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SuMo: A Tool for Protein Function Inference Based on 3D Structures Comparisons

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Part of the Focus on Structural Biology book series (FOSB, volume 8)

Abstract

The prediction of important residues for binding/recognition sites in protein 3D structures is still a matter of challenge. Indeed, binding sites recognition is generally based on geometry often combined with physico-chemical properties of the site since the conformation, size and chemical composition of the protein surface are all relevant for the interaction with a specific ligand. In our group, we designed an innovative bioinformatics method called SuMo in order to detect similar 3-dimensional (3D) sites in proteins (Jambon et al. Protein-Struct Funct Genet 52:137–145, 2003). This approach allowed the comparison of protein structures or substructures, and detected local spatial similarities: the main advantage of the method is its independence for both amino acid sequences and backbone structures. In contrast to already existing tools, the basis for this method is a representation of the protein structure by a set of stereo chemical groups that are defined independently from the notion of amino acid. An efficient heuristics for finding similarities has been developed which uses graphs of triangles of chemical groups to represent the protein structures. The SuMo (Surfing the Molecules) program allows the dynamic definition of chemical groups, the selection of sites in the proteins, and the management and screening of databases. The basic principle of SuMo has been used in several recent studies (Sperandio et al. J Cheml Inf Model 47:1097–1110, 2007) (Doppelt-Azeroual et al. Protein Sci 19:847–867, 2010). In order to give access to the SuMo tool, we proposed a web server (Jambon et al. Bioinformatics 21:3929–3930, 2005) reachable at http://sumo-pbil.ibcp.fr. This chapter will describe the main rationale we initially took for designing the first release of SuMo. In addition, we propose a completely new set of parameters best suitable for proteins and finally, we illustrate its power with several biological examples. Two of them dealing with serine proteases and lectins are given for a comparison purpose. The first two examples illustrate the capability of SuMo to deal with completely opposite modes of evolution i.e. convergence and divergence. A new biological application dealing with betalactame binding protein PBB molecules is also presented.

Keywords

Proteins Structural bioinformatics 3D structure Physico-chemical groups 3D sites Annotation Triangle form Delta-plus Delta-minus Glycine polar Hydrophobic aliphatic Carbon alpha Hydrophobic aromatic Target structure Objects Proteases Isomerases Lectins Betalactam Penicillin drug Cephalosporin drug Ceftazidime Serine proteases Protein-protein interaction SuMo 

Notes

Acknowledgements

Thanks are due to Martin Jambon as the main author of the original SuMo program written in OCAML.

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Université Lyon 1, CNRS, UMR 5086; Bases Moléculaires et Structurales des Systèmes InfectieuxLyonFrance

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