Validity conditions for stochastic chemical kinetics in diffusion-limited systems.

The chemical master equation (CME) and the mathematically equivalent stochastic simulation algorithm (SSA) assume that the reactant molecules in a chemically reacting system are "dilute" and "well-mixed" throughout the containing volume. Here we clarify what those two conditions mean, and we show why their satisfaction is necessary in order for bimolecular reactions to physically occur in the manner assumed by the CME and the SSA. We prove that these conditions are closely connected, in that a system will stay well-mixed if and only if it is dilute. We explore the implications of these validity conditions for the reaction-diffusion (or spatially inhomogeneous) extensions of the CME and the SSA to systems whose containing volumes are not necessarily well-mixed, but can be partitioned into cubical subvolumes (voxels) that are. We show that the validity conditions, together with an additional condition that is needed to ensure the physical validity of the diffusion-induced jump probability rates of molecules between voxels, require the voxel edge length to have a strictly positive lower bound. We prove that if the voxel edge length is steadily decreased in a way that respects that lower bound, the average rate at which bimolecular reactions occur in the reaction-diffusion CME and SSA will remain constant, while the average rate of diffusive transfer reactions will increase as the inverse square of the voxel edge length. We conclude that even though the reaction-diffusion CME and SSA are inherently approximate, and cannot be made exact by shrinking the voxel size to zero, they should nevertheless be useful in many practical situations.

[1]  Daniel T. Gillespie,et al.  Simulation Methods in Systems Biology , 2008, SFM.

[2]  D. Gillespie,et al.  A diffusional bimolecular propensity function. , 2009, The Journal of chemical physics.

[3]  Samuel A. Isaacson,et al.  The Reaction-Diffusion Master Equation as an Asymptotic Approximation of Diffusion to a Small Target , 2009, SIAM J. Appl. Math..

[4]  P. R. ten Wolde,et al.  Spatio-temporal correlations can drastically change the response of a MAPK pathway , 2009, Proceedings of the National Academy of Sciences.

[5]  A. M. Berezhkovskii,et al.  Irreversible bimolecular reactions of Langevin particles , 2001 .

[6]  Gillespie,et al.  Exact numerical simulation of the Ornstein-Uhlenbeck process and its integral. , 1996, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[7]  J. Elf,et al.  Stochastic reaction-diffusion kinetics in the microscopic limit , 2010, Proceedings of the National Academy of Sciences.

[8]  L. Petzold,et al.  Reaction-diffusion master equation in the microscopic limit. , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[9]  S. Schnell,et al.  Modelling reaction kinetics inside cells. , 2008, Essays in biochemistry.

[10]  R. Erban,et al.  Stochastic modelling of reaction–diffusion processes: algorithms for bimolecular reactions , 2009, Physical biology.

[11]  D. Gillespie A rigorous derivation of the chemical master equation , 1992 .

[12]  宁北芳,et al.  疟原虫var基因转换速率变化导致抗原变异[英]/Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A , 2005 .

[13]  D. Gillespie A General Method for Numerically Simulating the Stochastic Time Evolution of Coupled Chemical Reactions , 1976 .

[14]  George E. Kimball,et al.  Diffusion-controlled reaction rates , 1949 .

[15]  D. Gillespie Exact Stochastic Simulation of Coupled Chemical Reactions , 1977 .

[16]  K. McNeil,et al.  Correlations in stochastic theories of chemical reactions , 1976 .