Development of a Chemical Structure Comparison Method for Integrated Analysis of Chemical and Genomic Information in the Metabolic Pathways

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• 作者：Masahiro Hattori ; Yasushi Okuno ; Susumu Goto ; and Minoru Kanehisa
• 刊名：Journal of the American Chemical Society
• 出版年：2003
• 出版时间：October 1, 2003
• 年：2003
• 卷：125
• 期：39
• 页码：11853 - 11865
• 全文大小：406K
• 年卷期：v.125,no.39(October 1, 2003)
• ISSN：1520-5126

文摘

Cellular functions result from intricate networks of molecular interactions, which involve not onlyproteins and nucleic acids but also small chemical compounds. Here we present an efficient algorithm forcomparing two chemical structures of compounds, where the chemical structure is treated as a graphconsisting of atoms as nodes and covalent bonds as edges. On the basis of the concept of functionalgroups, 68 atom types (node types) are defined for carbon, nitrogen, oxygen, and other atomic specieswith different environments, which has enabled detection of biochemically meaningful features. Maximalcommon subgraphs of two graphs can be found by searching for maximal cliques in the association graph,and we have introduced heuristics to accelerate the clique finding and to detect optimal local matches(simply connected common subgraphs). Our procedure was applied to the comparison and clustering of9383 compounds, mostly metabolic compounds, in the KEGG/LIGAND database. The largest clusters ofsimilar compounds were related to carbohydrates, and the clusters corresponded well to the categorizationof pathways as represented by the KEGG pathway map numbers. When each pathway map was examinedin more detail, finer clusters could be identified corresponding to subpathways or pathway modules containingcontinuous sets of reaction steps. Furthermore, it was found that the pathway modules identified by similarcompound structures sometimes overlap with the pathway modules identified by genomic contexts, namely,by operon structures of enzyme genes.