title: An assessment of catalytic residue 3D ensembles for the prediction of enzyme function.
abstract: BACKGROUND
  The central element of each enzyme is the catalytic site, which commonly catalyzes a single biochemical reaction with high specificity. It was unclear to us how often sites that catalyze the same or highly similar reactions evolved on different, i. e. non-homologous protein folds and how similar their 3D poses are. Both similarities are key criteria for assessing the usability of pose comparison for function prediction.
  
  
  RESULTS
  We have analyzed the SCOP database on the superfamily level in order to estimate the number of non-homologous enzymes possessing the same function according to their EC number. 89% of the 873 substrate-specific functions (four digit EC number) assigned to mono-functional, single-domain enzymes were only found in one superfamily. For a reaction-specific grouping (three digit EC number), this value dropped to 35%, indicating that in approximately 65% of all enzymes the same function evolved in two or more non-homologous proteins. For these isofunctional enzymes, structural similarity of the catalytic sites may help to predict function, because neither high sequence similarity nor identical folds are required for a comparison. To assess the specificity of catalytic 3D poses, we compiled the redundancy-free set ENZ_SITES, which comprises 695 sites, whose composition and function are well-defined. We compared their poses with the help of the program Superpose3D and determined classification performance. If the sites were from different superfamilies, the number of true and false positive predictions was similarly high, both for a coarse and a detailed grouping of enzyme function. Moreover, classification performance did not improve drastically, if we additionally used homologous sites to predict function.
  
  
  CONCLUSIONS
  For a large number of enzymatic functions, dissimilar sites evolved that catalyze the same reaction and it is the individual substrate that determines the arrangement of the catalytic site and its local environment. These substrate-specific requirements turn the comparison of catalytic residues into a weak classifier for the prediction of enzyme function.
authors.affiliation: Faculty of Mathematics and Computer Science, University of Hagen, D-58084, Hagen, Germany. clemens@zvacek.de.
authors.forename: Clemens
authors.initials: C
authors.lastname: Žváček
authors.affiliation: Faculty of Mathematics and Computer Science, University of Hagen, D-58084, Hagen, Germany. gerald.friedrichs@fernuni-hagen.de.
authors.forename: Gerald
authors.initials: G
authors.lastname: Friedrichs
authors.affiliation: Institute of Biophysics and Physical Biochemistry, University of Regensburg, D-93040, Regensburg, Germany. leonhard.heizinger@ur.de.
authors.forename: Leonhard
authors.initials: L
authors.lastname: Heizinger
authors.affiliation: Institute of Biophysics and Physical Biochemistry, University of Regensburg, D-93040, Regensburg, Germany. rainer.merkl@ur.de.
authors.forename: Rainer
authors.initials: R
authors.lastname: Merkl
mesh_terms: D000596:Amino Acids / Q000737:chemistry*; D002384:Catalysis; D020134:Catalytic Domain; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D004798:Enzymes / Q000737:chemistry* / Q000378:metabolism*; D019143:Evolution, Molecular; D063990:Gene Ontology; D017386:Sequence Homology, Amino Acid; D013379:Substrate Specificity
chemical_list: D000596:Amino Acids; D004798:Enzymes