Bioinformatics Advance Access published online on May 8, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl181
1 Cologne University BioInformatics Center (CUBIC), Zülpicher Strasse 47, 50674 Koeln, Germany
* To whom correspondence should be addressed.
Motivation: The local and global aspects of metabolic network analyses allow us to identify enzymes or reactions that are crucial for the survival of the organism(s), therefore directing us towards the discovery of potential drug targets. Results: We demonstrate a new method ("load points") to rank the enzymes/metabolites in the metabolic network and propose a model to determine and rank the biochemical lethality in metabolic networks (enzymes/metabolites) through "choke points". Based on an extended form of the graph theory model of metabolic networks, metabolite structural information was used to calculate the k-shortest paths between metabolites (the presence of more than one competing path between substrate and product). On the basis of these paths and connectivity information, load points were calculated and used to empirically rank the importance of metabolites/enzymes in the metabolic network. The load point analysis emphasizes the role that the biochemical structure of a metabolite, rather than its connectivity (hubs), plays in the conversion pathway. In order to identify potential drug targets (based on the biochemical lethality of metabolic networks), the concept of "choke points" and "load points" was used to find enzymes (edges) which uniquely consume or produce a particular metabolite (nodes). A non-pathogenic bacterial strain Bacillus subtilis 168 (lactic acid producing bacteria) and a related pathogenic bacterial strain Bacillus anthracis Sterne (avirulent but toxigenic strain, producing the toxin Anthrax) were selected as model organisms. The choke point strategy was implemented on the pathogen bacterial network of Bacillus anthracis Sterne. Potential drug targets are proposed based on the analysis of the top 10 choke points in the bacterial network. A comparative study between the reported top 10 bacterial choke points and the human metabolic network was performed. Further biological inferences were made on results obtained by performing a homology search against the human genome. Availability: The load and choke point modules are introduced in the Pathway Hunter Tool (PHT), the basic version of which is available on http://www.pht.uni-koeln.de.
Received August 9, 2005
Revised May 3, 2006
Accepted May 4, 2006
Article
Observing local and global properties of metabolic pathways: "load points" and "choke points" in the metabolic networks
Syed Asad Rahman 1
and
Dietmar Schomburg 2 *
2 Cologne University BioInformatics Center (CUBIC), Zülpicher Strasse 47, 50674 Koeln, Germany; Institute for Biochemistry, Zülpicher Strasse 47, 50674 Koeln, Germany
Dietmar Schomburg, E-mail: d.schomburg{at}uni-koeln.de
Abstract
Associate Editor: Charlie Hodgman
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