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首页> 外文会议>International Symposium on Knowledge and Systems Sciences(KSS2004); 20041110-12; Ishikawa(JP) >A Novel Graph-Based Similarity Measure for 2D Chemical Structures
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A Novel Graph-Based Similarity Measure for 2D Chemical Structures

机译：一种基于图的二维化学结构相似性度量

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摘要

In this paper, we propose an innovative graph-based method to measure the similarity between chemical compounds described by 2D description. The similarity between two compounds which are presented by two graphs is computed by combining the weights of these graphs' non-overlap connected common subgraphs. We applied our similarity measure in conjunction with complete linkage clustering method to more than eleven thousand compounds in the KEGG/LIGAND database. We discovered that compound clusters contain highly similar structure compounds, which again share common names, take part in the same metabolic pathways, and have the same re-quirement of enzymes in their reactions. In addition, we discovered the surprising sameness between pathway modules identified by clusters of similar structure com-pounds and that identified by genomic contexts, namely, operon structures of enzyme genes.
机译：在本文中，我们提出了一种创新的基于图的方法来测量2D描述所描述的化合物之间的相似性。通过组合两个图的非重叠连接公共子图的权重，可以计算两个图表示的两种化合物之间的相似度。我们将我们的相似性度量与完整的链接聚类方法一起应用于KEGG / LIGAND数据库中的一万一千多种化合物。我们发现化合物簇包含高度相似的结构化合物，这些化合物又具有共同的名称，参与相同的代谢途径，并且在反应中对酶的需求相同。另外，我们发现了由相似结构化合物的簇鉴定的通路模块与由基因组背景鉴定的通路模块之间惊人的相同性，即酶基因的操纵子结构。

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