactions. The problem of interaction inference is then modeled as a constraint satisfiability problem and solved via linear programing. Experimental results on a combined yeast data set have demonstrated the robustness and the accuracy of the proposed algorithm. Moreover, we also map some predicted interacting domains to three-dimensional structures of protein complexes to show the validity of our predictions.


  1. 1.

    Enright AJ, Iliopoulos I, Kyrpides NC, Ouzounis CA: Protein interaction maps for complete genomes based on gene fusion events. Nature 1999, 402(6757):86–90. 10.1038/47056

    Article  Google Scholar 

  2. 2.

    Marcotte EM, Pellegrini M, Ng H-L, Rice DW, Yeates TO, Eisenberg D: Detecting protein function and protein-protein interactions from genome sequences. Science 1999, 285(5428):751–753. 10.1126/science.285.5428.751

    Article  Google Scholar 

  3. 3.

    Bock JR, Gough DA: Predicting protein-protein interactions from primary structure. Bioinformatics 2001, 17(5):455–460. 10.1093/bioinformatics/17.5.455

    Article  Google Scholar 

  4. 4.

    Park J, Lappe M, Teichmann SA: Mapping protein family interactions: intramolecular and intermolecular protein family interaction repertories in the pdb and yeast. Journal of Molecular Biology 2001, 307: 929–938. 10.1006/jmbi.2001.4526

    Article  Google Scholar 

  5. 5.

    Pellegrini M, Marcotte EM, Thompson MJ, Eisenberg D, Yeates TO: Assigning protein fucntions by comparative genome analysis: protein phylogenetic profiles. Proceedings of the National Academy of Sciences of the United States of America 1999, 96(8):4285–4288. 10.1073/pnas.96.8.4285

    Article  Google Scholar 

  6. 6.

    Goffard N, Garcia V, Iragne F, Groppi A, de Daruvar A: Ippred: server for proteins interactions inference. Bioinformatics 2003, 19: 903–904. 10.1093/bioinformatics/btg091

    Article  Google Scholar 

  7. 7.

    Dandekar T, Snel B, Huynen M, Bork P: Conservation of gene order: a fingerprint of proteins that physically interact. Trends in Biochemical Sciences 1998, 23: 324–328. 10.1016/S0968-0004(98)01274-2

    Article  Google Scholar 

  8. 8.

    Eisen MB, Spellman PT, Brown PO, Botstein D: Cluster analysis and display of genome-wide expression patterns. Proceedings of the National Academy of Sciences of the United States of America 1998, 95: 14863–14868. 10.1073/pnas.95.25.14863

    Article  Google Scholar 

  9. 9.

    Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ: Basic local alignment search tool. Journal of Molecular Biology 1990, 215: 403–410.

    Article  Google Scholar 

  10. 10.

    Ito T, Chiba T, Ozawa R, Yoshida M, Hattori M, Sakaki Y: A comprehensive two hybrid analysis to explore the yeast protein interactome. Proceedings of the National Academy of Sciences of the United States of America 2001, 98(8):4569–4574. 10.1073/pnas.061034498

    Article  Google Scholar 

  11. 11.

    Uetz P, Giot L, Cagney G, et al.: A comprehensive analysis of protein-protein interactions in saccharomyces cerevisiae . Nature 2000, 403(6770):623–627. 10.1038/35001009

    Article  Google Scholar 

  12. 12.

    Ho Y, Gruhler A, Heilbut A, et al.: Systematic identification of protein complexes in saccharomyces cerevisiae by mass spectrometry. Nature 2002, 415: 180–183. 10.1038/415180a

    Article  Google Scholar 

  13. 13.

    Mrowka R, Patzak A, Herze H: Is there a bias in proteome research? Genome Research 2001, 11(12):1971–1973. 10.1101/gr.206701

    Article  Google Scholar 

  14. 14.

    Ito T, Tashiro K, Muta S, et al.: Toward a protein-protein interaction map of the budding yeast: a comprehensive system to examine two-hybrid interactions in all possible combinations between the yeast proteins. Proceedings of the National Academy of Sciences of the United States of America 2000, 97(3):1143–1147. 10.1073/pnas.97.3.1143

    Article  Google Scholar 

  15. 15.

    Deng M, Mehta S, Sun F, Chen T: Inferring domain-domain interactions from protein-protein interactions. Proceedings of the 6th Annual International Conference on Computational Biology (RECOMB '02), April 2002, Washington, DC, USA 117–126.

    Google Scholar 

  16. 16.

    Hayashida M, Ueda N, Akutsu T: A simple method for interring strengths of protein-protein interactions. Genome Informatics 2004, 15(1):56–68.

    Google Scholar 

  17. 17.

    Kim WK, Park J, Suh JK: Large scale statistical prediction of protein-protein interaction by potentially interacting domain (pid) pair. Genome Informatics 2002, 13: 42–50.

    Google Scholar 

  18. 18.

    Ng SK, Zhang Z, Tan SH: Integrative approach for computationally inferring protein domain interactions. Bioinformatics 2003, 19(8):923–929. 10.1093/bioinformatics/btg118

    Article  Google Scholar 

  19. 19.

    Sprinzak E, Margalit H: Correlated sequence-signatures as markers of protein-protein interaction. Journal of Molecular Biology 2001, 311(4):681–692. 10.1006/jmbi.2001.4920

    Article  Google Scholar 

  20. 20.

    Wojcik J, Schächter V: Protein-protein interaction map inference using interacting domain profile pairs. Bioinformatics 2001, 17(suppl. 1):S296–S305.

    Article  Google Scholar 

  21. 21.

    Hayashida M, Ueda N, Akutsu T: Interring strengths of protein-protein interactions from experimental data using linear programming. Bioinformatics 2003, 19(suppl. 2):ii58–ii65.

    Google Scholar 

  22. 22.

    Hazbun TR, Fields S: Networking proteins in yeast. Proceedings of the National Academy of Sciences of the United States of America 2001, 98(8):4277–4278. 10.1073/pnas.091096398

    Article  Google Scholar 

  23. 23.

    Du D, Gu J, Pardalos P: Satisfiability Problem: Theory and Application, DIMACS Series in Discrete Mathematics. Volume 35. American Mathematical Society, Providence, RI, USA; 1997.

    Book  Google Scholar 

  24. 24.

    Gramm J, Hirsch EA, Niedermeier R, Rossmanith P: New worst-case upper bounds for max-2-sat with application to maxcut. Discrete Applied Mathematics 2003, 130(2):139–155. 10.1016/S0166-218X(02)00402-X

    MathSciNet  Article  Google Scholar 

  25. 25.

    Zhang H, Shen H: Exact algorithms for maxsat. Electronic Notes in Theoretical Computer Science 2003, 86(1):1–14. 10.1016/S1571-0661(04)80648-0

    MathSciNet  Article  Google Scholar 

  26. 26.

    Hooker J: Resolution and the integrality of satisfiability problems. Mathematical Programming 1996, 74: 1–10.

    MathSciNet  MATH  Google Scholar 

  27. 27.

    Bateman A, Coin L, Durbin R, et al.: The pfam protein families database. Nucleic Acids Research 2004, 32: D138–D141. 10.1093/nar/gkh121

    Article  Google Scholar 

  28. 28.

    Mewes HW, Frishman D, Gruber C, et al.: MIPS: a database for genomes and protein sequences. Nucleic Acids Research 2000, 28(1):37–40. 10.1093/nar/28.1.37

    Article  Google Scholar 

  29. 29.

    Pawsona T, Rainaa M, Nasha P: Interaction domains: from simple binding events to complex cellular behavior. FEBS Letters 2002, 513: 2–10. 10.1016/S0014-5793(01)03292-6

    Article  Google Scholar 

Download references

Author information



Corresponding author

Correspondence to Ya Zhang.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and Permissions

About this article

Cite this article

Zhang, Y., Zha, H., Chu, CH. et al. Towards Inferring Protein Interactions: Challenges and Solutions. EURASIP J. Adv. Signal Process. 2006, 037349 (2006).

Download citation


  • Protein Interaction
  • Abstract Representation
  • Conjunctive Norm Form
  • Domain Level
  • Satisfiability Problem