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A New Method for Estimating Enzyme Activity and Control Coefficients in vivo

  • Barbara E. Wright
  • Kathy R. Albe
Chapter
Part of the NATO ASI Series book series (NSSA, volume 190)

Abstract

An understanding of metabolism in vivo must, of course, be based upon a systems analysis that includes an examination of the role and relationships of all the variables involved. These include the concentrations of substrates, products, and effectors as well as enzyme kinetic mechanisms, constants and enzyme activity. Current research in areas such as biochemical differentiation, aging, biotechnology, etc., is focussed primarily on the regulation of metabolism by enzyme activity. In fact, metabolites are generally more important than enzymes in controlling reaction rates. As we shall be discussing the citric acid cycle it is appropriate to quote Krebs (1957): “The average half-life of the acids in the tricarboxylic acid cycle ... is a few seconds. The amounts of enzyme in the tissue are sufficient to deal with the intermediates as soon as they arise: in other words, the amount of available substrate is the factor limiting the rate at which the intermediary step proceeds.” And yet, the recent literature on metabolic regulation in vivo describes the role of metabolites by such passive and mysterious words as “elasticity,” while enzymes are given credit as the force behind “control coefficients.” Reactions are often referred to by the name of the enzyme catalyst, and the rate of a reaction in vivo is often equated with the activity of the enzyme. Some of this prejudice stems from in vitro studies, in which enzymes must be diluted to the point at which they limit the rate of the reaction being measured, while substrates must be present at levels greatly exceeding their in vivo concentration.

Keywords

Succinate Dehydrogenase Malate Dehydrogenase Isocitrate Dehydrogenase Malic Enzyme Citric Acid Cycle 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1990

Authors and Affiliations

  • Barbara E. Wright
    • 1
  • Kathy R. Albe
    • 1
  1. 1.Division of Biological SciencesUniversity of MontanaMissoulaUSA

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