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

Abstract

Cellular functions result from intricate networks of molecular interactions, which involve not only proteins and nucleic acids but also small chemical compounds. Here we present an efficient algorithm for comparing two chemical structures of compounds, where the chemical structure is treated as a graph consisting of atoms as nodes and covalent bonds as edges. On the basis of the concept of functional groups, 68 atom types (node types) are defined for carbon, nitrogen, oxygen, and other atomic species with different environments, which has enabled detection of biochemically meaningful features. Maximal common 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 of 9383 compounds, mostly metabolic compounds, in the KEGG/LIGAND database. The largest clusters of similar compounds were related to carbohydrates, and the clusters corresponded well to the categorization of pathways as represented by the KEGG pathway map numbers. When each pathway map was examined in more detail, finer clusters could be identified corresponding to subpathways or pathway modules containing continuous sets of reaction steps. Furthermore, it was found that the pathway modules identified by similar compound structures sometimes overlap with the pathway modules identified by genomic contexts, namely, by operon structures of enzyme genes.

Structural analyses of a hypothetical minimal metabolism

“…When more than one substrate, or more than one product, were represented for a given reaction in a pathway map, we included connections only through pairs of compounds that have at least one carbon atom in common on the two sides of the reaction. For this purpose, we used the atomic mappings of the corresponding reactions annotated in the RPAIR database (Hattori et al 2003). Finally, we automatically checked for errors in the directionality of the reaction detected by Ma & Zeng (2003) and made efforts to correct additional obvious inconsistencies.…”

Acute lymphoblastic leukemia with TEL-AML1 fusion has lower expression of genes involved in purine metabolism and lower de novo purine synthesis

“…We selected 129 probes sets (82 genes) involved in purine metabolism pathways according to the Kyoto Encyclopedia of Genes and Genomes (KEGG) 12 (Supplemental Document).…”

Unifying Bioinformatics and Chemoinformatics for Drug Design

“…Next, consider the second case when a ligand has a target receptor, and one wishes to query (assay) the same receptor for activity by using similar ligands. In this case, KEGG atom type (Hattori et al, 2003) frequency profiles are used to represent molecules, and ligands with similar frequency patterns are returned by a similarity search. The idea that similar frequency patterns results in similar molecules is based on the concept in linear algebra that vectors with minimum distance between them in a space have similar component vectors.…”