Overview

This chapter begins by examining some of the difficulties encountered when conventional deterministic programming methods are applied to cell signaling pathways. These include the combinatorial explosion of large numbers of different species and the instability associated with reactions between small numbers of molecules. The advantages of individual-based, stochastic modeling are then reviewed and a novel stochastic program, called StochSim, is described.

The application of stochastic models to signaling pathways is examined with specific reference to the pathway employed by coliform bacteria in the detection of attractants and repellents. Key conceptual advances underlying this approach are the recognition that many individual proteins in a pathway operate in functional units, known as receptor complexes, and that thermally driven flipping of proteins and protein complexes from one conformation to another underlies all signaling events inside the cell.

The bacterial chemotaxis pathway is controlled by two large protein assemblies associated with the plasma membrane the receptor complex and the flagellar motor. Stochastic modeling of these two complexes and the conformational changes they undergo allows us to integrate biochemical and thermodynamic data into a coherent and manageable account.

The more we learn about cell signaling pathways, the less, paradoxically, we seem to understand. As the numbers of receptors, kinases, and G-proteins carrying signals increase and details of their protein structures, post-translational modifications and interconnections multiply, it becomes increasingly difficult to visualize any pathway as a whole. Of course, it can be argued that many, perhaps most, of...