Integrin activation.
Ontology highlight
ABSTRACT:
SUBMITTER: Ginsberg MH
PROVIDER: S-EPMC4345508 | biostudies-literature | 2014 Dec
REPOSITORIES: biostudies-literature
Publications
Integrin-mediated cell adhesion is important for development, immune responses, hemostasis and wound healing. Integrins also function as signal transducing receptors that can control intracellular pathways that regulate cell survival, proliferation, and cell fate. Conversely, cells can modulate the affinity of integrins for their ligands a process operationally defined as integrin activation. Analysis of activation of integrins has now provided a detailed molecular understanding of this unique f ...[more]
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Project description:Geier2011 - Integrin activation
Rule based model that integrates the available data to test the biololical hypotheses regarding the role of talin, Dok1 and PIPKI in integrin activation.
This model is described in the article:
A computational analysis of the dynamic roles of talin, Dok1, and PIPKI for integrin activation.
Geier F, Fengos G, Iber D.
PLoS One. 2011;6(11):e24808.
Abstract:
Integrin signaling regulates cell migration and plays a pivotal role in developmental processes and cancer metastasis. Integrin signaling has been studied extensively and much data is available on pathway components and interactions. Yet the data is fragmented and an integrated model is missing. We use a rule-based modeling approach to integrate available data and test biological hypotheses regarding the role of talin, Dok1 and PIPKI in integrin activation. The detailed biochemical characterization of integrin signaling provides us with measured values for most of the kinetics parameters. However, measurements are not fully accurate and the cellular concentrations of signaling proteins are largely unknown and expected to vary substantially across different cellular conditions. By sampling model behaviors over the physiologically realistic parameter range we find that the model exhibits only two different qualitative behaviors and these depend mainly on the relative protein concentrations, which offers a powerful point of control to the cell. Our study highlights the necessity to characterize model behavior not for a single parameter optimum, but to identify parameter sets that characterize different signaling modes.
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2014-03-05 | MODEL1208280001 | BioModels
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