1. Physics 414: Introduction to Biophysics Professor Henry Greenside September 26, 2017

2. Schedule for next few weeks
No class a week from Thursday, October 5: inauguration of President Price), homework due Fri
No class on Tuesday, October 10: fall break.
In-class problem solving, review October 12
Midterm exam on Tuesday, October 17. Will cover everything up to and and including October 12, closed book but equations, data provided except k
Is Oct 17 best date for the midterm
out of Oct 12, 17, or 19?

3. Class discussions: some review questions to see if you are keeping up with the reading
What is the Monod-Wyman-Changeux (WMC) model and what is it good for?
Why is cooperativity useful biologically?
What is the Pauling model and what is it good for?
What is a kinase, what is a phosphatase, why are these important or relevant?
What is the “Bohr effect” related to hemoglobin?
What is a “response regulator” and what is its significance?
What does PDB stand for?
What are two major points of Chapter 8?

4. Statistical physics of hemoglobin (Sec 7. 2
Statistical physics of hemoglobin (Sec 7.2.4) Cooperativity as interaction energy J
Assume V_box = (1 nm)^3, leads to effective concentration 10/6 ~ 1.7 M.

5. More sophisticated hemoglobin binding models
Assume V_box = (1 nm)^3, leads to effective concentration 10/6 ~ 1.7 M.

6. Comparison of models with experiment
Assume V_box = (1 nm)^3, leads to effective concentration 10/6 ~ 1.7 M.

7. Statistical physics of “dimeric hemoglobin” or “dimoglobin” (Sec 7. 2
Assume V_box = (1 nm)^3, leads to effective concentration 10/6 ~ 1.7 M.

8. Oxygen occupancy for “dimoglobin”
Assume V_box = (1 nm)^3, leads to effective concentration 10/6 ~ 1.7 M.

9. O2 occupancy <N> for “dimoglobin”
Assume V_box = (1 nm)^3, leads to effective concentration 10/6 ~ 1.7 M.

10. Probabilities of O2 binding to “dimoglobin”
Assume V_box = (1 nm)^3, leads to effective concentration 10/6 ~ 1.7 M.

11. Probabilities of O2 binding for Adair hemoglobin model
Assume V_box = (1 nm)^3, leads to effective concentration 10/6 ~ 1.7 M.
Cooperativity greatly suppresses intermediate states, strongly favors fully saturated states (good for transporting lots of O2).

12. Another way to get cooperativity: two different conformational states of protein Monod-Wyman-Changeux (MWC) model
“tense”
conformation T
“relaxed”
conformation R
Assume V_box = (1 nm)^3, leads to effective concentration 10/6 ~ 1.7 M.

13. Monod-Wyman-Changeux (MWC) model of dimoglobin
Assume V_box = (1 nm)^3, leads to effective concentration 10/6 ~ 1.7 M.

14. Monod-Wyman-Changeux (MWC) model of dimoglobin
Assume V_box = (1 nm)^3, leads to effective concentration 10/6 ~ 1.7 M.

15. Simple 4-state model of phosphorylation similar to MWC model
Assume V_box = (1 nm)^3, leads to effective concentration 10/6 ~ 1.7 M.
Protein is active or not, protein is phosphorylated or not,
two state variables sigma1, sigma2

16. Simple 4-state model of phosphorylation similar to MWC model
Assume V_box = (1 nm)^3, leads to effective concentration 10/6 ~ 1.7 M.

17. Other applications of the Monod-Wyman-Changeux (MWC) Model
Hemoglobin
Ligand-gated ion channels, like vision photoreceptor
Bacterial chemotaxis.
Spatial patterning via gene expression
Assume V_box = (1 nm)^3, leads to effective concentration 10/6 ~ 1.7 M.

18. Chapter 8: Random Walks and the Structure of Macromolecules
Assume V_box = (1 nm)^3, leads to effective concentration 10/6 ~ 1.7 M.

19. Chapter 8: Random Walks and the Structure of Macromolecules
What are some key points of the first two sections?
Purpose of this chapter?
(Harvard freshman anecdote)
Assume V_box = (1 nm)^3, leads to effective concentration 10/6 ~ 1.7 M.

20. Numerical exploration of random walks Mathematica notebook random-walks.nb
Assume V_box = (1 nm)^3, leads to effective concentration 10/6 ~ 1.7 M.

21. At the blackboard: why root-mean-square distance from origin of random walk goes as Sqrt[number of steps]
I gave more general vector version of argument on page 314 of PBOC2 of why the root-mean-square (rms) distance from the origin after taking N successive random steps of equal length a is Sqrt[N]. Key point is to take “ensemble average” <..> of the distance squared, which means to average over all possible random walks starting from the origin and taking the same number of steps. Outline of algebra is following:
Assume V_box = (1 nm)^3, leads to effective concentration 10/6 ~ 1.7 M.

22. Why does ?
Assume V_box = (1 nm)^3, leads to effective concentration 10/6 ~ 1.7 M.

23. One-minute End-of-class Question