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PMID: 17397255 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Potential energy landscape and robustness of a gene regulatory network: toggle switch.

PLoS computational biology ·Vol. 3 ·No. 3 ·2007-03-30 ·Pages e60

Kim KY, Wang J

Abstract

Finding a multidimensional potential landscape is the key for addressing important global issues, such as the robustness of cellular networks. We have uncovered the underlying potential energy landscape of a simple gene regulatory network: a toggle switch. This was realized by explicitly constructing the steady state probability of the gene switch in the protein concentration space in the presence of the intrinsic statistical fluctuations due to the small number of proteins in the cell. We explored the global phase space for the system. We found that the protein synthesis rate and the unbinding rate of proteins to the gene were small relative to the protein degradation rate; the gene switch is monostable with only one stable basin of attraction. When both the protein synthesis rate and the unbinding rate of proteins to the gene are large compared with the protein degradation rate, two global basins of attraction emerge for a toggle switch. These basins correspond to the biologically stable functional states. The potential energy barrier between the two basins determines the time scale of conversion from one to the other. We found as the protein synthesis rate and protein unbinding rate to the gene relative to the protein degradation rate became larger, the potential energy barrier became larger. This also corresponded to systems with less noise or the fluctuations on the protein numbers. It leads to the robustness of the biological basins of the gene switches. The technique used here is general and can be applied to explore the potential energy landscape of the gene networks.

MeSH Terms
Computer Simulation Energy Metabolism/physiology Gene Expression Regulation/physiology Logistic Models Models, Biological Proteome/metabolism Signal Transduction/physiology
Chemicals
Proteome
Authors & Affiliations
2 authors, click to expand affiliations / ORCID
Kim Keun-Young
Department of Physics and Astronomy, State University of New York Stony Brook, Stony Brook, New York, United States of America.
Wang Jin
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Article Info
Journal
PLoS computational biology
Abbr.
PLoS Comput Biol
ISSN
1553-7358
Published
2007-03-30
Epub
2007-00-14
Pages
e60
Language
English
Region
United States
NLM ID
101238922
PMCID
PMC1848002
Subset
IM
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