Metabolic control analysis

Metabolic control

Metabolic control analysis (MCA) is a mathematical framework for describing
metabolic, signaling, and genetic pathways. MCA quantifies how variables, such as fluxes and species concentrations, depend on network parameters. In particular, it is able to describe how network dependent properties,
called control coefficients, depend on local properties called elasticities or Elasticity Coefficients. MCA was originally developed to describe the control in metabolic pathways
but was subsequently extended to describe signaling and genetic networks. MCA has sometimes also been referred to as Metabolic Control Theory, but this terminology was rather strongly opposed by Henrik Kacser, one of the founders. More recent work has shown that MCA can be mapped directly on to classical control theory and are as such equivalent. Biochemical systems theory (BST) is a similar formalism, though with rather different objectives. Both are evolutions of an earlier theoretical analysis by Joseph Higgins. Chemical reaction network theory is another theoretical framework that has overlap with both MCA and BST but is considerably more mathematically formal in its approach. It's emphasis is primarily on dynamic stability criteria and related theorems associated with mass action networks. In more recent years the field has also developed a sensitivity analysis which is similar if not identical to MCA and BST.

The flux control summation theorem was discovered independently by the Kacser/Burns group]].

Classical Control theory is a field of mathematics that deals with the control of dynamical systems in engineered processes and machines. In 2004 Brian Ingalls published a paper that showed that classical control theory and metabolic control analysis were identical. The only difference was that metabolic control analysis was confined to zero frequency responses when cast in the frequency domain whereas classical control theory imposes no such restriction. The other significant difference is that classical control theory has no notion of stoichiometry and conservation of mass which makes it more cumbersome to use but also means it fails to recognize the structural properties inherent in stoichiometric networks which provide useful biological insights.