Poster Presentation 2014 International Biophysics Congress

General framework for thermodynamically consistent parameterization and efficient sampling of metabolic reactions (#670)

Pedro A. Saa 1 , Lars K. Nielsen 1
  1. AIBN, The University of Queensland, Brisbane, QLD, Australia
During the past decade, genome-scale stoichiometric models have enabled the exploration and quantification of metabolic phenotypes by using constraint-based modeling methods. Such methods have proved to be extremely useful in characterizing metabolic behaviours under different environmental conditions as well as predicting the result of particular genetic modifications. Although stoichiometric models enable a diversity of analysis, their predictions are limited by lack of enzyme kinetics. Kinetics is frequently represented by simplified approximate formulas (e.g. mass action, reversible Michaelis-Menten, etc.). Many real kinetic behaviours are ignored by these approaches. Moreover, the full thermodynamic relationship between parameters is lost which complicates sampling feasible parameter sets. Here, we present a General Reaction Assembly and Sampling Platform (GRASP), which enables parameterizing and sampling kinetic models by integrating the generalized MCW model with the elementary reaction formalism. By formulating the appropriate thermodynamic constraints, we developed a framework that enables parameterization of simple as well as complex reaction mechanisms, such as random-order and allosteric mechanisms, without sacrificing complexity or using simplifying assumptions. This thermodynamically consistent parameterization incurs no loss in generality and can be efficiently sampled employing standard probability distributions. We used the sampled models to explore the full kinetic space of reactions and to assess the impact of thermodynamics and reaction mechanisms on kinetics. Moreover, we applied this approach to a tightly-regulated small network comprising the methionine cycle in human hepatocytes. Our results reinforce the notion that biological meaningful kinetic parameter sets are constrained to a small portion of the kinetic space allowable by thermodynamics.