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Spatio-temporal modeling of signaling protein recruitment to EGFR.

Hsieh MY, Yang S, Raymond-Stinz MA, Edwards JS, Wilson BS - BMC Syst Biol (2010)

Bottom Line: The agent-based and rule-based approach permits consideration of combinatorial complexity, a problem associated with multiple phosphorylation sites and the potential for simultaneous binding of adaptors.Simultaneous docking of multiple proteins is highly dependent on receptor-adaptor stability and independent of clustering.Overall, we propose that receptor density, reaction kinetics and membrane spatial organization all contribute to signaling efficiency and influence the carcinogenesis process.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Molecular Genetics and Microbiology, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA.

ABSTRACT

Background: A stochastic simulator was implemented to study EGFR signal initiation in 3D with single molecule detail. The model considers previously unexplored contributions to receptor-adaptor coupling, such as receptor clustering and diffusive properties of both receptors and binding partners. The agent-based and rule-based approach permits consideration of combinatorial complexity, a problem associated with multiple phosphorylation sites and the potential for simultaneous binding of adaptors.

Results: The model was used to simulate recruitment of four different signaling molecules (Grb2, PLCgamma1, Stat5, Shc) to the phosphorylated EGFR tail, with rules based on coarse-grained prediction of spatial constraints. Parameters were derived in part from quantitative immunoblotting, immunoprecipitation and electron microscopy data. Results demonstrate that receptor clustering increases the efficiency of individual adaptor retainment on activated EGFR, an effect that is overridden if crowding is imposed by receptor overexpression. Simultaneous docking of multiple proteins is highly dependent on receptor-adaptor stability and independent of clustering.

Conclusions: Overall, we propose that receptor density, reaction kinetics and membrane spatial organization all contribute to signaling efficiency and influence the carcinogenesis process.

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Comparison of the sharing and competing docking models. Simulations in (A-B) used the parameter values fitted to A431 cells data, while simulations in (C) used Kholodenko's parameter values [36]. (A) Results of simulations show similar number of adaptors docked to EGFR at steady state, when receptors are overexpressed and clustered. (B) Results of simulations for sharing and competing models at steady state, when receptors are at normal expression levels (50,000 receptors/cell) and either clustered or random. Receptor clustering increases the efficiency of adaptor retainment to EGFR, but sharing does not contribute further efficiency. (C) Results show that use of slow dissociation rates produces a dramatic increase in the shared docking of adaptors on EGFR tails, simulated for 50,000 clustered receptors in the spatial-stochastic model.
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Figure 5: Comparison of the sharing and competing docking models. Simulations in (A-B) used the parameter values fitted to A431 cells data, while simulations in (C) used Kholodenko's parameter values [36]. (A) Results of simulations show similar number of adaptors docked to EGFR at steady state, when receptors are overexpressed and clustered. (B) Results of simulations for sharing and competing models at steady state, when receptors are at normal expression levels (50,000 receptors/cell) and either clustered or random. Receptor clustering increases the efficiency of adaptor retainment to EGFR, but sharing does not contribute further efficiency. (C) Results show that use of slow dissociation rates produces a dramatic increase in the shared docking of adaptors on EGFR tails, simulated for 50,000 clustered receptors in the spatial-stochastic model.

Mentions: Rate constants were next derived by parameter fitting using the Potters Wheel toolbox, building on the parameters established for phosphorylation kinetics in Figure 2. Because this is an ODE-based approach that assumes a well-mixed chemical system, the docking rate constants were multiplied by a scaling factor (f in equation 3) prior to testing for fitness in our agent-based, spatially heterogeneous model. In simulations, the extracellular domain of the model was populated with 20 nM EGF, the simulated membrane expressed 1592 EGFR, and the intracellular domain contained either 56 Grb2, 55 Shc, 59 Stat5 or 154 PLCĪ³1. Simulations were run for each of the four adaptors individually and parameters adjusted to match the experimental data (Figure 3J-M). The docking and dissociation rate constants arrived at for each protein using this computational method are reported in Table 2. Note that these values are similar to those predicted by single particle methods [32] but that the dissociation rate constants are significantly faster than previously used in deterministic models. As discussed in the context of Figure 5C, this has a large impact on the spatial simulation outcome and experimental verification is a priority for our future work.


Spatio-temporal modeling of signaling protein recruitment to EGFR.

Hsieh MY, Yang S, Raymond-Stinz MA, Edwards JS, Wilson BS - BMC Syst Biol (2010)

Comparison of the sharing and competing docking models. Simulations in (A-B) used the parameter values fitted to A431 cells data, while simulations in (C) used Kholodenko's parameter values [36]. (A) Results of simulations show similar number of adaptors docked to EGFR at steady state, when receptors are overexpressed and clustered. (B) Results of simulations for sharing and competing models at steady state, when receptors are at normal expression levels (50,000 receptors/cell) and either clustered or random. Receptor clustering increases the efficiency of adaptor retainment to EGFR, but sharing does not contribute further efficiency. (C) Results show that use of slow dissociation rates produces a dramatic increase in the shared docking of adaptors on EGFR tails, simulated for 50,000 clustered receptors in the spatial-stochastic model.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2877007&req=5

Figure 5: Comparison of the sharing and competing docking models. Simulations in (A-B) used the parameter values fitted to A431 cells data, while simulations in (C) used Kholodenko's parameter values [36]. (A) Results of simulations show similar number of adaptors docked to EGFR at steady state, when receptors are overexpressed and clustered. (B) Results of simulations for sharing and competing models at steady state, when receptors are at normal expression levels (50,000 receptors/cell) and either clustered or random. Receptor clustering increases the efficiency of adaptor retainment to EGFR, but sharing does not contribute further efficiency. (C) Results show that use of slow dissociation rates produces a dramatic increase in the shared docking of adaptors on EGFR tails, simulated for 50,000 clustered receptors in the spatial-stochastic model.
Mentions: Rate constants were next derived by parameter fitting using the Potters Wheel toolbox, building on the parameters established for phosphorylation kinetics in Figure 2. Because this is an ODE-based approach that assumes a well-mixed chemical system, the docking rate constants were multiplied by a scaling factor (f in equation 3) prior to testing for fitness in our agent-based, spatially heterogeneous model. In simulations, the extracellular domain of the model was populated with 20 nM EGF, the simulated membrane expressed 1592 EGFR, and the intracellular domain contained either 56 Grb2, 55 Shc, 59 Stat5 or 154 PLCĪ³1. Simulations were run for each of the four adaptors individually and parameters adjusted to match the experimental data (Figure 3J-M). The docking and dissociation rate constants arrived at for each protein using this computational method are reported in Table 2. Note that these values are similar to those predicted by single particle methods [32] but that the dissociation rate constants are significantly faster than previously used in deterministic models. As discussed in the context of Figure 5C, this has a large impact on the spatial simulation outcome and experimental verification is a priority for our future work.

Bottom Line: The agent-based and rule-based approach permits consideration of combinatorial complexity, a problem associated with multiple phosphorylation sites and the potential for simultaneous binding of adaptors.Simultaneous docking of multiple proteins is highly dependent on receptor-adaptor stability and independent of clustering.Overall, we propose that receptor density, reaction kinetics and membrane spatial organization all contribute to signaling efficiency and influence the carcinogenesis process.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Molecular Genetics and Microbiology, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA.

ABSTRACT

Background: A stochastic simulator was implemented to study EGFR signal initiation in 3D with single molecule detail. The model considers previously unexplored contributions to receptor-adaptor coupling, such as receptor clustering and diffusive properties of both receptors and binding partners. The agent-based and rule-based approach permits consideration of combinatorial complexity, a problem associated with multiple phosphorylation sites and the potential for simultaneous binding of adaptors.

Results: The model was used to simulate recruitment of four different signaling molecules (Grb2, PLCgamma1, Stat5, Shc) to the phosphorylated EGFR tail, with rules based on coarse-grained prediction of spatial constraints. Parameters were derived in part from quantitative immunoblotting, immunoprecipitation and electron microscopy data. Results demonstrate that receptor clustering increases the efficiency of individual adaptor retainment on activated EGFR, an effect that is overridden if crowding is imposed by receptor overexpression. Simultaneous docking of multiple proteins is highly dependent on receptor-adaptor stability and independent of clustering.

Conclusions: Overall, we propose that receptor density, reaction kinetics and membrane spatial organization all contribute to signaling efficiency and influence the carcinogenesis process.

Show MeSH
Related in: MedlinePlus