Abstract
The pattern of flux and concentration control coefficients in an integrated mitochondrial energetics model is examined by applying a generalized matrix method of control analysis to calculate control coefficients, as well as response coefficients The computational model of Cortassa et al. encompasses oxidative phosphorylation, the TCA cycle, and Ca(2+) dynamics. Control of ATP synthesis, TCA cycle, and ANT fluxes were found to be distributed among various mitochondrial processes. Control is shared by processes associated with ATP/ADP production and transport, as well as by Ca(2+) dynamics. The calculation also analyzed the control of the concentrations of key regulatory ions and metabolites (Ca(2+), NADH, ADP). The approach we have used demonstrates how properties of integrated systems may be understood through applications of computational modeling and control analysis.
Highlights
In the midst of a transition between analytical and integrative periods in biology, cell physiology is moving from the unraveling of most metabolic pathways, along with their constituent enzymes, towards quantification of integrated networks of reactions [1]
We present selected results obtained with the generalized method of control analysis by Reder [27], as applied to the isolated mitochondrial energetics (ME) model (Scheme 1)
The matrix method does not assume complete fulfillment of the Metabolic Control Analysis (MCA) theorems; as expected from applying it to the steady state, we found that the summation theorems for the flux (= 1.0) and intermediate concentration (= 0) control coefficients were satisfied, along with the summation of the response coefficients (= -1.0) for metabolites [8]
Summary
In the midst of a transition between analytical and integrative periods in biology, cell physiology is moving from the unraveling of most metabolic pathways, along with their constituent enzymes, towards quantification of integrated networks of reactions [1]. Bioenergetics focuses on metabolism, as a mesh of biochemical reactions, and as an evolving, dynamic, and spatially organized, mass-energy-information network [2] Germane to their functionality is the understanding of how those networks are controlled and regulated as a whole. The most frequently reported value is the flux control coefficient, CEJki :
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