Towards kinetic modeling of genome-scale metabolic networks without sacrificing stoichiometric, thermodynamic and physiology constraints

Mathematical modeling is an essential tool for a comprehensive understanding of cell metabolism and its interactions with the environmental and process conditions. Recent developments in the construction and analysis of stoichiometric models made it possible to define limits on steady-state metabolic behavior using flux balance analysis. However, detailed information about enzyme kinetics and enzyme regulation is needed to formulate kinetic models that can accurately capture the dynamic metabolic responses. The use of mechanistic enzyme kinetics is a difficult task due to uncertainty in the kinetic properties of enzymes. Therefore, the majority of recent works consider only the mass action kinetics for the reactions in the metabolic networks. In this work, we applied the ORACLE framework and constructed a large-scale, mechanistic kinetic model of optimally grown E. coli. We investigated the complex interplay between stoichiometry, thermodynamics, and kinetics in determining the flexibility and capabilities of metabolism. Our results indicate that enzyme saturation is a necessary consideration in modeling metabolic networks and it extends the feasible ranges of the metabolic fluxes and metabolite concentrations. Our results further suggest that the enzymes in metabolic networks have evolved to function at different saturation states to ensure greater flexibility and robustness of the cellular metabolism.