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3D Protein Surface Segmentation through Mathematical Morphology

  • Virginio Cantoni
  • Riccardo Gatti
  • Luca Lombardi
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 273)

Abstract

An important research activity in proteomics is the study of geometrical and topological aspects that characterize the surfaces of proteins or ligand molecules. The functionalities and the molecular interactions of an unknown protein can be, in a first approximation, inferred by comparing her geometrical shape with that of known molecules. The aim of this paper is to identify particular features of molecular 3D surfaces in a new and efficient way by using a set of mathematical morphological operators. The obtained segments constitute pockets and protrusions. Pockets are generally the concave and deepest spots were active sites take place. The protrusions set, on the other hand, is the complementary region of the pockets and therefore, can be used by docking algorithms in the study of protein-protein and protein-ligand interactions.

Keywords

Structural biology Protein structure analysis Protein-ligand interaction Surface segmentation 

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References

  1. 1.
    Barber, C.B., Dobkin, D.P., Huhdanpaa, H.: The Quickhull Algorithm for Convex Hull. ACM Transactions on Mathematical Software 22(4), 469–483 (1996)MathSciNetzbMATHCrossRefGoogle Scholar
  2. 2.
    Binkowski, A.T., Naghibzadeh, S., Liang, J.: Castp: Computed atlas of surface topography of proteins. Nucl. Acids Res. 31(13), 3352–3355 (2003)CrossRefGoogle Scholar
  3. 3.
    Bock, M.E., Garutti, C., Guerra, C.: Effective labeling of molecular surface points for cavity detection and location of putative binding sites. In: Proc. of CSB, San Diego, vol. 6, pp. 263–744 (2007)Google Scholar
  4. 4.
    Bock, M.E., Garutti, C., Guerra, C.: Cavity detection and matching for binding site recognition. Theoretical Computer Science 408, 151–162 (2008)zbMATHCrossRefGoogle Scholar
  5. 5.
    Borgefors, G., Sanniti di Baja, G.: Analyzing Nonconvex 2D and 3D Patterns. Computer Vision and Image Understanding 63(1), 145–157 (1996)CrossRefGoogle Scholar
  6. 6.
    Brady, G.P., Stouten, P.F.W.: Fast prediction and visualization of protein binding pockets with PASS. J. Comput-Aided Mol. Des. 14, 383–401 (2000)CrossRefGoogle Scholar
  7. 7.
    Cantoni, V., Gatti, R., Lombardi, L.: Segmentation of SES for Protein Structure Analysis. In: Proc. of the 1st International Conference on Bioinformatics, Valencia, pp. 83–89 (2010)Google Scholar
  8. 8.
    Cantoni, V., Gatti, R., Lombardi, L.: Proteins Pockets Analysis and Description. In: Proc. of the 1st International Conference on Bioinformatics, Valencia, pp. 211–216 (2010)Google Scholar
  9. 9.
    Glaser, F., Rosenberg, Y., Kessel, A., Pupko, T., Bental, N.: The consurf-hssp database: the mapping of evolutionary conservation among homologs onto pdb structures. Proteins 58(3), 610–617 (2005)CrossRefGoogle Scholar
  10. 10.
    Glaser, F., Morris, R.J., Najmanovich, R.J., Laskowski, R.A., Thornton, J.M.: A Method for Localizing Ligand Binding Pockets in Protein Structures. PROTEINS: Structure, Function, and Bioinformatics 62, 479–488 (2006)CrossRefGoogle Scholar
  11. 11.
    Huang, B., Schroeder, M.: LIGSITEcsc: predicting ligand binding sites using the Connolly surface and degree of conservation. BMC Structural Biology 24, 6–19 (2006)Google Scholar
  12. 12.
    Laskowski, R.A.: Surfnet: a program for visualizing molecular surfaces, cavities and intermolecular interactions. J. Mol. Graph. 13(5), 323–330 (1995)CrossRefGoogle Scholar
  13. 13.
    Levitt, D.G., Banaszak, L.J.: Pocket: a computer graphics method for identifying and displaying protein cavities and their surrounding amino acids. J. Mol. Graph. 10(4), 229–234 (1992)CrossRefGoogle Scholar
  14. 14.
    Liang, J., Edelsbrunner, H., Woodward, C.: Anatomy of protein pockets and cavities: measurement of binding site geometry and implications for ligand design. Protein Sci. 7(9), 1884–1897 (1998)CrossRefGoogle Scholar
  15. 15.
    Serra, J.: Image analysis and mathematical morphology. Academic Press (1983)Google Scholar
  16. 16.
    Shulman-Peleg, A., Nussinov, R., Wolfson, H.: Recognition of Functional Sites in Protein Structures. J. Mol. Biol. 339, 607–633 (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Virginio Cantoni
    • 1
  • Riccardo Gatti
    • 1
  • Luca Lombardi
    • 1
  1. 1.Computer Vision Lab, Department of Computer Engineering and Systems ScienceUniversity of PaviaPaviaItaly

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