Journal of Computer-Aided Molecular Design

, Volume 18, Issue 11, pp 697–708 | Cite as

Comparison of substructural epitopes in enzyme active sites using self-organizing maps

  • Katrin Kupas
  • Alfred Ultsch
  • Gerhard Klebe


This paper presents a new algorithm to compare substructural epitopes in protein binding cavities. Through the comparison of binding cavities accommodating well characterized ligands with cavities whose actual guests are yet unknown, it is possible to draw some conclusions on the required shape of a putative ligand likely to bind to the latter cavities. To detect functional relationships among proteins, their binding-site exposed physicochemical characteristics are described by assigning generic pseudocenters to the functional groups of the amino acids flanking the particular active site. The cavities are divided into small local regions of four pseudocenters having the shape of a pyramid with triangular basis. To find similar local regions, an emergent self-organizing map is used for clustering. Two local regions within the same cluster are similar and form the basis for the superpositioning of the corresponding cavities to score this match. First results show that the similarities between enzymes with the same EC number can be found correctly. Enzymes with different EC numbers are detected to have no common substructures. These results indicate the benefit of this method and motivate further studies.


data mining de novo design functional comparison of proteins self-organizing neural 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Grindley, H.M., Artymiuk, P.J., Rice, D.W., Willett, P. 1993J. Mol. Biol.,229707Google Scholar
  2. Spriggs, R.V., Artymiuk, P.J., Willett, P. 2003J. Chem. Inf. Comput. Sci.,43412Google Scholar
  3. Wallace, A.C., Laskowski, R.A., Thornton, J.M. 1996Protein Sci.,51001Google Scholar
  4. Wallace, A.C., Borkakoti, N., Thornton, J.M. 1997Protein Sci.,62308Google Scholar
  5. Russell, R.B. 1998J. Mol. Biol.,2791211Google Scholar
  6. Stark, A., Sunyaev, S., Russell, R.B. 2003J. Mol. Biol.,3261307Google Scholar
  7. Stark, A., Russell, R.B. 2003Nucleic Acids Res.,313341Google Scholar
  8. Wangikar, P.P., Tendulkar, A.V., Ramya, S., Mali, D.N., Sarawagi, S. 2003J. Mol. Biol.,326955Google Scholar
  9. Hamelryck, T. 2003Proteins,5196Google Scholar
  10. Kleywegt, G.J. 1999J. Mol. Biol.,2851887Google Scholar
  11. Bachar, O., Fischer, D., Nussinov, R., Wolfson, H. 1993Protein Eng.,6279Google Scholar
  12. Rosen, M., Lin, S.L., Wolfson, H., Nussinov, R. 1998Protein Eng.,11263Google Scholar
  13. Kinoshita, K., Nakamura, H. 2003Protein Sci.,121589Google Scholar
  14. Lehtonen, J.V., Denessiouk, K., May, A.C., Johnson, M.S. 1999Proteins,34341Google Scholar
  15. Poirrette, A.R., Artymiuk, P.J., Rice, D.W., Willett, P. 1997J. Comput.-Aided Mol. Des.,11557Google Scholar
  16. Yan, A., Gasteiger, J. 2003J. Chem. Inf. Comput. Sci.,43429Google Scholar
  17. Stahl, M., Taroni, C., Schneider, G. 2000Protein Eng.1383Google Scholar
  18. Schmitt, S., Kuhn, D., Klebe, G. 2002J. Mol. Biol.,323387Google Scholar
  19. Kohonen, T. 1982Biol. Cybernetics,4359Google Scholar
  20. Ultsch, A., Proc. Workshop on Self-organizing Maps, Kyushu, Japan, 2003, pp. 225–230.Google Scholar
  21. Ultsch, A., Proc. Conf. Soc. for Information and Classification, 1992.Google Scholar
  22. Ultsch, A. 2004U-Matrix a tool to visualize clusters in high dimensional data. Technical Report No. 36Department of Mathematics and Computer ScienceUniversity of MarburgGoogle Scholar
  23. Hendlich, M., Rippmann, F., Barnickel, G. 1997J. Mol. Graph. Model,15359Google Scholar
  24. Hendlich, M., Bergner, A., Gunther, J., Klebe, G. 2003J. Mol. Biol.326607Google Scholar
  25. Bairoch, A. 2000Nucleic Acids Res.28304Google Scholar
  26. Siemon, R., Einige Werkzeuge zum Einsatz von selbstorganisierenden Neuronalen Netzen zur Strukturanalyse von Wirkstoff-Rezeptoren. Diploma Thesis, Department of Mathematics and Computer Science, University of Marburg, 2001.Google Scholar

Copyright information

© Springer 2005

Authors and Affiliations

  1. 1.Data Bionics Research Group, Department of Computer ScienceUniversity of MarburgGermany
  2. 2.Department of Pharmaceutical ChemistryUniversity of MarburgGermany

Personalised recommendations