(650f) A Statistical Thermodynamical Interpretation of Metabolism

The metabolic network of a cell can be decomposed into discrete elementary modes that contribute, each with a certain probability, to the overall flux through the metabolism. These modes are cell function supporting, fundamental pathways that represent permissible 'quantum' states of the metabolism. For the case that cellular regulatory mechanisms for pathway fluxes evolved in an unbiased way, we show that the usage probabilities of individual elementary modes are expected to be distributed according to Boltzmann's distribution law such that the rate of entropy generation is maximized. Such distribution can be observed experimentally in highly evolved metabolic networks. Therefore, cell function has a natural tendency to operate at a maximum rate of entropy generation using preferentially efficient pathways with small reaction entropies as suggested by the Gibbs measure. Ultimately, evolution of metabolic networks appears to be driven by forces that can be quantified by the distance of the current metabolic state from the state of maximum entropy generation that represents the unbiased, most probable selection of fundamental pathway choices.