To understand the complex system of life it is required to investigate the characteristics of biomolecular network consisting of not only proteins or nucleic acids but also small chemical compounds (1
). In spite of a number of sequence comparison servers, there are few servers to compare chemical structures for metabolic pathway analyses. In addition, almost all servers for chemical structure comparisons commonly use the bit-string method (3
), and there had been no server based on the graph comparison method, which is considered more accurate. In this context, we have developed two types of chemical structure search servers as parts of the GenomeNet computation services, aiming at the better comprehension of the relationship between genomic and chemical implications of metabolic pathways. One is the SIMCOMP (4
) server for the chemical similarity search and the other is the SUBCOMP for the chemical substructure search, where both servers provide links to the KEGG PATHWAY and BRITE databases (6
). SIMCOMP (SIMilar COMPound) has originally been developed as a graph-based method for comparing chemical structures, which searches for the maximal cliques in the association graph as the maximum common induced subgraph (MCIS). However, the current version of SIMCOMP can also compute the maximum common edge subgraph (MCES), which is faster because of the small number of nodes in an association graph. Moreover, we have now added further computation features to SIMCOMP, including chirality check and PATHWAY/BRITE mapping. In contrast, SUBCOMP (SUBstructure matching of COMPounds) is an extended method based on the bit-vector representation for searching chemical substructures, which is often used as a rapid alternative to more time-consuming (but more accurate) SIMCOMP.
The notable features of the SIMCOMP and SUBCOMP servers are as follows: (i) After obtaining the list of similar compounds, users can map the selected entries onto the KEGG PATHWAY or KEGG BRITE databases. This feature may help us to investigate biological roles of those chemical compounds as well as a query compound. (ii) Both SIMCOMP and SUBCOMP can discriminate the isomeric structures, including the R−/S− chirality found at asymmetrical carbons and the cis–trans isomerism around the carbon–carbon double bonds. (iii) Various matching conditions are now available in the SUBCOMP computation. ‘Charge’ and ‘Valence’ options will distinguish ionized atoms from normal atoms and the valence of each atom, in other words, the oxidation state of each atom, respectively. ‘Coordinate bond’ option can be used to consider the coordinate bond formed between anion–cation single bond. (iv) The superstructure search is also available for searching chemical compounds that are included in the query structure, in the SUBCOMP.
With these characteristic features, both structure search servers can provide the way of the biochemical analyses on the metabolic networks for chemical compounds including bioactive natural products and drugs. The results of mapping onto PATHWAY or BRITE databases may indicate which biological functions are involved in the selected chemicals.