Abstract
The knowledge of the biological function of proteins would have great impact on the identification of novel drug targets, and on finding the molecular causes of diseases. Unfortunately, the experimental determination of protein function is a very expensive and time consuming process. As a consequence, the development of computational techniques to complement and guide the experimental process is a crucial and fundamental step for biological analysis.
The final goal of the activity here presented is to provide a method that allows the identification of sites of possible protein-protein and protein-ligand interaction on the basis of the geometrical and topological structure of protein surfaces. The goal is then to discover complementary regions (that is with concave and convex segments that match each others) among different proteins. In particular, we are considering the first step of this process: the segmentation of the protein surface in protuberances and inlets through the analysis of convexity and concavity. To this end, two approaches will be described with a comparative assessment in terms of accuracy and speed of execution.
Chapter PDF
Similar content being viewed by others
References
Akutsu, T.: Protein structure alignment using dynamic programming and iterative improvement. IEICE Trans. Inf. and Syst. E78-D, 1–8 (1996)
Bock, M.E., Garutti, C., Guerra, C.: Spin image profile: a geometric descriptor for identifying and matching protein cavities. In: Proc. of CSB, San Diego (2007)
Bock, M.E., Garutti, C., Guerra, C.: Cavity detection and matching for binding site recognition. Theoretical Computer Science (2008), doi:10.1016/j.tcs.2008.08.018
Borgefors, G., Sanniti di Baja, G.: Analysing non-convex 2D and 2D patterns. Computer Vision and Image Understanding 63(1), 145–157 (1996)
Cantoni, V., Cinque, L., Guerra, C., Levialdi, S., Lombardi, L.: 2D Object recognition by multiscale tree matching. Pattern Recognition 31(10), 1443–1454 (1998)
Cantoni, V., Levialdi, S.: Contour labelling by pyramidal processing. In: Duff, M.J.B. (ed.) Intermediate-level Image Processing, ch. XI, pp. 181–190. Academic Press, New York (1986)
Coleman, R.G., Burr, M.A., Sourvaine, D.L., Cheng, A.C.: An intuitive approach to measuring protein surface curvature. Proteins: Struct. Funct. Bioinform. 61, 1068–1074 (2005)
Connolly, M.L.: Measurement of protein surface shape by solid angles. J. Mol. Graphics 4, 3–6 (1986)
Day, R., Beck, D.A., Armen, R.S., Daggett, V.: A consensus view of fold space: combining SCOP, CATH, and the Dali Domain Dictionary. Protein Sci. 12(10), 2150–2160 (2003)
Frome, A., Huber, D., Kolluri, R., Baulow, T., Malik, J.: Recognizing Objects in Range Data Using Regional Point Descriptors. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3023, pp. 224–237. Springer, Heidelberg (2004)
Gallus, G., Neurath, P.W.: Improved computer chromosome analysis incorporating preprocessing and boundary analysis. Phys. Med. Biol. 15, 435–445 (1970)
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)
Horn, B.K.P.: Extended Gaussian images. Proc. IEEE 72(12), 1671–1686 (1984)
http://www.pdb.org/ (visited, April 2009)
Jacob, F.: Evolution and tinkering. Science 196, 1161–1166 (1977)
Kabsch, W., Sander, C.: Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. Biopolymers 22(12), 2577–2637 (1983)
Kang, S.B., Ikeuchi, K.: The complex EGI: a new representation for 3-D pose determination. IEEE-T-PAMI, 707–721 (1993)
Masuya, M.: Shape Analysis of Protein Molecule and Legand-Receptor Docking Studies Using Mathematical Morphology, Doctoral Thesis, The University of Tokyo (1996)
Nicholls, A., Sharp, K.A., Honig, B.: Protein folding and association: insights from the interfacial and thermodynamic properties of hydrocarbons. Proteins 11, 281–296 (1991)
Shulman-Peleg, A., Nussinov, R., Wolfson, H.: Recognition of Functional Sites in Protein Structures. J. Mol. Biol. 339, 607–633 (2004)
Shum, H., Hebert, M., Ikeuchi, K.: On 3D shape similarity. In: Proceedings of the IEEE-CVPR 1996, pp. 526–531 (1996)
Sridharan, S., Nicholls, A., Honig, B.: A new vertex algorithm to calculate solvent accessible surface area. Biophys. J. 61, A174 (1992)
Takeshi, K.: Multi-scale Pocket Detection on Protein Surface Using 3D Image Processing Technique. IPSJ SIG 2006(99) (BIO-6), 49–56 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Cantoni, V., Gatti, R., Lombardi, L. (2009). Towards Protein Interaction Analysis through Surface Labeling. In: Foggia, P., Sansone, C., Vento, M. (eds) Image Analysis and Processing – ICIAP 2009. ICIAP 2009. Lecture Notes in Computer Science, vol 5716. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04146-4_65
Download citation
DOI: https://doi.org/10.1007/978-3-642-04146-4_65
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04145-7
Online ISBN: 978-3-642-04146-4
eBook Packages: Computer ScienceComputer Science (R0)
