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E-Cell System pp 105–142Cite as

Dynamic Kinetic Modeling of Mitochondrial Energy Metabolism

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Part of the book series: Molecular Biology Intelligence Unit ((MBIU))

Abstract

Computer simulations can be used to predict the dynamic behaviour of metabolic pathways and to provide evidence in support of clinical treatments for metabolic disorders. Here, we performed dynamic kinetic simulations of mitochondrial energy metabolism using the E-Cell Simulation Environment. The simulation model was developed as a reconstruction of publicly available kinetic studies on the enzymes of the respiratory chain, the TCA cycle, fatty acid β-oxidation and the inner-membrane metabolite transporters.1 Rate equations for the 58 enzymatic reactions and 286 of the 471 kinetic parameters were taken from 36 and 45 articles, respectively. Approximately 80% of the articles that contributed to the kinetic properties of the mitochondrial model have “kinetics” and the enzyme name as their MeSH terms. The published data were mainly obtained from various tissues in five mammals (human, bovine, pig, rabbit and rat). The other kinetic parameters were estimated numerically using a genetic algorithm module of E-Cell to satisfy the Lineweaver-Burk plot of each enzyme. The simulations indicated that increasing coenzyme Q and succinate promotes the total activity of the respiratory chain without affecting other pathways. This result agrees qualitatively with a clinical case report of treatment with coenzyme Q and succinate.2 In another case, oxoglutarate supplementation also activated the respiratory chain, but mainly through activation by Complex I. This contrasts with the electron donation through the succinate dehydrogenase complex in the case of coenzyme Q + succinate. These results support the utility of the mitochondrial metabolism model in elucidating action mechanism of clinical treatments.

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  1. Department of Biophysics and Biochemistry, University of Tokyo, Tokyo, Japan

    Katsuyuki Yugi

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Yugi, K. (2013). Dynamic Kinetic Modeling of Mitochondrial Energy Metabolism. In: E-Cell System. Molecular Biology Intelligence Unit. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6157-9_8

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