Enzyme kinetic constants in vivo are largely unknown, which limits the construction of large metabolic models. In theory, kinetic constants can be fitted to measured metabolic fluxes, metabolite concentrations, and enzyme concentrations, but these estimation problems are typically non-convex. This makes them hard to solve, especially if models are large. The model balancing method assumes that the metabolic fluxes are given and show that consistent kinetic constants, metabolite levels, and enzyme levels can then be found by solving a convex optimality problem. Model balancing can employ a wide range of rate laws, accounts for thermodynamic constraints on parameters, and considers the dependences between flux directions and metabolite concentrations through thermodynamic forces. It can be used to complete and adjust available data, to estimate in-vivo kinetic constants from omics data, or to construct plausible metabolic states with a predefined flux distribution.
If you use enzyme cost minimization in your work, please cite
Model balancing: consistent in-vivo kinetic constants and metabolic states obtained by convex optimisation
Liebermeister W. (2019) bioRxiv doi:10.1101/2019.12.23.887166v1
Matlab code is available on github.
Please contact Wolfram Liebermeister with any questions or comments.