Max-Delbrueck-Center for Molecular Medicine
Robert-Roessle-Str. 10
13092 Berlin
Phone: +49-030-94063125
Email: stschust@mdc-berlin.de
The topological analysis of metabolic systems has become an integrative part of bioinformatics. This analysis includes tools for the computer-aided construction of biochemical pathways, which is instrumental in biotechnology and functional genomics [Schuster et al., 2000]. One of these methods is based on the concept of elementary flux modes. It allows one to test whether sets of enzymes form a consistent pathway allowing mass balancing for each intermediate and complying with the directionality of reactions (irreversibility). This concept is here illustrated by a biochemical network taken from nucleotide metabolism. Pathway analysis can be performed without the knowledge of kinetic parameters. An algorithm for determining all elementary modes in biochemical reaction networks of any complexity has been implemented by us earlier, in the program METATOOL [Pfeiffer et al., 1999]. Here, we present the newest version of METATOOL (version 3.5), which includes several new features such as the detection of the connectivity distribution (with connectivity defined as the number of reactions in which a given substance participates). Furthermore, the branch point metabolites of a network and the conservation relations are given explicitly. Dead-end metabolites and sets of inconsistent irreversible reactions are highlighted, which helps the user to check model consistency. Moreover, the elementary modes are compared with the vectors in the convex basis.
An important and complicated technical question in the computation of elementary modes is the suitable classification of external metabolites (sources and sinks) and internal metabolites (intermediates). A reasonable criterion for this classification is to minimize the number of elementary modes. This criterion is related to Kolmogorov complexity and was chosen in order to reduce combinatorial explosion in complex networks. We present two strategies (implemented as C programs) to find the convenient classification. These tools are illustrated by the nucleotide metabolism example.
Up to now it is impossible to analyse the whole metabolism of organisms. Therefore, block-diagonalization and cluster analysis based on the shortest pathways is used to decompose large metabolic network into smaller ones.