 So in the Chevron plot I'm simply plotting k or again the logarithm of k the rate as a function of something happening. Protein denitration is an easy thing happening. So I have grinodinium hydrochloride for instance my nasty ion going from whatever 0 to 5 molar or something and then I'm going to get a curve that looks roughly like this. What this means is that when I have zero concentration of grinodinium hydrochloride I'm very rapidly going to go towards folding. So I will rapidly reach equilibrium because all protein is folded almost. At very high concentration I will also have a rapid process because everything unfolds and it's going to be slowest in the middle. As an isolated curve this is pretty useless but the beauty here is when we start comparing things and what should we compare? Well normally the first the native protein the native protein sequence we frequently call that WT for wild type. And then I can introduce a second sequence here which we call mutant is a good word because it is a mutant. And now there are several slopes here. Remember all these slopes they were related to the free energies and the energy barriers right? Energy barriers in particular. So what if we look at them and I'm particularly going to look at them at the half point of the original transition here. So this is where folding dominated and this is where unfolding dominated. So where folding dominates what this really tells me is the energy barrier when I'm going from the unfolded state to the transition rate right? Look at the Arrhenius plot derivation if you don't recall that. So leave some room for a delta there in a second. L and K unfolded to native. That is going to be proportional to well there's going to be an extra factor here. I can write equal sign strictly it's not equal but the difference is going to be equal. That is going to correspond to a change in free energy of the transition state minus the unfolded state. Technically it's not the difference but I want to put the difference there too. The idea here now if I'm comparing the mutant to sorry the wild type to the mutant do you see how this slope the curvature changes with the mutant and what this means is that the barrier from unfolded to the transition state has changed due to this mutant. So it's possible that this mutant was at least part of the transition state. That's interesting because now I find an indirect way of accessing the transition state. Similarly I can compare all these four curves just doing the free energy barrier from the unfolded from the folded to the transition state. If I combine them I can also look at what is the difference in K unfolded to native divided by native to unfolded and that's going to correspond to the difference in the native free energy minus the unfolded free energy. So this really tells me for this particular residue on top how much did it change the free energy barrier in the transition state when I did this mutation. On the bottom we say how much did we change the stability of the final native states when I made this residue. And the way we think about this if these are roughly the same that meant that I saw the entire change from my mutation already when we were in the transition state. So my residue must have had all its interactions formed already in the transition state. It was fully part of the transition state. On the other hand if this is zero it doesn't change it doesn't appear to change the free energy barrier at all. That means that it didn't influence the transition state at all and that likely means that my residue was not part of it. So just by taking the quotient of these we end up with something called a phi value. So the phi value is literally the quota between the difference of the transition state barrier divided by the change in stabilization and the idea is that you get both of them just by measuring things in the chevron plot when you have systematic differences here. If the phi value is zero I'm not part of the transition state. If the phi value for my residue is one I am part of the transition state. Now we can identify transition states indirectly without really having their structure and compare that to models. That's super cool so I'm going to show you a few of these studies and people have used chevron plots to define transition states. Why are they called chevron plots? Well it has to do with this small mark that you might see on the military uniforms or so this is the chevron and you can probably recognize the shape of the plot. So chevron plot.