FAST MONTE CARLO SIMULATION METHODS FOR BIOLOGICAL REACTION-DIFFUSION SYSTEMS IN SOLUTION AND ON SURFACES.
Many important physiological processes operate at time and space scales far beyond those accessible to atom-realistic simulations, and yet discrete stochastic rather than continuum methods may best represent finite numbers of molecules interacting in complex cellular spaces. We describe and validate new tools and algorithms developed for a new version of the MCell simulation program (MCell3), which supports generalized Monte Carlo modeling of diffusion and chemical reaction in solution, on surfaces representing membranes, and combinations thereof. A new syntax for describing the spatial directionality of surface reactions is introduced, along with optimizations and algorithms that can substantially reduce computational costs (e.g., event scheduling, variable time and space steps). Examples for simple reactions in simple spaces are validated by comparison to analytic solutions. Thus we show how spatially realistic Monte Carlo simulations of biological systems can be far more cost-effective than often is assumed, and provide a level of accuracy and insight beyond that of continuum methods.
HHMI Janelia Farm Research Campus, Ashburn, VA 20147 and Computational Neurobiology Laboratory, The Salk Institute, La Jolla, CA 92037. This author was supported by grants NIH R01 GM069630, NIH P01-NS044306, NSF PHY-0216576, and PHY-0225630 and by HHMI.
Rex A
RA
Kerr
Thomas M
TM
Bartol
Boris
B
Kaminsky
Markus
M
Dittrich
Jen-Chien Jack
JC
Chang
Scott B
SB
Baden
Terrence J
TJ
Sejnowski
Joel R
JR
Stiles