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Automatic generation of cellular reaction networks with Moleculizer 1.0

Nature Biotechnology volume 23, pages 131–136 (2005)Cite this article

Abstract

Accurate simulation of intracellular biochemical networks is essential to furthering our understanding of biological system behavior. The number of protein complexes and of chemical interactions among them has traditionally posed significant problems for simulation algorithms. Here we describe an approach to the exact stochastic simulation of biochemical networks that emphasizes the contribution of protein complexes to these systems. This simulation approach starts from a description of monomeric proteins and specifications for binding, unbinding and other reactions. This manageable specification is reasonably intuitive for biologists. Rather than requiring the inclusion of all possible complexes and reactions from the outset, our approach incorporates new complexes and reactions only when needed as the simulation proceeds. As a result, the simulation generates much smaller reaction networks, which can be exported to other simulators for further analysis. We apply this approach to the automatic generation of reaction systems for the study of signal transduction networks.

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Figure 1: Reaction network generation cycle.
Figure 2: Dimerization example.
Figure 3: 'Runaway' polymerization.
Figure 4: Illustrative simulation output.

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Acknowledgements

L.L. conceived, designed and programmed Moleculizer. R.B. started and fostered the program of quantitative biological inquiry that enabled the development of Moleculizer and helped frame explanations of the work for biologists. L.L. and R.B. wrote the manuscript and stand as guarantors of its veracity. The work was supported by a grant from the US Defense Advanced Research Projects Agency and by the “Alpha Project” at the Center for Genomic Experimentation and Computation, a National Institutes of Health Center of Excellence in Genomic Science. The Alpha Project is supported by grant P50 HG02370 to R.B. from the National Human Genome Research Institute.

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Authors and Affiliations

  1. The Molecular Sciences Institute, 2168 Shattuck Avenue, Berkeley, 94704, California, USA

    Larry Lok & Roger Brent

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  1. Larry Lok
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Correspondence to Larry Lok.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Fig. 1

An intentional combinatorial explosion generating many species of complexes. (PDF 42 kb)

Supplementary Fig. 2

Use of reperesentation–invariant hash (PDF 34 kb)

Supplementary Fig. 3

Major components of the alpha signal transduction pathway in yeast. (PDF 48 kb)

Supplementary Table 1

Performance effects of species and reaction generation on simulation of receptor part of the alpha pathway. (PDF 51 kb)

Supplementary Table 2

Performance effects of species and reaction generation on “full” alpha pathway simulation. (PDF 37 kb)

Supplementary Table 3

Main executables delivered with Moleculizer 1.0. (PDF 39 kb)

Supplementary Table 4

File formats connected with Moleculizer 1.0. (PDF 48 kb)

Supplementary Notes (PDF 247 kb)

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Lok, L., Brent, R. Automatic generation of cellular reaction networks with Moleculizer 1.0. Nat Biotechnol 23, 131–136 (2005). https://doi.org/10.1038/nbt1054

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