Evidence map›Paper›PMID 26538500›Full record

ArticleBMC bioinformatics2015

An assessment of catalytic residue 3D ensembles for the prediction of enzyme function.

Clemens Žváček, Gerald Friedrichs, Leonhard Heizinger, Rainer Merkl

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Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Clemens ŽváčekFaculty of Mathematics and Computer Science, University of Hagen, D-58084, Hagen, Germany. clemens@zvacek.de.
Gerald FriedrichsFaculty of Mathematics and Computer Science, University of Hagen, D-58084, Hagen, Germany. gerald.friedrichs@fernuni-hagen.de.
Leonhard HeizingerInstitute of Biophysics and Physical Biochemistry, University of Regensburg, D-93040, Regensburg, Germany. leonhard.heizinger@ur.de.
Rainer MerklInstitute of Biophysics and Physical Biochemistry, University of Regensburg, D-93040, Regensburg, Germany. rainer.merkl@ur.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 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.

resultsWe 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.

conclusionsFor 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.

Indexed as

Amino AcidsCatalysisCatalytic DomainComputational BiologyDatabases, ProteinEnzymesEvolution, MolecularGene OntologySequence Homology, Amino AcidSubstrate SpecificityAmino AcidsEnzymes

Identifiers

PMID26538500
PMCPMC4634577

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