Literature DB >> 19894929

A diffusional bimolecular propensity function.

Daniel T Gillespie1.   

Abstract

We derive an explicit formula for the propensity function (stochastic reaction rate) of a generic bimolecular chemical reaction in which the reactant molecules move about by diffusion, as solute molecules in a bath of much smaller and more numerous solvent molecules. Our derivation assumes that the solution is macroscopically well stirred and dilute in the solute molecules. It effectively extends the physical rationale for the chemical master equation and the stochastic simulation algorithm from well-stirred dilute gases to well-stirred dilute solutions, with the former becoming a limiting case of the latter. This extension is important for cellular systems, where the solvent molecules are typically water and the solute (reactant) molecules are much larger organic structures, whose relatively low populations often require a discrete-stochastic formalism. In the course of our derivation, we illuminate some limitations on the ability of the classical diffusion equation to accurately describe how a diffusing molecule moves on spatial and temporal scales that are relevant to collision-induced chemical reactions.

Entities:  

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Year:  2009        PMID: 19894929      PMCID: PMC2780463          DOI: 10.1063/1.3253798

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  2 in total

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Journal:  J Phys Chem B       Date:  2009-02-12       Impact factor: 2.991

  2 in total
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2.  Constant-complexity stochastic simulation algorithm with optimal binning.

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3.  State Space Truncation with Quantified Errors for Accurate Solutions to Discrete Chemical Master Equation.

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4.  Reaction rates for mesoscopic reaction-diffusion kinetics.

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Journal:  J Chem Phys       Date:  2012-08-28       Impact factor: 3.488

7.  Perspective: Stochastic algorithms for chemical kinetics.

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Journal:  J Chem Phys       Date:  2013-05-07       Impact factor: 3.488

8.  Mesoscopic-microscopic spatial stochastic simulation with automatic system partitioning.

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Review 9.  Mapping the architecture of the HIV-1 Tat circuit: A decision-making circuit that lacks bistability and exploits stochastic noise.

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10.  ACCURATE CHEMICAL MASTER EQUATION SOLUTION USING MULTI-FINITE BUFFERS.

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