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

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...

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Autores principales: Žváček, Clemens, Friedrichs, Gerald, Heizinger, Leonhard, Merkl, Rainer
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4634577/
https://www.ncbi.nlm.nih.gov/pubmed/26538500
http://dx.doi.org/10.1186/s12859-015-0807-6
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author Žváček, Clemens
Friedrichs, Gerald
Heizinger, Leonhard
Merkl, Rainer
author_facet Žváček, Clemens
Friedrichs, Gerald
Heizinger, Leonhard
Merkl, Rainer
author_sort Žváček, Clemens
collection PubMed
description 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0807-6) contains supplementary material, which is available to authorized users.
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spelling pubmed-46345772015-11-06 An assessment of catalytic residue 3D ensembles for the prediction of enzyme function Žváček, Clemens Friedrichs, Gerald Heizinger, Leonhard Merkl, Rainer BMC Bioinformatics Research Article 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0807-6) contains supplementary material, which is available to authorized users. BioMed Central 2015-11-04 /pmc/articles/PMC4634577/ /pubmed/26538500 http://dx.doi.org/10.1186/s12859-015-0807-6 Text en © Žváček et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Žváček, Clemens
Friedrichs, Gerald
Heizinger, Leonhard
Merkl, Rainer
An assessment of catalytic residue 3D ensembles for the prediction of enzyme function
title An assessment of catalytic residue 3D ensembles for the prediction of enzyme function
title_full An assessment of catalytic residue 3D ensembles for the prediction of enzyme function
title_fullStr An assessment of catalytic residue 3D ensembles for the prediction of enzyme function
title_full_unstemmed An assessment of catalytic residue 3D ensembles for the prediction of enzyme function
title_short An assessment of catalytic residue 3D ensembles for the prediction of enzyme function
title_sort assessment of catalytic residue 3d ensembles for the prediction of enzyme function
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4634577/
https://www.ncbi.nlm.nih.gov/pubmed/26538500
http://dx.doi.org/10.1186/s12859-015-0807-6
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