The specification of SBML Level 1 is freely available from http://www.sbml.org/

Methods are presented for simulating chemical reaction networks with a spatial resolution that is accurate to nearly the size scale of individual molecules. Using an intuitive picture of chemical reaction systems, each molecule is treated as a point-like particle that diffuses freely in three-dimensional space. When a pair of reactive molecules collide, such as an enzyme and its substrate, a reaction occurs and the simulated reactants are replaced by products. Achieving accurate bimolecular reaction kinetics is surprisingly difficult, requiring a careful consideration of reaction processes that are often overlooked. This includes whether the rate of a reaction is at steady-state and the probability that multiple reaction products collide with each other to yield a back reaction. Inputs to the simulation are experimental reaction rates, diffusion coefficients and the simulation time step. From these are calculated the simulation parameters, including the 'binding radius' and the 'unbinding radius', where the former defines the separation for a molecular collision and the latter is the initial separation between a pair of reaction products. Analytic solutions are presented for some simulation parameters while others are calculated using look-up tables. Capabilities of these methods are demonstrated with simulations of a simple bimolecular reaction and the Lotka-Volterra system.

B cells recognize foreign antigens by virtue of cell surface immunoglobulin receptors and are most effectively activated by membrane-bound ligands. Here, we show that in the early stages of this process, B cells exhibit a two-phase response in which they first spread over the antigen-bearing membrane and then contract, thereby collecting bound antigen into a central aggregate. The extent of this response, which is both signaling- and actin-dependent, determines the quantity of antigen accumulated and hence the degree of B cell activation. Brownian dynamic simulations reproduce essential features of the antigen collection process and suggest a possible basis for affinity discrimination. We propose that dynamic spreading is an important step of the immune response.

Chemotactic bacteria such as Escherichia coli can detect and respond to extremely low concentrations of attractants, concentrations of less than 5 nM in the case of aspartate. They also sense gradients of attractants extending over five orders of magnitude in concentration (up to 1 mM aspartate). Here we consider the possibility that this combination of sensitivity and range of response depends on the clustering of chemotactic receptors on the surface of the bacterium. We examine what will happen if ligand binding changes the activity of a receptor, propagating this change in activity to neighbouring receptors in a cluster. Calculations based on these assumptions show that sensitivity to extracellular ligands increases with the extent of spread of activity through an array of receptors, but that the range of concentrations over which the array works is severely diminished. However, a combination of low threshold of response and wide dynamic range can be attained if the cell has both clusters and single receptors on its surface, particularly if the extent of activity spread can adapt to external conditions. A mechanism of this kind can account quantitatively for the sensitivity and response range of E. coli to aspartate.

Many proteins in living cells appear to have as their primary function the transfer and processing of information, rather than the chemical transformation of metabolic intermediates or the building of cellular structures. Such proteins are functionally linked through allosteric or other mechanisms into biochemical 'circuits' that perform a variety of simple computational tasks including amplification, integration and information storage.

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A concerted flow of actin filaments associated with the inner face of the plasma membrane may provide the basis for many animal cell movements. The flow is driven by gradients of tension in the cell cortex, which pull cortical components from regions of relaxation to regions of contraction. In some cases cortical components return through the cytoplasm to establish a continuous cycle. This cortically located motor may drive cell locomotion, growth cone migration, the capping of antigens on a lymphocyte surface, and cytokinesis.

No abstract