Searching in Protein State Space

  • Dietmar Seipel
  • Jörg Schultz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6547)


The increasing complexity of protein interaction networks makes their manual analysis infeasible. Signal transduction processes pose a specific challenge, as each protein can perform different functions, depending on its state.

Here, we present a Prolog and Xml based system which explores the protein state space. Starting with state based information about the function of single proteins, the system searches for all biologically reasonable states that can be reached from the starting point. As facts of general molecular biology have been integrated, novel reasonable states, not encoded in the starting set, can be reached. Furthermore, the influence of modifications like mutations or additions of further proteins can be explored. Thus, the system could direct experiments and allow to predict their outcome.


Logic Programming Protein Interaction Network System Biology Markup Language Computation Tree Logic Signal Transduction Process 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [Alemendros–Jiménez et al., 2007]
    Almendros–Jiménez, J.M., Becerra–Terón, A., Enciso–Baños, F.J.: Integrating xquery and Logic Programming. In: Proc. 17th International Conference on Applications of Declarative Programming and Knowledge Management (INAP 2007) and 21st Workshop on (Constraint) Logic Programming (WLP 2007), pp. 136–147 (2007)Google Scholar
  2. [Baral, 2004]
    Baral, C., Chancellor, K., Tran, N., Tran, N.L., Joy, A., Berens, M.: A knowledge based approach for representing and reasoning about signaling networks. Bioinformatics 20 (suppl. 1), i15–i22 (2004)CrossRefGoogle Scholar
  3. [Bardwell, 2005]
    Bardwell, L.: A walk–through of the yeast mating pheromone response pathway. Peptides 26(2), 339–350 (2005)CrossRefGoogle Scholar
  4. [Borie et al., 2003]
    Borie, D.C., Si, M.–S., Morris, R.E., Reitz, B.A., Changelian, P.S.: JAK3 inhibition as a new concept for immune suppression. Curr. Opin. Investig. Drugs 4(11), 1297–1303 (2003)Google Scholar
  5. [Bratko, 2001]
    Bratko, I.: prolog– Programming for Artificial Intelligence, 3rd edn. Addison-Wesley, Reading (2001)zbMATHGoogle Scholar
  6. [Clocksin & Mellish, 2003]
    Clocksin, W.F., Mellish, C.S.: Programming in prolog, 5th edn. Springer, Heidelberg (2003)CrossRefzbMATHGoogle Scholar
  7. [Consortium, 2008]
    Consortium, G.O.: The Gene Ontology project in 2008. Nucleic Acids Res. 36, D440–444 (2008)CrossRefGoogle Scholar
  8. [Dickens et al., 1997]
    Dickens, M., Rogers, J.S., Cavanagh, J., Raitano, A., Xia, Z., Halpern, J.R., Greenberg, M.E., Sawyers, C.L., Davis, R.J.: A cytoplasmic inhibitor of the JNK signal transduction pathway. Science 277(5326), 693–696 (1997)CrossRefGoogle Scholar
  9. [Duan et al., 2002]
    Duan, X.J., Xenarios, I., Eisenberg, D.: Describing biological protein interactions in terms of protein states and state transitions: the LiveDIP database. Mol. Cell Proteomics 1(2), 104–116 (2002)CrossRefGoogle Scholar
  10. [Fages et al., 2004]
    Fages, F., Soliman, S., Chabrier, N.: Modelling and querying interaction networks in the biochemical abstract machine BIOCHAM. Journal of Biological Physics and Chemistry 4, 64–73 (2004)CrossRefGoogle Scholar
  11. [Grafahrend–Belau et al., 2008]
    Grafahrend–Belau, E., Schreiber, F., Heiner, M., Sackmann, A., Junker, B.H., Grunwald, S., Speer, A., Winder, K., Koch, I.: Modularization of biochemical networks based on classification of Petri net t–invariants. BMC Bioinformatics 9, 90 (2008)CrossRefGoogle Scholar
  12. [Heinecke et al., 2009]
    Heinecke, K., Seher, A., Schmitz, W., Mueller, T.D., Sebald, W., Nickel, J.: Receptor oligomerization and beyond: a case study in bone morphogenetic proteins. Journal BMC Biology 7, 59 (2009)CrossRefGoogle Scholar
  13. [Hermjakob et al., 2004]
    Hermjakob, H., Montecchi–Palazzi, L., Bader, G., Wojcik, J., Salwinski, L., Ceol, A., Moore, S., Orchard, S., Sarkans, U., von Mering, C., Roechert, B., Poux, S., Jung, E., Mersch, H., Kersey, P., Lappe, M., Li, Y., Zeng, R., Rana, D., Nikolski, M., Husi, H., Brun, C., Shanker, K., Grant, S.G.N., Sander, C., Bork, P., Zhu, W., Pandey, A., Brazma, A., Jacq, B., Vidal, M., Sherman, D., Legrain, P., Cesareni, G., Xenarios, I., Eisenberg, D., Steipe, B., Hogue, C., Apweiler, R.: The HUPO PSI’s molecular interaction format – a community standard for the representation of protein interaction data. Nat. Biotechnology 22(2), 177–183 (2004)CrossRefGoogle Scholar
  14. [Hucka et al., 2003]
    Hucka, M., Finney, A., Sauro, H., Bolouri, H., Doyle, J., Kitano, H., Arkin, A., Bornstein, B., Bray, D., Cornish–Bowden, A., Cuellar, A., Dronov, S., Gilles, E., Ginkel, M., Gor, V., Goryanin, I., Hedley, W., Hodgman, T., Hofmeyr, J.–H., Hunter, P., Juty, N., Kasberger, J., Kremling, A., Kummer, U., NovÃĺre, N.L., Loew, L., Lucio, D., Mendes, P., Minch, E., Mjolsness, E., Nakayama, Y., Nelson, M., Nielsen, P., Sakurada, T., Schaff, J., Shapiro, B., Shimizu, T., Spence, H., Stelling, J., Takahashi, K., Tomita, M., Wagner, J., Wang, J., Forum, S.: The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics 19(4), 524–531 (2003)CrossRefGoogle Scholar
  15. [Karp, 2001]
    Karp, P.: Pathway databases: a case study in computational symbolic theories. Science 293(5537), 2040–2044 (2001)CrossRefGoogle Scholar
  16. [Keseler et al., 2009]
    Keseler, I.M., Bonavides–Martínez, C., Collado–Vides, J., Gama–Castro, S., Gunsalus, R.P., Johnson, D.A., Krummenacker, M., Nolan, L.M., Paley, S., Paulsen, I.T., Peralta–Gil, M., Santos–Zavaleta, A., Shearer, A.G., Karp, P.D.: EcoCyc: a comprehensive view of Escherichia coli biology. Nucleic Acids Research 37, D464–470 (2009)CrossRefGoogle Scholar
  17. [O’Shea et al., 2002]
    O’Shea, J.J., Gadina, M., Schreiber, R.D.: Cytokine signaling in 2002: new surprises in the Jak/Stat pathway. Cell 109 suppl., S121–131 (2002)CrossRefGoogle Scholar
  18. [Ratsch et al., 2003]
    Ratsch, E., Schultz, J., Saric, J., Lavin, P., Wittig, U., Reyle, U., Rojas, I.: Developing a protein–interactions ontology. Comparative and Functional Genomics 4, 85–89 (2003)CrossRefGoogle Scholar
  19. [Regev et al., 2001]
    Regev, A., Silverman, W., Shapiro, E.: Representation and simulation of biochemical processes using the π–calculus process algebra. In: Pacific Symposium on Biocomputing, pp. 459–470 (2001)Google Scholar
  20. [Rzhetsky et al., 2000]
    Rzhetsky, A., Koike, T., Kalachikov, S., Gomez, S., Krauthammer, M., Kaplan, S., Kra, P., Russo, J., Friedman, C.: A knowledge model for analysis and simulation of regulatory networks. Bioinformatics 16(12), 1120–1128 (2000)CrossRefGoogle Scholar
  21. [Saunders et al., 2008]
    Saunders, B., Lyon, S., Day, M., Riley, B., Chenette, E., Subramaniam, S., Vadivelu, I.: The Molecule Pages database. Nucleic Acids Research 36, D700–706 (2008)CrossRefGoogle Scholar
  22. [Schacherer et al., 2001]
    Schacherer, F., Choi, C., Götze, U., Krull, M., Pistor, S., Wingender, E.: The TRANSPATH signal transduction database: a knowledge base on signal transduction networks. Bioinformatics 17(11), 1053–1057 (2001)CrossRefGoogle Scholar
  23. [Seipel, 2002]
    Seipel, D.: Processing xml–documents in prolog. In: Proc. 17th Workshop on Logic Programming, WLP 2002 (2002)Google Scholar
  24. [Spellman et al., 2002]
    Spellman, P.T., Miller, M., Stewart, J., Troup, C., Sarkans, U., Chervitz, S., Bernhart, D., Sherlock, G., Ball, C., Lepage, M., Swiatek, M., Marks, W., Goncalves, J., Markel, S., Iordan, D., Shojatalab, M., Pizarro, A., White, J., Hubley, R., Deutsch, E., Senger, M., Aronow, B.J., Robinson, A., Bassett, D., Stoeckert, C.J., Brazma, A.: Design and implementation of microarray gene expression markup language (MAGE–ML). Genome Biology 3(9) (2002); RESEARCH0046Google Scholar
  25. [Wang & Dohlman, 2004]
    Wang, Y., Dohlman, H.G.: Pheromone signaling mechanisms in yeast: a prototypical sex machine. Science 306(5701), 1508–1509 (2004)CrossRefGoogle Scholar
  26. [Wielemaker, 2009]
    Wielemaker, J.: swi–prolog 5.0 Reference Manual and Wielemaker, J., Anjewierden, A (2009) Programming in xpce/prolog (2009),
  27. [Zheng et al., 2008]
    Zheng, S., Sheng, J., Wang, C., Wang, X., Yu, Y., Li, Y., Michie, A., Dai, J., Zhong, Y., Hao, P., Liu, L., Li, Y.: MPSQ: a web tool for protein–state searching. Bioinformatics 24, 2412–2413 (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Dietmar Seipel
    • 1
  • Jörg Schultz
    • 2
  1. 1.Department of Computer ScienceUniversity of WürzburgWürzburgGermany
  2. 2.Department of Bioinformatics, BiozentrumUniversity of WürzburgWürzburgGermany

Personalised recommendations