E-zyme: Predicting potential EC numbers from the chemical transformation pattern of substrate-product pairs

Yoshihiro Yamanishi, Masahiro Hattori, Masaaki Kotera, Susumu Goto, Minoru Kanehisa

    Research output: Contribution to journalArticle

    40 Citations (Scopus)

    Abstract

    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.

    Original languageEnglish
    Pages (from-to)i179-i186
    JournalBioinformatics
    Volume25
    Issue number12
    DOIs
    Publication statusPublished - Jun 9 2009

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    All Science Journal Classification (ASJC) codes

    • Biochemistry
    • Molecular Biology
    • Computational Theory and Mathematics
    • Computer Science Applications
    • Computational Mathematics
    • Statistics and Probability

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