1. Presentation Schedule

2. Homework 8 Compare the tumor-immune model using Von Bertalanffy growth to the one presented in class using a qualitative analysis… Determine the number of steady states and their stability using qualitative approaches when analytical progress is not possible. Be sure to nondimensionalize and generate phase portraits. Does the qualitative behavior differ from that of the model presented in class? If so, how? Consider sigma to be your bifurcation parameter

3. Models for Molecular Events Recetor-Ligand Binding

4. Definitions Receptor –a protein molecule, embedded in either the plasma membrane or cytoplasm of a cell, to which a mobile signaling (or "signal") molecule may attach. Ligand –a signal triggering substance that is able to bind to and form a complex with a biomolecule to serve a biological purpose –ay be a peptide (such as a neurotransmitter), a hormone, a pharmaceutical drug, or a toxin,

5. Why Receptor Ligand Binding is Important Individual cells must be able to interact with a complex variety of molecules, derived from not only the outside environment but also generated within the cell itself. Protein-ligand binding has an important role in the function of living organisms and is one method that the cell uses to interact with these wide variety of molecules. When such binding occurs, the receptor undergoes conformational changes, which ordinarily initiates a cellular response.

6. Example: VEGF Receptors

7. Possible Cellular Responses

8. Cellular Uptake Molecules are taken up by cells in different ways –Glucose is transported inside cells by facilitated diffusion –Other water soluble molecules must be carried into the cell via receptor-mediated endocytosis process by which cells internalize molecules via the inward budding of plasma membrane vesicles containing proteins with receptor sites specific to the molecules being internalized.

9. Facilitated Diffusion and Receptor-Mediated Endocytosis

10. Chemostat Revisited Recall that we modeled nutrient uptake using Why should saturation occur? –Limited number of receptors or carrier molecules –Limited rate of internalization and release C r/2 r a

11. Goal Model the process of nutrient uptake Schematic Diagram

12. STEP 1 Reaction Diagram Reaction diagrams can be converted to a system of odes that describe the rates of change of the concentration of the reactants + Extracellular Nutrient Free Recepto r N-R Complex + Intracellular Nutrient k2k2 N R CR P + k1k1 k-1k-1 +

13. The Law of Mass Action To go from molecules to concentration we use the Law of Mass Action –When two or more reactants are involved in a reaction step, the rate of the reaction is proportional to the product of the concentrations of the reactants. –Convention: k i ’s are the proportionality constants

14. Model Variables VariableDefinitionUnits r[R]#/cell n[N]Moles/volum e c[C]#/cell p[P]moles/volum e

15. The Model Equations

16. Notes The p equation is decoupled –We only need to consider 3 equations The total number of receptors is conserved –We only need to consider 2 differential equations (the c and n equations), together with:

17. Reduced Model Note: Because this is a system of two equations, we use the traditional stability and phase plane analysis, but let’s do something different first.

18. Quasi-Steady State Assumption The concentration of the substrate- bound enzyme (and hence also the unbound enzyme) change much more slowly than those of the product and substrate. Rationale –Small molecules like glucose are found in higher concentrations than the receptors are –If this is true, then receptors are working at maximal capacity Therefore the occupancy rate is virtually constant

19. Quasi-Steady State Approximation The QSSA is written as

20. Michaelis-Menton Kinetics A simple substitution shows that we have derived the Michaelis-Mention kinetic form that we used in the chemostat model.

21. Problem with QSSA By assuming that dc/dt = 0, we changed the nature of the model from 2 ODEs to one ODE and one algebraic expression. There must be consequences for doing this. To see which timescales QSSA is valid on, let’s nondimensionalize.

22. Nondimensionalization The nutrient and complexes are scaled by their initial conditions. Time is scaled by receptor density multiplied by the association rate.

23. Nondimensional Equations Now we see that assuming dc/dt = 0 is equivalent to assuming that  << 1, which means r 0 << n 0.

24. Validity of QSSA So, on timescales of the order 1/(k 1 r 0 ) (ie long timescales), receptor-mediated nutrient uptake can to approximated by

25. Behavior of Solutions u is a decreasing function of time and v decreases if u decreases. Therefore, on this timescale ( = long times), both the nutrient and complex concentrations are decreasing This can’t always be true, recall that we started with c(0) = 0. Let’s see how the solutions behave on short timescales

26. Nondimensionalize The nutrient and complexes are scaled by their initial conditions. Time is scaled by nutrient concentration multiplied by the association rate.

27. On Short Timescales We can now predict how receptors fill up

28. On Short Timescales Now if  = r 0 /n 0 ~ 0, we have We can now predict how receptors fill up

29. Short Timescale Solutions So v rises quickly to a maximum on short timescales.

30. Complete Behavior Initially, v rapidly rises which means receptor density quickly increases Eventually, the nutrient is depleted and the the density of bound complexes follows suit The behavior of the system can be completely determined by solving approximate equations on two different timescales

31. QSSA vs Full Model Behavior

33. Traditional Analysis The only steady state is u = 0, v = 0 and it is stable Eventually all of the nutrient is consumed and internalized and all of the receptors are empty