Cellular information transfer regarded from a stoichiometry and control analysis perspective

Metabolic control analysis (MCA) allows one to formalize important aspects of information processing in living cells. For example, information processing via multi-level enzyme cascades can be quantified in terms of the response coefficient of a cellular target to a signal. In many situations, control and response coefficients cannot be determined exactly for all enzymes involved, owing to difficulties in `observingʹ all enzymes experimentally. Here, we review a number of qualitative approaches that were developed to cope with such situations. The usefulness of the concept of null-space of the stoichiometry matrix for analysing the structure of intracellular signaling networks is discussed. It is shown that signal transduction operates very efficiently when the network structure is such that the null-space matrix can be blockdiagonalized (which may or may not imply that the network consists of several disconnected parts) and some enzymes have low elasticities to their substrates.