Specification, annotation, visualization and simulation of a large rule-based model for ERBB receptor signaling

Matthew S. Creamer, Edward C. Stites, Meraj Aziz, James A. Cahill, Chin W. Tan, Michael E. Berens, Haiyong Han, Kimberley J. Bussey, Daniel D. Von Hoff, William S. Hlavacek, Richard G Posner

Research output: Contribution to journalArticle

23 Citations (Scopus)

Abstract

Background: Mathematical/computational models are needed to understand cell signaling networks, which are complex. Signaling proteins contain multiple functional components and multiple sites of post-translational modification. The multiplicity of components and sites of modification ensures that interactions among signaling proteins have the potential to generate myriad protein complexes and post-translational modification states. As a result, the number of chemical species that can be populated in a cell signaling network, and hence the number of equations in an ordinary differential equation model required to capture the dynamics of these species, is prohibitively large. To overcome this problem, the rule-based modeling approach has been developed for representing interactions within signaling networks efficiently and compactly through coarse-graining of the chemical kinetics of molecular interactions.Results: Here, we provide a demonstration that the rule-based modeling approach can be used to specify and simulate a large model for ERBB receptor signaling that accounts for site-specific details of protein-protein interactions. The model is considered large because it corresponds to a reaction network containing more reactions than can be practically enumerated. The model encompasses activation of ERK and Akt, and it can be simulated using a network-free simulator, such as NFsim, to generate time courses of phosphorylation for 55 individual serine, threonine, and tyrosine residues. The model is annotated and visualized in the form of an extended contact map.Conclusions: With the development of software that implements novel computational methods for calculating the dynamics of large-scale rule-based representations of cellular signaling networks, it is now possible to build and analyze models that include a significant fraction of the protein interactions that comprise a signaling network, with incorporation of the site-specific details of the interactions. Modeling at this level of detail is important for understanding cellular signaling.

Original languageEnglish (US)
Article number107
JournalBMC Systems Biology
Volume6
DOIs
StatePublished - Aug 22 2012

Fingerprint

Receptor
Annotation
Visualization
Cell signaling
Specification
Specifications
Proteins
Post Translational Protein Processing
Simulation
Protein
Interaction
Model
Threonine
Serine
Tyrosine
Phosphorylation
Molecular interactions
Modeling
Theoretical Models
Software

Keywords

  • Epidermal growth factor (EGF) receptor (EGFR)
  • Rule-based modeling
  • Systems biology
  • Temporal phosphoproteomics

ASJC Scopus subject areas

  • Molecular Biology
  • Structural Biology
  • Applied Mathematics
  • Modeling and Simulation
  • Computer Science Applications

Cite this

Specification, annotation, visualization and simulation of a large rule-based model for ERBB receptor signaling. / Creamer, Matthew S.; Stites, Edward C.; Aziz, Meraj; Cahill, James A.; Tan, Chin W.; Berens, Michael E.; Han, Haiyong; Bussey, Kimberley J.; Von Hoff, Daniel D.; Hlavacek, William S.; Posner, Richard G.

In: BMC Systems Biology, Vol. 6, 107, 22.08.2012.

Research output: Contribution to journalArticle

Creamer, MS, Stites, EC, Aziz, M, Cahill, JA, Tan, CW, Berens, ME, Han, H, Bussey, KJ, Von Hoff, DD, Hlavacek, WS & Posner, RG 2012, 'Specification, annotation, visualization and simulation of a large rule-based model for ERBB receptor signaling', BMC Systems Biology, vol. 6, 107. https://doi.org/10.1186/1752-0509-6-107
Creamer, Matthew S. ; Stites, Edward C. ; Aziz, Meraj ; Cahill, James A. ; Tan, Chin W. ; Berens, Michael E. ; Han, Haiyong ; Bussey, Kimberley J. ; Von Hoff, Daniel D. ; Hlavacek, William S. ; Posner, Richard G. / Specification, annotation, visualization and simulation of a large rule-based model for ERBB receptor signaling. In: BMC Systems Biology. 2012 ; Vol. 6.
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AU - Tan, Chin W.

AU - Berens, Michael E.

AU - Han, Haiyong

AU - Bussey, Kimberley J.

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AU - Hlavacek, William S.

AU - Posner, Richard G

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KW - Systems biology

KW - Temporal phosphoproteomics

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