FAST MONTE CARLO SIMULATION METHODS FOR BIOLOGICAL REACTION-DIFFUSION SYSTEMS IN SOLUTION AND ON SURFACES

By Rex A. Kerr, T. Bartol, B. Kaminsky, Markus Dittrich, Jen-Chien Chang, S. Baden, Terrence J. Sejnowski, J. Stiles. SIAM Journal on Scientific Computing, 2008

339 citations recorded by the source corpus.

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.

Subfields: Biophysics, Molecular Biology, Physical and Theoretical Chemistry

View Paper: https://www.semanticscholar.org/paper/3e20065599bba55cc9ea99cf586e9dd0ff157453

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In Biophysics

1. Adam P. Arkin

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3. Steven S. Andrews
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Citations in the corpus

• Weighted Ensemble Simulation: Review of Methodology, Applications, and Software (2017, neutral): “To our knowledge, the first freely available, highly scalable, and interoperable WE software package was WESTPA (74), which has been widely applied to a variety of systems ranging in scale from atomistic to cellular (2–4, 21, 22, 59, 62, 63, 75, 76) and interfaced with a diversity of dynamics engine”
• Detailed Simulations of Cell Biology with Smoldyn 2.1 (2010, background): “As Table 2 shows, Smoldyn took 47 s to run this test (on a MacBook Pro laptop with a 2.33 GHz Intel Core 2 Duo processor and OS 10.4.11, and with single-threaded operation), which was more than a factor of 2 faster than either ChemCell or MCell.”