Extraction of Binding Sites in Proteins by Searching for Similar Local Molecular Surfaces

  • Satoshi Koizumi
  • Keisuke Imada
  • Tomonobu Ozaki
  • Takenao Ohkawa
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5265)


There is much research on the automatic extraction of new binding sites in proteins by searching for common sites in proteins with identical functions. While many binding sites consist of concave structures, it is difficult to compare such concaves directly due to the various sizes of concaves. To cope with this difficulty and to realize detailed and precise comparisons between concaves, we propose a method of searching for and comparing concaves by gradually changing the size. By experiments with enzyme proteins, we confirmed that extraction accuracy for the binding sites is improved.


Functional Site Molecular Surface Surface Data Neighboring Vertex Test Protein 
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.


  1. 1.
    Suyama, M., Ohhara, O.: Domcut: prediction of inter-domain linker regions in amino acid sequences. Bioinformatics 19(5), 673–674 (2003)CrossRefPubMedGoogle Scholar
  2. 2.
    Goto, S., Nishioka, T., Kanehisa, M.: Ligand: chemical database for enzyme reactions. Bioinformatics 14, 591–599 (1998)CrossRefPubMedGoogle Scholar
  3. 3.
    Shrestha, N.L., Kawaguchi, Y., Nakagawa, T., Ohkawa, T.: A method of filtering protein surface motifs based on similarity among local surfaces (2004)Google Scholar
  4. 4.
    Liang, J., Edelsbrunner, H., Woodward, C.: Anatomy of protein pockets and cavities: Measurement of binding site geometry and implications for ligand design. Protein Science 7, 1884–1897 (1998)CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Shrestha, N.L., Kawaguchi, Y., Ohkawa, T.: Sumomo: A protein surface motif mining module. International Journal of Computational Intelligence and Applications 4(4), 431–449 (2004)CrossRefGoogle Scholar
  6. 6.
    Stryer, L.: Biochemistry, Tokyou Kagaku DoujinGoogle Scholar
  7. 7.
    Kinoshita, K., Nakamura, H.: ef-site and pdbjviewer: database and viewer for protein functional sites. Bioinformatics 20(8), 1329–1330 (2004)CrossRefPubMedGoogle Scholar
  8. 8.
    Goldman, B.B., Wipke, W.T.: Qsd quadratic shape descriptors. 2. molecular docking using quadratic shape descriptors (qsdock). PROTEIN: Structures, Function, and Genetics 38, 79–94 (2000)CrossRefGoogle Scholar
  9. 9.
    Takagi, M., Shimoda, H.: Handbook of image analysis. Tokyo University Publication (1991)Google Scholar
  10. 10.
    Murzina, A.G., Brennera, S.E., Hubbarda, T., Chothia, C.: Scop: a structural classification of proteins database for the investigation of sequences and structures. J. Mol. Biol. 247, 536–540 (2004)Google Scholar
  11. 11.
    Sigrist, C.J.A., Cerutti, L., Hulo, N., Gattiker, A., Falquet, L., Pagnia, M., Bairoch, A., Bucher, P.: Prosite: a documented database using patterns and profiles as motif descriptors. Brief Bioinform. 3, 265–274 (2002)CrossRefPubMedGoogle Scholar
  12. 12.
    Sacan, A., Ozturk, O., Ferhatosmanoglu, H., Wang, Y.: Lfm-pro: a tool for detecting significant local structural sites in proteins. Bioinformatics 23(6), 709–716 (2007)CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Satoshi Koizumi
    • 1
  • Keisuke Imada
    • 2
  • Tomonobu Ozaki
    • 3
  • Takenao Ohkawa
    • 1
  1. 1.Graduate School of EngineeringKobe UniversityJapan
  2. 2.Graduate School of Science and TechnologyKobe UniversityJapan
  3. 3.Organization of Advanced Science and TechnologyKobe UniversityJapan

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