Thermodynamics As an Optimization Goal for Metabolism: Prediction of Metabolite Levels, Rate Constants and Post-Translational Regulation
Conference on Constraint-Based Reconstruction and Analysis (COBRA)
Sunday, October 14, 2018 - 6:00pm to 7:00pm
Nature selects those organisms that can reproduce the fastest while maintaining fitness and extracting the least amount of energy from their environment. This problem can be formulated as a maximum entropy production rate problem that includes experimental and physical constraints. We report the application this approach for modeling biological systems in lieu of having in vivorate constants. The method is applied in four steps: (1) a new constrained optimization approach based on Marcelinâs 1910 mass action equation is used to obtain the maximum entropy distribution, (2) the predicted metabolite concentrations are compared to those generally expected from experiment using a loss function from which post-translational regulation of enzymes is inferred, (3) the system is re-optimized with the inferred regulation from which rate constants are determined from the metabolite concentrations and reaction fluxes, and finally (4) a full ODE-based, mass action simulation with rate parameters and allosteric regulation is obtained. From the last step, the power characteristics and resistance of each reaction can be determined. The method is applied to the central metabolism of Neurospora crassaand the flow of material through the three competing pathways of upper glycolysis, the non-oxidative pentose phosphate pathway, and the oxidative pentose phosphate pathway are evaluated as a function of the NADP/NADPH ratio. It is predicted that regulation of phosphofructokinase (PFK) and flow through the pentose phosphate pathway are essential for preventing an extreme level of fructose 1, 6-bisphophate accumulation. Such an extreme level of fructose 1,6-bisphophate would otherwise result in a glassy cytoplasm with limited diffusion, dramatically decreasing the entropy and energy production rate and, consequently, biological competitiveness.