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. 2015 Jul 15;31(14):2406-8.
doi: 10.1093/bioinformatics/btv149. Epub 2015 Mar 18.

Multiscale reaction-diffusion simulations with Smoldyn

Martin Robinson  1 , Steven S Andrews  2 , Radek Erban  1
Affiliations

Multiscale reaction-diffusion simulations with Smoldyn

Martin Robinson et al. Bioinformatics. .

Abstract

Smoldyn is a software package for stochastic modelling of spatial biochemical networks and intracellular systems. It was originally developed with an accurate off-lattice particle-based model at its core. This has recently been enhanced with the addition of a computationally efficient on-lattice model, which can be run stand-alone or coupled together for multiscale simulations using both models in regions where they are most required, increasing the applicability of Smoldyn to larger molecule numbers and spatial domains. Simulations can switch between models with only small additions to their configuration file, enabling users with existing Smoldyn configuration files to run the new on-lattice model with any reaction, species or surface descriptions they might already have.

Availability and implementation: Source code and binaries freely available for download at www.smoldyn.org, implemented in C/C++ and supported on Linux, Mac OSX and MS Windows.

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Figures

Fig. 1.
Fig. 1.
(a) Multiscale Smoldyn simulation of yeast signalling between haploid Saccharomyces cerevisiae of opposite mating types (MATa and MATα; Andrews et al., 2010). The centre region contains a detailed off-lattice model of several MATa and MATα cells, which is coupled to a coarse on-lattice model to describe the diffusion and interaction of a pheromone (α-factor) and a pheromone-degrading protease (Bar1) within the surrounding environment. (b) Speed-up versus lattice spacing h that can be achieved by using the on-lattice model for the bulk of the domain (speed-up equals 1 for a purely off-lattice simulation). The simulation domain is a 100 × 100 × 100 μm cube with an absorbing boundary. The gradient of bound α-factor across the central cell (a measure of simulation accuracy) did not vary with h over the range considered, and the mean was within 1% of that obtained from the purely off-lattice simulation
See this image and copyright information in PMC

References

    1. Andrews S.S. (2012) Spatial and stochastic cellular modeling with the smoldyn simulator. In: van Helden, et al. (eds.). Bacterial Molecular Networks: Methods and Protocols, Methods in Molecular Biology, vol. 804, pp. 519–542. - PubMed
    1. Andrews S.S., Bray D. (2004) Stochastic simulation of chemical reactions with spatial resolution and single molecule detail. Phys. Biol., 1, 137. - PubMed
    1. Andrews S.S., et al. (2010) Detailed simulations of cell biology with smoldyn 2.1. PLoS Comput. Biol., 6, e1000705. - PMC - PubMed
    1. Elf J., Ehrenberg M. (2004) Spontaneous separation of bi-stable biochemical systems into spatial domains of opposite phases. Syst. Biol., 1, 230–236. - PubMed
    1. Erban R., et al. (2014) Multiscale stochastic reaction–diffusion modeling: application to actin dynamics in filopodia. Bull. Math. Biol., 76,799–818. - PubMed

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