title: Bringing metabolic networks to life: convenience rate law and thermodynamic constraints.
abstract: BACKGROUND
  Translating a known metabolic network into a dynamic model requires rate laws for all chemical reactions. The mathematical expressions depend on the underlying enzymatic mechanism; they can become quite involved and may contain a large number of parameters. Rate laws and enzyme parameters are still unknown for most enzymes.
  
  
  RESULTS
  We introduce a simple and general rate law called "convenience kinetics". It can be derived from a simple random-order enzyme mechanism. Thermodynamic laws can impose dependencies on the kinetic parameters. Hence, to facilitate model fitting and parameter optimisation for large networks, we introduce thermodynamically independent system parameters: their values can be varied independently, without violating thermodynamical constraints. We achieve this by expressing the equilibrium constants either by Gibbs free energies of formation or by a set of independent equilibrium constants. The remaining system parameters are mean turnover rates, generalised Michaelis-Menten constants, and constants for inhibition and activation. All parameters correspond to molecular energies, for instance, binding energies between reactants and enzyme.
  
  
  CONCLUSIONS
  Convenience kinetics can be used to translate a biochemical network--manually or automatically--into a dynamical model with plausible biological properties. It implements enzyme saturation and regulation by activators and inhibitors, covers all possible reaction stoichiometries, and can be specified by a small number of parameters. Its mathematical form makes it especially suitable for parameter estimation and optimisation. Parameter estimates can be easily computed from a least-squares fit to Michaelis-Menten values, turnover rates, equilibrium constants, and other quantities that are routinely measured in enzyme assays and stored in kinetic databases.
authors.affiliation: Computational Systems Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany. lieberme@molgen.mpg.de
authors.forename: Wolfram
authors.initials: W
authors.lastname: Liebermeister
authors.forename: Edda
authors.initials: E
authors.lastname: Klipp
mesh_terms: D004734:Energy Metabolism; D004789:Enzyme Activation; D004798:Enzymes / Q000378:metabolism; D007700:Kinetics; D008954:Models, Biological; D013816:Thermodynamics
chemical_list: D004798:Enzymes