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E-zyme: predicting potential EC numbers from the chemical transformation pattern of substrate-product pairs
Motivation: The IUBMB's Enzyme Nomenclature system, commonly known as the Enzyme Commission (EC) numbers, plays key roles in classifying enzymatic reactions and in linking the enzyme genes or proteins to reactions in metabolic pathways. There are numerous reactions known to be present in variou...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2009
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2687977/ https://www.ncbi.nlm.nih.gov/pubmed/19477985 http://dx.doi.org/10.1093/bioinformatics/btp223 |
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author | Yamanishi, Yoshihiro Hattori, Masahiro Kotera, Masaaki Goto, Susumu Kanehisa, Minoru |
author_facet | Yamanishi, Yoshihiro Hattori, Masahiro Kotera, Masaaki Goto, Susumu Kanehisa, Minoru |
author_sort | Yamanishi, Yoshihiro |
collection | PubMed |
description | Motivation: The IUBMB's Enzyme Nomenclature system, commonly known as the Enzyme Commission (EC) numbers, plays key roles in classifying enzymatic reactions and in linking the enzyme genes or proteins to reactions in metabolic pathways. There are numerous reactions known to be present in various pathways but without any official EC numbers, most of which have no hope to be given ones because of the lack of the published articles on enzyme assays. Results: In this article we propose a new method to predict the potential EC numbers to given reactant pairs (substrates and products) or uncharacterized reactions, and a web-server named E-zyme as an application. This technology is based on our original biochemical transformation pattern which we call an ‘RDM pattern’, and consists of three steps: (i) graph alignment of a query reactant pair (substrates and products) for computing the query RDM pattern, (ii) multi-layered partial template matching by comparing the query RDM pattern with template patterns related with known EC numbers and (iii) weighted major voting scheme for selecting appropriate EC numbers. As the result, cross-validation experiments show that the proposed method achieves both high coverage and high prediction accuracy at a practical level, and consistently outperforms the previous method. Availability: The E-zyme system is available at http://www.genome.jp/tools/e-zyme/ Contact: kanehisa@kuicr.kyoto-u.ac.jp |
format | Text |
id | pubmed-2687977 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-26879772009-06-02 E-zyme: predicting potential EC numbers from the chemical transformation pattern of substrate-product pairs Yamanishi, Yoshihiro Hattori, Masahiro Kotera, Masaaki Goto, Susumu Kanehisa, Minoru Bioinformatics Ismb/Eccb 2009 Conference Proceedings June 27 to July 2, 2009, Stockholm, Sweden Motivation: The IUBMB's Enzyme Nomenclature system, commonly known as the Enzyme Commission (EC) numbers, plays key roles in classifying enzymatic reactions and in linking the enzyme genes or proteins to reactions in metabolic pathways. There are numerous reactions known to be present in various pathways but without any official EC numbers, most of which have no hope to be given ones because of the lack of the published articles on enzyme assays. Results: In this article we propose a new method to predict the potential EC numbers to given reactant pairs (substrates and products) or uncharacterized reactions, and a web-server named E-zyme as an application. This technology is based on our original biochemical transformation pattern which we call an ‘RDM pattern’, and consists of three steps: (i) graph alignment of a query reactant pair (substrates and products) for computing the query RDM pattern, (ii) multi-layered partial template matching by comparing the query RDM pattern with template patterns related with known EC numbers and (iii) weighted major voting scheme for selecting appropriate EC numbers. As the result, cross-validation experiments show that the proposed method achieves both high coverage and high prediction accuracy at a practical level, and consistently outperforms the previous method. Availability: The E-zyme system is available at http://www.genome.jp/tools/e-zyme/ Contact: kanehisa@kuicr.kyoto-u.ac.jp Oxford University Press 2009-06-15 2009-05-27 /pmc/articles/PMC2687977/ /pubmed/19477985 http://dx.doi.org/10.1093/bioinformatics/btp223 Text en © 2009 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Ismb/Eccb 2009 Conference Proceedings June 27 to July 2, 2009, Stockholm, Sweden Yamanishi, Yoshihiro Hattori, Masahiro Kotera, Masaaki Goto, Susumu Kanehisa, Minoru E-zyme: predicting potential EC numbers from the chemical transformation pattern of substrate-product pairs |
title | E-zyme: predicting potential EC numbers from the chemical transformation pattern of substrate-product pairs |
title_full | E-zyme: predicting potential EC numbers from the chemical transformation pattern of substrate-product pairs |
title_fullStr | E-zyme: predicting potential EC numbers from the chemical transformation pattern of substrate-product pairs |
title_full_unstemmed | E-zyme: predicting potential EC numbers from the chemical transformation pattern of substrate-product pairs |
title_short | E-zyme: predicting potential EC numbers from the chemical transformation pattern of substrate-product pairs |
title_sort | e-zyme: predicting potential ec numbers from the chemical transformation pattern of substrate-product pairs |
topic | Ismb/Eccb 2009 Conference Proceedings June 27 to July 2, 2009, Stockholm, Sweden |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2687977/ https://www.ncbi.nlm.nih.gov/pubmed/19477985 http://dx.doi.org/10.1093/bioinformatics/btp223 |
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