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Metabolite and reaction inference based on enzyme specificities

机译:基于酶特异性的代谢物和反应推断

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摘要

Motivation: Many enzymes are not absolutely specific, or even promiscuous: they can catalyze transformations of more compounds than the traditional ones as listed in, e.g. KEGG. This information is currently only available in databases, such as the BRENDA enzyme activity database. In this article, we propose to model enzyme aspecificity by predicting whether an input compound is likely to be transformed by a certain enzyme. Such a predictor has many applications, for example, to complete reconstructed metabolic networks, to aid in metabolic engineering or to help identify unknown peaks in mass spectra.
机译:动机:许多酶不是绝对特异性的,甚至不是混杂的:它们可以催化比例如凯格该信息当前仅在数据库中可用,例如BRENDA酶活性数据库。在本文中,我们建议通过预测输入化合物是否可能被某种酶转化来对酶特异性建模。这样的预测器具有许多应用,例如,完成重构的代谢网络,辅助代谢工程或帮助识别质谱图中的未知峰。

著录项

  • 来源
    《Bioinformatics》 |2009年第22期|p.2975-2982|共8页
  • 作者单位

    1The Delft Bioinformatics Lab, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Mekelweg 4, 2628 CD Delft, 2Bioprocess Technology Group, Department of Biotechnology, Delft University of Technology, Julianalaan 67, 2628 BC Delft, 3Kluyver Centre for Genomics of Industrial Fermentation, P.O. Box 5057, 2600 GA Delft and 4Netherlands Bioinformatics Center, 260 NBIC, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands;

  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
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