Non-equilibrium strategies enabling ligand specificity by signaling receptors
- Department of Biomedical Engineering, Yale University, United States
- Department of Physics, Yale University, United States
- MRC Protein Phosphorylation and Ubiquitylation Unit, University of Dundee, United Kingdom
- Systems Biology Institute, Yale University, United States
Figures
Figure 1
Reaction scheme of kinetic proofreading models.
Chemical species and rate constants are shown in the figure. R denotes ligand-free receptors, B denotes ligand-bound inactive receptors, and are phosphorylated receptors. The ultimate phosphorylated species PN (marked red) is assumed to be signaling competent. (a) shows the traditional model first proposed by McKeithan, 1995. (b, c) show the sustained signaling model and the limited signaling model (Lever et al., 2014) which introduce additional receptor states, and I respectively, directly following receptor activation.
Figure 2
Ligand discrimination in kinetic proofreading models.
(a) Activity plotted as a function of non-dimensional ligand dissociation rate for the traditional KPR scheme (Figure 1a). (b) Activity plotted as a function of non-dimensional ligand dissociation rate for the limited signaling model (Figure 1b). (c) The dependence of the activity on the dimensionless phosphorylation rate ฯ for the limited signaling model. All figures plotted for a sequence of N = 1, 5, and 10 phosphorylation sites.
Figure 3
Reaction scheme of kinetic sorting model.
Chemical species and rate constants are shown in the figure. denotes ligand-free receptors, denotes ligand-bound inactive receptors, and are phosphorylated receptors. represents an implicit source and sink, corresponding to receptor delivery and internalization, respectively. It does not denote a physical chemical species.
Figure 4
Kinetic sorting of receptor species.
Abundances of network species (ligand bound inactive receptor) and for a signaling receptor with phosphorylation sites. Abundances are shown for ligands of three different affinities. The inset shows the activity of the first phosphorylation site . Species abundances below are not shown.
Figure 5
Kinetic sorting model predicts ligand specificity.
(a) The activity of the phosphorylation site as a function of dimensionless dissociation rate . The activity is normalized to the maximum activity. The maximum as a function of is shown in the inset. (b) Activity of the first phosphorylation site plotted as a function of the dissociation rate for different values of the phosphorylation rate . (c, d) Activity of the first phosphorylation site plotted as a function of phosphorylation rate (dephosphorylation rate in panel d) for different values of the dissociation rate .
Figure 6
Multiple phosphorylation sites and receptor degradation dictate ligand specificity.
(a) Activity of the first phosphorylation site, , as a function of the dissociation rate for signaling networks with different number of phosphorylation sites. (b) The optimal dissociation rate that leads to maximum phosphorylation activity as a function of dimensionless degradation rate for different values of . is shown only if . (c) The relative activity of a ligand with dissociation rate that differs by compared to plotted as a function of for different values of (see inset). Of the two ligands that differ in stability by , the ligand exhibiting maximum activity is considered.
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Non-equilibrium strategies enabling ligand specificity by signaling receptors
eLife 14:RP107524.
https://doi.org/10.7554/eLife.107524.3
