The control of cell metabolism for homogeneous vs. heterogeneous enzyme systems

G. Rickey Welch, Tamás Keleti, Beáta Vértessy

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Metabolic control theories, based on such parameters as "elasticity coefficients" and "flux-control coefficients", have emergd in recent years. These offer a potentially unifying, holistic paradigm for understanding the regulation of cell metabolism. Much of the foundation relies on the supposition that the system is a homogeneous bulk-phase solution of individual enzymes. We examine some of the tenets of such theories, in the light of increasing knowledge of enzyme organization in vivo. We cast the control parameters into a more general form applicable to the linear kinetic regime, using a newly defined unit-the kinetic power, which allows complete specification in terms of any and all factors which bear upon the conversion of free substrate to free product in situ. Extending the control theory to heterogeneous states of enzyme organization, we make a formal distinction between "solution connectivity" and "structural connectivity" in a multienzyme system. The use of "structural" rate expressions leads to the definition of a flux-control coefficient which specifies the interdependence of the individual rate processes in an organized system. The problems and limitations in applying the control theory to experimental analysis of real systems in situ are discussed. "We have arrived at last at a point which comes rather close to what might be defined as 'molecular control of cellular activity', only to discover that the 'controlling' molecules have themselves acquired their specific configurations, which are the key to their power of control, by virtue of their membership in the population of an organized cell, hence under 'cellular control'." (Weiss, 1963).

Original languageEnglish
Pages (from-to)407-422
Number of pages16
JournalJournal of Theoretical Biology
Issue number4
Publication statusPublished - Feb 21 1988


ASJC Scopus subject areas

  • Statistics and Probability
  • Modelling and Simulation
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

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