models/chapter2

These models are all based on the ReactionScheme object which can be accessed most easily through the ReactionSchemeEditor. Along with it comes a tool to calculate the behavior of reaction schemes, RSCalc, which integrates the equations and plots the results. The other component used in some of them is the Profile object and its ProfileEditor which can be used to set the timecourse of an imposed concentration change.

binding	1. A simple binding reaction of the form A + B <--> X. The split arrow is a shortcut for this type of reaction which can also be constructed explicitly with the orange + symbol. Click on the different nodes to see and change their starting concentrations C-0. The forward and reverse rates of the reaction can be set on the right-hand side. The D-diff variable is for the diffusion constants of the different species, but here it has no effect since the calculation assumes a single well-mixed pool.
enzyme	2. Enzyme reactions implemented in two different ways. The diagram shows two independent reaction schemes. The one at the top uses an enzyme arrow (the fourth one from the left on the component bar at the very top). Clicking this arrow brings its three parameters into the sliders on the right. Below it is a scheme doing exactly the same thing but drawn out in full, explicitly showing the substrate + enzyme complex. Click on each of these to see how their parameters relate to those of the enzyme reaction. Note in particular that the forward rate for the enzyme plus product going to their complex is zero. this is why the enzyme arrow only needs three parameters. The graph shows the evolution of the concentrations of the various species. They do not lie on top of each other because the starting conditions are slightly different. Click the substrate pool in the lower diagram and adjust its starting concentration C-0. When this is exactly 1, the two schemes have the same starting conditions and are completely equivalent. To gain fine control over the variables, either put the mouse over them and use the keyboard, or click on the button and drag the mouse vertically away from the slider before moving it left or right. The farther you are away, the finer the control of the value.
fig3A	3. Competitive inhibition of enzyme activity. Demonstration for figure 2.3A. This model has a single enzyme pool acting on two different substrates. It illstrates how the formation of product P1 can be inhibited by increasing S2. The demo starts out with S1 at 1 and S2 at 0.5. The plot to monitor is P1, the product formed from S1. To see how S2 affects P1, click on S2 to activate its concentration slider (labelled C-O). Then vary initial concentrations of S2 from 0.1 to 100 uM and observe how P1 levels drop as S2 rises. This replicates the plot in figure 3 A. As a further exercise, observe how alterations of enzyme parameters affect the outcome at different levels of S2. Which manipulation has least effect ?
fig3B	4. High substrate effects on equilibria. Demonstration for figure 2.3B. In this model an activator A binds to an inactive enzyme B to produce the active enzyme E. A and B remain identical to each other in this simulation since they start out at the same concentration. Their plots will therefore overlap. The point of the model is to show that the substrate S, which is apparently downstream of A and B, actually affects their equilibrium. This would have obvious consequences for any other reaction mediated by A. To run the demo, click on S to activate its concentration slider. Vary S between 0.1 and 100 uM, and monitor the effect on A and B.
box4Fig3A	5 a PKC model with only basal activation and Ca activation. This model corresponds to reactions 1, 2 and 3 in Box 4, Figure B2.2B. To generate the plot in Box 4, Figure B2.3A, vary levels of Ca betwee 0.1 and 10. The total activity of PKC is the sum of the PKC-basal and PKC-Ca levels. Based on the behaviour of the PKC-basal curve, can you speculate about a possible reason for the discrepancy between the experimental (solid line) and simulated (dashed line) curves at 10 uM Ca ?
box4Fig3B	5 b. Same model as 5a plus AA activation of PKC. This corresponds to reaction 4 in Box 4, Figure B2.2B. To generate the plot in Box 4, Figure B2.3B, set Ca to zero, and vary AA between 1 and 50. The total PKC activity is now the sum of PKC-basal and PKC-AA, since the PKC-Ca is zero. Note that this model is not sufficient to generate the correct response of PKC to AA in the presence of 1 uM Ca. Instead we obtain the plot with crosses in Box 4, Figure B2.3C.
box3Fig2CD	5 c. Final version with synergistic activation of PKC by Ca and AA. This crucial step is added by introducing reaction 5 (Box 3, Figure 2.1B) and the Ca.AA.PKC active form in the model. We can start out by replicating Box 3, figure 2.2C now, by setting Ca to 1 uM and varying AA between 0.1 and 50. The main contributors to PKC activity are now PKC-Ca and Ca.AA.PKC. The final test of the model is to generate the rather steep activation curve (Box 3, Figure D). This uses the same model, but now AA is fixed at 50 uM and Ca is varied between 0.001 and 10 uM. Here each of the active PKC forms contribute significantly to total activity in different parts of the Ca range.