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Coarse-Grained Molecular Simulation of Diffusion and Reaction Kinetics in a Crowded Virtual Cytoplasm

Douglas Ridgway ^*, Gordon Broderick ^* , Ana Lopez-Campistrous ^*, Melania Ru'aini ^*, Philip Winter ^*, Matthew Hamilton , Pierre Boulanger , Andriy Kovalenko  and Michael J. Ellison ^* ¶

^* Institute for Biomolecular Design, Faculty of Medicine, and Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada; National Institute for Nanotechnology, Edmonton, Alberta, Canada; and ^¶ Department of Biochemistry, University of Alberta, Edmonton, Alberta, Canada

Correspondence: Address reprint requests to Michael J. Ellison, Institute for Biomolecular Design, University of Alberta, Edmonton, AB T6G 2H7, Canada. Tel.: 780-492-6352; Fax: 780-492-9394; E-mail: mike.ellison{at}ualberta.ca.

We present a general-purpose model for biomolecular simulations at the molecular level that incorporates stochasticity, spatial dependence, and volume exclusion, using diffusing and reacting particles with physical dimensions. To validate the model, we first established the formal relationship between the microscopic model parameters (timestep, move length, and reaction probabilities) and the macroscopic coefficients for diffusion and reaction rate. We then compared simulation results with Smoluchowski theory for diffusion-limited irreversible reactions and the best available approximation for diffusion-influenced reversible reactions. To simulate the volumetric effects of a crowded intracellular environment, we created a virtual cytoplasm composed of a heterogeneous population of particles diffusing at rates appropriate to their size. The particle-size distribution was estimated from the relative abundance, mass, and stoichiometries of protein complexes using an experimentally derived proteome catalog from Escherichia coli K12. Simulated diffusion constants exhibited anomalous behavior as a function of time and crowding. Although significant, the volumetric impact of crowding on diffusion cannot fully account for retarded protein mobility in vivo, suggesting that other biophysical factors are at play. The simulated effect of crowding on barnase-barstar dimerization, an experimentally characterized example of a bimolecular association reaction, reveals a biphasic time course, indicating that crowding exerts different effects over different timescales. These observations illustrate that quantitative realism in biosimulation will depend to some extent on mesoscale phenomena that are not currently well understood.