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

被引:236
作者
Kerr, Rex A. [1 ,2 ]
Bartol, Thomas M. [2 ]
Kaminsky, Boris [4 ]
Dittrich, Markus [4 ]
Chang, Jen-Chien Jack [4 ]
Baden, Scott B. [5 ]
Sejnowski, Terrence J. [3 ]
Stiles, Joel R. [4 ,6 ]
机构
[1] HHMI, Ashburn, VA 20147 USA
[2] Salk Inst Biol Studies, Computat Neurobiol Lab, La Jolla, CA 92037 USA
[3] Univ Calif San Diego, Ctr Theoret Biol Phys, Div Biol Sci, La Jolla, CA 92093 USA
[4] Pittsburgh Supercomp Ctr, Pittsburgh, PA 15213 USA
[5] Univ Calif San Diego, Dept Comp Sci & Engn, La Jolla, CA 92093 USA
[6] Carnegie Mellon Univ, Mellon Coll Sci, Pittsburgh, PA 15213 USA
关键词
MCell; DReAMM; Monte Carlo; cell simulation; reaction-diffusion; concentration clamp; microscopic reversibility;
D O I
10.1137/070692017
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
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.
引用
收藏
页码:3126 / 3149
页数:24
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