  Many cellular and subcellular biological processes can be described in terms
of diffusing and chemically reacting species (e.g. enzymes). Such
reaction-diffusion processes can be mathematically modelled using either
deterministic partial-differential equations or stochastic simulation
algorithms. The latter provide a more detailed and precise picture, and several
stochastic simulation algorithms have been proposed in recent years. Such
models typically give the same description of the reaction-diffusion processes
far from the boundary of the simulated domain, but the behaviour close to a
reactive boundary (e.g. a membrane with receptors) is unfortunately
model-dependent. In this paper, we study four different approaches to
stochastic modelling of reaction-diffusion problems and show the correct choice
of the boundary condition for each model. The reactive boundary is treated as
partially reflective, which means that some molecules hitting the boundary are
adsorbed (e.g. bound to the receptor) and some molecules are reflected. The
probability that the molecule is adsorbed rather than reflected depends on the
reactivity of the boundary (e.g. on the rate constant of the adsorbing chemical
reaction and on the number of available receptors), and on the stochastic model
used. This dependence is derived for each model.
