Abstract
An important aspect of kinetic modeling is the ability to provide predictive information on network control and dynamic responses to genetic or environmental perturbations based on innate enzyme kinetics. In a top-down approach to model assembly, unknown kinetic parameters are calculated using experimental data such as metabolite pool concentrations and transient labeling patterns after supply of an isotopically labeled substrate. These kinetic parameters can then be used to calculate flux control coefficients for every reaction in a network, which aids in the identification of enzymatic reactions that exert the most control over the network as a whole. This chapter describes a modeling approach to estimate kinetic parameters which are then used to perform metabolic control analysis. An example is provided for the benzenoid network of Petunia hybrida; however, the methodologies can be applied to any small segment of metabolism.
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Acknowledgments
This work is supported by the National Institutes of Health (NRSA fellowship number GM095273 for AMC) and by the US National Science Foundation (grant number MCB-0615700 for JAM and DR).
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Marshall-Colon, A., Sengupta, N., Rhodes, D., Morgan, J.A. (2014). Simulating Labeling to Estimate Kinetic Parameters for Flux Control Analysis. In: Dieuaide-Noubhani, M., Alonso, A. (eds) Plant Metabolic Flux Analysis. Methods in Molecular Biology, vol 1090. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-688-7_13
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DOI: https://doi.org/10.1007/978-1-62703-688-7_13
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