Skip to main content

Integrating Web Resources to Model Protein Structure and Function

  • Chapter

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4126))

Abstract

In this paper we address computational aspects of protein structure and function, including prediction of secondary structure, folding, structure determination from Nuclear Magnetic Resonance data, modelling of protein interactions, and metabolic pathways. The subject is introduced with an overview of protein structure and chemistry and the algorithms and representations used to model protein structures. The main focus of the paper is the integration of information from sources relevant to protein structure modelling, such as structure databases and modelling servers, a task made difficult by the heterogeneity of formats, the diversity of data sources, and the sheer volume of information available, making evident the need for a standard framework for data sharing, i.e. the Semantic Web. To help solve this problem, we present tools being developed according to the concept of a Semantic Web. These include the UniProtRDF project and tools currently implemented on the Chemera molecular modelling software which can facilitate the search and application of information available from Internet servers and databases.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   49.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   63.00
Price excludes VAT (USA)
  • Compact, lightweight 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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Darby, N.J., Creighton, T.E.: Protein Structure: In Focus. Oxford University Press, Oxford (1993)

    Google Scholar 

  2. Branden, C., Tooze, J.: Introduction to Protein Structure, 2nd edn., Garland (1999)

    Google Scholar 

  3. http://www.expasy.org/sprot/

  4. Altschul, S.F., Gish, W., Miller, W., Myers, E.W., Lipman, D.J.: J. Mol. Biol. 215, 403–410 (1990)

    Google Scholar 

  5. Bairoch, A., Apweiler, R., Wu, C.H., Barker, W.C., Boeckmann, B., Ferro, S., Gasteiger, E., Huang, H., Lopez, R., Magrane, M., Martin, M.J., Natale, D.A., O’Donovan, C., Redaschi, N., Yeh, L.S.: The Universal Protein Resource (UniProt). Nucleic Acids Res. 33, D154–D159 (2005)

    Article  Google Scholar 

  6. http://www.ebi.ac.uk/GOA/

  7. Gene Ontology Consortium (2006). The Gene Ontology (GO) project in 2006. Nucleic Acids Research 34, D322–D326 (2006)

    Google Scholar 

  8. Simons, K.T., Kooperberg, C., Huang, E., Baker, D.: Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions. J. Mol. Biol. 268(1), 209–25 (1997)

    Article  Google Scholar 

  9. Krippahl, L., Barahona, P.: Propagating N-ary Rigid-Body Constraints. In: Rossi, F. (ed.) CP 2003. LNCS, vol. 2833, pp. 452–465. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  10. Krippahl, L., Barahona, P.: PSICO: Solving Protein Structures with Constraint Programming and Optimisation. Constraints 7, 317–331 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  11. Krippahl, L., Barahona, P.: Applying Constraint Programming to Rigid Body Protein Docking, Lecture Notes in Computer Science CP 2005. In: van Beek, P. (ed.) CP 2005. LNCS, vol. 3709, pp. 373–387. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  12. Krippahl, L., Moura, J.J., Palma, P.N.: Modeling Protein Complexes with BiGGER. Proteins 52(1), 19–23 (2003)

    Article  Google Scholar 

  13. Halperin, I., Ma, B., Wolfson, H., Nussinov, R.: Principles of Docking: An Overview of Search Algorithms and a Guide to Scoring Functions. PROTEINS: Structure, Function, and Genetics 47, 409–443 (2002)

    Article  Google Scholar 

  14. Lattman, E.E.: Protein-structure prediction – a special issue. Proteins: Struct., Funct., Genet. 23, 1 (1995)

    Article  Google Scholar 

  15. Bonneau, R., Strauss, C., Rohl, C., Chivian, D., Bradley, P., Malmstrom, L., Robertson, T., Baker, D.: De Novo Prediction of Three-dimensional Structures for Major Protein Families. J. Mol. Biol. 322(1), 65 (2002)

    Article  Google Scholar 

  16. Schwede, T., Kopp, J., Guex, N., Peitsch, M.C.: SWISS-MODEL: an automated protein homology-modeling server. Nucleic Acids Research 31, 3381–3385 (2003)

    Article  Google Scholar 

  17. Guex, N., Peitsch, M.C.: SWISS-MODEL and the Swiss-PdbViewer: An environment for comparative protein modelling. Electrophoresis 18, 2714–2723 (1997)

    Article  Google Scholar 

  18. Peitsch, M.C.: Protein modeling by E-mail Bio/Technology, vol.13, pp. 658–660 (1995)

    Google Scholar 

  19. http://swissmodel.expasy.org//SWISS-MODEL.html

  20. Guex, N., Peitsch, M.C.: SWISS-MODEL and the Swiss-PdbViewer: An environment for comparative protein modelling. Electrophoresis 18, 2714–2723 (1997)

    Article  Google Scholar 

  21. http://expasy3.isb-sib.ch/~ejain//rdf/

  22. http://www.ebi.ac.uk/Tools/webservices/index.html

  23. Labarga, A., et al.: Web services at EBI EMBnet. news 11(4), 18–23 (2005)

    Google Scholar 

  24. Pillai, S., Silventoinen, V., Kallio, K., Senger, M., Sobhany, S., Tate, J., Velankar, S., Golovin, A., Henrick, K., Rice, P., Stoehr, P., Lopez, R.: SOAP-based services provided by the European Bioinformatics Institute. Nucleic Acids Res. 33(1), W25–W28 (2005)

    Article  Google Scholar 

  25. Raghava, G.P.S.: APSSP2: A combination method for protein secondary structure prediction based on neural network and example based learning. CASP5. A-132 (2002)

    Google Scholar 

  26. Rost, B., Sander, C.: J. of Molecular Biology 232, 584–599 (1993)

    Google Scholar 

  27. Rost, B.: PROF: Predicting one-dimensional protein structure by profile based neural networks (unpublished, 2000)

    Google Scholar 

  28. Rost, B., Yachdav, G., Liu, J.: The Predict Protein Server. Nucleic Acids Research (Web Server issue) 32, W321–W326 (2003)

    Article  Google Scholar 

  29. http://www.rcsb.org/pdb/Welcome.do

  30. Berman, H.M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T.N., Weissig, H., Shindyalov, I.N., Bourne, P.E.: The Protein Data Bank. Nucleic Acids Research 28, 235–242 (2000)

    Article  Google Scholar 

  31. Orengo, C.A., Michie, A.D., Jones, S., Jones, D.T., Swindells, M.B., Thornton, J.M.: CATH- A Hierarchic Classification of Protein Domain Structures. Structure 5(8), 1093–1108 (1997)

    Article  Google Scholar 

  32. Pearl, F.M.G., Lee, D., Bray, J.E., Sillitoe, I., Todd, A.E., Harrison, A.P., Thornton, J.M., Orengo, C.A.: Assigning genomic sequences to CATH Nucleic Acids Research  28(1), 277–282 (2000)

    Google Scholar 

  33. http://www.biochem.ucl.ac.uk/bsm/cath/cath.html

  34. Murzin, A.G., Brenner, S.E., Hubbard, T., Chothia, C.: SCOP: a structural classification of proteins database for the investigation of sequences and structures. J. Mol. Biol. 247, 536–540 (1995)

    Google Scholar 

  35. http://scop.mrc-lmb.cam.ac.uk/scop/

  36. Bateman, A., Coin, L., Durbin, R., Finn, R., Hollich, V., Griffiths-Jones, S., Khanna, A., Marshall, M., Moxon, S., Sonnhammer, E., Studholme, D., Yeats, C., Eddy, S.: The Pfam Protein Families Database. Nucleic Acids Research Database Issue 32, D138–D141 (2004)

    Article  Google Scholar 

  37. Sonnhammer, E.L.L., Eddy, S.R., Birney, E., Bateman, A., Durbin, R.: Pfam: Multiple sequence alignments and HMM-profiles of protein domains. Nucleic Acids Research 26, 320–322 (1998)

    Article  Google Scholar 

  38. http://www.sanger.ac.uk/Software/Pfam/

  39. Finn, R.D., Marshall, M., Bateman, A.: iPfam: visualization of protein-protein interactions in PDB at domain and amino acid resolutions. Bioinformatics 21, 410–412 (2005)

    Article  Google Scholar 

  40. http://pywebsvcs.sourceforge.net/

  41. http://www.biopython.org/

  42. http://www.ruleml.org/

  43. http://rewerse.net/

  44. Berger, S., Bry, F., Bolzer, O., Furche, T., Schaffert, S., Wieser, C.: Xcerpt and visXcerpt: Twin Query Languages for the Semantic Web. In: Proc. Int. Semantic Web Conf. (2004)

    Google Scholar 

  45. Pătrânjan, P.L.: The Language XChange: A Declarative Approach to Reactivity on the Web. PhD Thesis, Institute for Informatics, University of Munich (July 2005)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Krippahl, L. (2006). Integrating Web Resources to Model Protein Structure and Function. In: Barahona, P., Bry, F., Franconi, E., Henze, N., Sattler, U. (eds) Reasoning Web. Reasoning Web 2006. Lecture Notes in Computer Science, vol 4126. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11837787_8

Download citation

  • DOI: https://doi.org/10.1007/11837787_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-38409-0

  • Online ISBN: 978-3-540-38412-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics