Literature DB >> 16045939

Signal transduction networks: topology, response and biochemical processes.

Orkun S Soyer1, Marcel Salathé, Sebastian Bonhoeffer.   

Abstract

Conventionally, biological signal transduction networks are analysed using experimental and theoretical methods to describe specific protein components, interactions, and biochemical processes and to model network behavior under various conditions. While these studies provide crucial information on specific networks, this information is not easily converted to a broader understanding of signal transduction systems. Here, using a specific model of protein interaction we analyse small network topologies to understand their response and general properties. In particular, we catalogue the response for all possible topologies of a given network size to generate a response distribution, analyse the effects of specific biochemical processes on this distribution, and analyse the robustness and diversity of responses with respect to internal fluctuations or mutations in the network. The results show that even three- and four-protein networks are capable of creating diverse and biologically relevant responses, that the distribution of response types changes drastically as a function of biochemical processes at protein level, and that certain topologies strongly pre-dispose a specific response type while others allow for diverse types of responses. This study sheds light on the response types and properties that could be expected from signal transduction networks, provides possible explanations for the role of certain biochemical processes in signal transduction and suggests novel approaches to interfere with signaling pathways at the molecular level. Furthermore it shows that network topology plays a key role on determining response type and properties and that proper representation of network topology is crucial to discover and understand so-called building blocks of large networks.

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Year:  2005        PMID: 16045939     DOI: 10.1016/j.jtbi.2005.05.030

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  15 in total

1.  Control of Streptococcus pyogenes virulence: modeling of the CovR/S signal transduction system.

Authors:  Alexander Y Mitrophanov; Gordon Churchward; Mark Borodovsky
Journal:  J Theor Biol       Date:  2006-11-21       Impact factor: 2.691

2.  Evolution of complexity in signaling pathways.

Authors:  Orkun S Soyer; Sebastian Bonhoeffer
Journal:  Proc Natl Acad Sci U S A       Date:  2006-10-23       Impact factor: 11.205

3.  Global mapping of gene/protein interactions in PubMed abstracts: a framework and an experiment with P53 interactions.

Authors:  Xin Li; Hsinchun Chen; Zan Huang; Hua Su; Jesse D Martinez
Journal:  J Biomed Inform       Date:  2007-01-17       Impact factor: 6.317

4.  Adaptive dynamics with a single two-state protein.

Authors:  Attila Csikász-Nagy; Orkun S Soyer
Journal:  J R Soc Interface       Date:  2008-08-06       Impact factor: 4.118

5.  BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling.

Authors:  Song Feng; Julien F Ollivier; Peter S Swain; Orkun S Soyer
Journal:  Nucleic Acids Res       Date:  2015-06-22       Impact factor: 16.971

6.  Artemisinin attenuated ischemic stroke induced cell apoptosis through activation of ERK1/2/CREB/BCL-2 signaling pathway in vitro and in vivo.

Authors:  Tangming Peng; Shuai Li; Linlin Liu; Chao Yang; Mohd Farhan; Ligang Chen; Qiaozhu Su; Wenhua Zheng
Journal:  Int J Biol Sci       Date:  2022-07-11       Impact factor: 10.750

Review 7.  Sirtuins-Mediated System-Level Regulation of Mammalian Tissues at the Interface between Metabolism and Cell Cycle: A Systematic Review.

Authors:  Parcival Maissan; Eva J Mooij; Matteo Barberis
Journal:  Biology (Basel)       Date:  2021-03-04

8.  Ground state robustness as an evolutionary design principle in signaling networks.

Authors:  Onder Kartal; Oliver Ebenhöh
Journal:  PLoS One       Date:  2009-12-01       Impact factor: 3.240

9.  Branched motifs enable long-range interactions in signaling networks through retrograde propagation.

Authors:  Tharmaraj Jesan; Uddipan Sarma; Subhadra Halder; Bhaskar Saha; Sitabhra Sinha
Journal:  PLoS One       Date:  2013-05-31       Impact factor: 3.240

10.  A framework for evolutionary systems biology.

Authors:  Laurence Loewe
Journal:  BMC Syst Biol       Date:  2009-02-24
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