  Networks coming from protein-protein interactions, transcriptional
regulation, signaling, or metabolism may appear to have "unusual" properties.
To quantify this, it is appropriate to randomize the network and test the
hypothesis that the network is not statistically different from expected in a
motivated ensemble. However, when dealing with metabolic networks, the
randomization of the network using edge exchange generates fictitious reactions
that are biochemically meaningless. Here we provide several natural ensembles
of randomized metabolic networks. A first constraint is to use valid
biochemical reactions. Further constraints correspond to imposing appropriate
functional constraints. We explain how to perform these randomizations with the
help of Markov Chain Monte Carlo (MCMC) and show that they allow one to
approach the properties of biological metabolic networks. The implication of
the present work is that the observed global structural properties of real
metabolic networks are likely to be the consequence of simple biochemical and
functional constraints.
