Thermodynamically Explicit Kinetics with Potential for Genome-wide Application
Metabolic processes are inherently dynamic, yet genome-scale models are often limited to steady-state analysis, which cannot capture time-dependent responses crucial for understanding complex diseases like cancer. This work introduces a Thermodynamically Explicit (TDE) kinetic framework to bridge this gap by constructing dynamic metabolic models grounded in fundamental thermodynamic principles. Our approach uses standard chemical potentials to derive simplified rate laws for metabolic reactions, reducing the kinetic complexity of each reaction to a single, biochemically determined prefactor ({lambda}), which we will name kinetic capacity factor. The number of parameters in the suggested TDE kinetics is indeed minimal in the sense that it uses the lowest possible number of free parameters required to define a reaction rate that is both dynamic and thermodynamically consistent. We demonstrate the validity and practical application of this framework by re-parameterizing a well-established kinetic model of glycolysis. The resulting TDE model successfully reproduces the dynamic behavior of the original, more complex model in simulations. By streamlining the parameterization process, the TDE kinetic framework offers a powerful and scalable tool for building genome-wide dynamic metabolic models. This approach paves the way for more accurate and predictive simulations of metabolic behavior, with significant potential for applications in systems biology, medicine, and biotechnology.