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引用次数: 0
摘要
在活细胞中的许多化学反应中,酶在某些化合物(底物)转化为其他化合物(产物)的过程中起催化剂的作用。对这些反应形成的代谢途径进行比较分析,可以提供有关其进化和药理靶点的重要信息(Dandekar et al. 1999)。构成途径的每种酶都根据EC(酶委员会)编号系统进行分类,该系统由四组编号组成,用于对催化的化学反应类型进行分类。在本研究中,我们认为反应的相似性可以通过各自酶的EC数的相似性来表达。因此,为了找到途径之间的共同模式,希望能够使用EC数的功能层次来表示反应的相似性。在本文中,我们提出了一种利用信息内容扩展到具有层次结构的符号的多重对齐算法。通过将该方法应用于糖、DNA和氨基酸代谢的途径分析,证明了该方法的有效性。
A multiple alignment algorithm for metabolic pathway analysis using enzyme hierarchy.
In many of the chemical reactions in living cells, enzymes act as catalysts in the conversion of certain compounds (substrates) into other compounds (products). Comparative analyses of the metabolic pathways formed by such reactions give important information on their evolution and on pharmacological targets (Dandekar et al. 1999). Each of the enzymes that constitute a pathway is classified according to the EC (Enzyme Commission) numbering system, which consists of four sets of numbers that categorize the type of the chemical reaction catalyzed. In this study, we consider that reaction similarities can be expressed by the similarities between EC numbers of the respective enzymes. Therefore, in order to find a common pattern among pathways, it is desirable to be able to use the functional hierarchy of EC numbers to express the reaction similarities. In this paper, we propose a multiple alignment algorithm utilizing information content that is extended to symbols having a hierarchical structure. The effectiveness of our method is demonstrated by applying the method to pathway analyses of sugar, DNA and amino acid metabolisms.