Embedding of pathway models into metabolic networks

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Kinetic pathway models are usually bounded by external metabolites with fixed concentrations. In reality, pathways are embedded in larger networks whose dynamics (e.g., a depletion of biosynthetic precursors) can feed back on the pathways and change their dynamics. Since network-scale kinetic models are hardly available, I present an algorithm to embed kinetic pathway models into larger metabolic network models with simplified kinetics and rate constants obtained from elasticity sampling.

In the algorithm, the compounds and reactions are mapped between kinetic and stoichiometric models and a hybrid model with a metabolic state (characterised by flux distribution, metabolite levels, and thermodynamic forces) is constructed. In a second step, the reactions in the stoichiometric network are equipped with standard rate laws, resulting in a complete kinetic model with a thermodynamically feasible steady state. The algorithm allows to control the resulting steady state and guarantees a thermodynamically feasible model. Two example cases are presented below.