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Abstract

Math. description of metabolic systems allows the calcn. of the expected responses of metab. to genetic modifications and the identifications of the most promising targets for metabolic engineering. Metabolic control anal. (MCA) provides such a description in the form of quant. indexes (elasticities and control coeffs.). These indexes are detd. by perturbation expts. around a ref. steady state and, therefore, the predictive power of MCA is limited to small changes in the metabolic parameters. The modeling framework introduced here allows accurate description of the metabolic responses over wide range of changes in the metabolic parameters. The framework requires information about the MCA indexes at the ref. state and the corresponding values of the metabolic reaction rates, and employs simplifying assumptions about the reaction mechanisms. It is shown that knowledge of the intracellular metabolite concns. is not necessary for the application of the framework. The performance of the methodol. is illustrated using three elementary metabolic systems that display highly nonlinear responses to the modification in their parameters: an unbranched pathway, an interconvertible enzyme system, and a branched pathway subject to feedback inhibition. (c) 1999 Academic Press. [on SciFinder (R)]

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