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Efficient modeling, simulation and coarse-graining of biological complexity with NFsim

Nature Methods volume 8, pages 177–183 (2011)Cite this article

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Abstract

Managing the overwhelming numbers of molecular states and interactions is a fundamental obstacle to building predictive models of biological systems. Here we introduce the Network-Free Stochastic Simulator (NFsim), a general-purpose modeling platform that overcomes the combinatorial nature of molecular interactions. Unlike standard simulators that represent molecular species as variables in equations, NFsim uses a biologically intuitive representation: objects with binding and modification sites acted on by reaction rules. During simulations, rules operate directly on molecular objects to produce exact stochastic results with performance that scales independently of the reaction network size. Reaction rates can be defined as arbitrary functions of molecular states to provide powerful coarse-graining capabilities, for example to merge Boolean and kinetic representations of biological networks. NFsim enables researchers to simulate many biological systems that were previously inaccessible to general-purpose software, as we illustrate with models of immune system signaling, microbial signaling, cytoskeletal assembly and oscillating gene expression.

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Figure 1: Combinatorial complexity in multisite phosphorylation and NFsim performance scaling.
Figure 2: Schematic overview of NFsim.
Figure 3: Simulation performance and parameter estimation for receptor aggregation models.
Figure 4: Tracking molecular connectivity during simulation of cytoskeletal actin polymerization.
Figure 5: Coarse-graining with local and global functions.
Figure 6: Achieving multiple levels of resolution with conditional and functional rate-law expressions.

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Acknowledgements

We thank J. Berro, E. De La Cruz and T. Pollard for help with the actin assembly model, R. Gutenkunst, C. Henry, J. Hogg, G. Jentsch, W. Pontius and F. Xia for general testing, J. Hogg for assistance in extending BioNetGen, and R. Alexander, G. Altan-Bonnet, P. Cluzel, N. Frankel, L. Harris, W. Hlavacek and G. Jentsch for comments on the manuscript. Supported by the US National Science Foundation (CCF-0829836 to M.W.S. and T.E.; CCF-0829788 to J.R.F.).

Author information

Authors and Affiliations

  1. Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, Connecticut, USA

    Michael W Sneddon & Thierry Emonet

  2. Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, USA

    Michael W Sneddon & Thierry Emonet

  3. Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA

    James R Faeder

  4. Department of Physics, Yale University, New Haven, Connecticut, USA

    Thierry Emonet

Authors
  1. Michael W Sneddon
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Contributions

M.W.S. wrote the software and performed all simulations. M.W.S., J.R.F. and T.E. designed the algorithms and research and wrote the manuscript.

Corresponding author

Correspondence to Thierry Emonet.

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Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–7, Supplementary Tables 1–7 and Supplementary Notes 1–12 (PDF 1020 kb)

Supplementary Video 1

Unconstrained actin growth simulated with NFsim. Visualizations depict ATP-actin subunits (blue), ADP-Pi actin subunits (cyan), ADP actin subunits (red) and filament ends that are capped by capping protein (yellow). In this simulation, the concentration of the ADF/cofilin severing complex is set to zero, which allows the structure to continue rapid growth throughout the simulation. (MOV 2940 kb)

Supplementary Video 2

Actin growth in the presence of ADF/cofilin. Visualizations depict ATP-actin subunits (blue), ADP-Pi actin subunits (cyan), ADP actin subunits (red) and filament ends that are capped by capping protein (yellow). In this simulation, a steady-state regime is achieved where branching and polymerization reactions are compensated by the severing of filaments. Severed ends of the filament are discarded from the simulation so that only a single connected structure is followed over time. Notice that actin structures are typically small and consist of only a few filaments that are capped. Occasional stochastic events, however, allow periods of rapid growth and the transient formation of much larger structures. (MOV 2049 kb)

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Sneddon, M., Faeder, J. & Emonet, T. Efficient modeling, simulation and coarse-graining of biological complexity with NFsim. Nat Methods 8, 177–183 (2011). https://doi.org/10.1038/nmeth.1546

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