There are plenty of things to optimize in a med-chem project other than binding affinity. But if you don’t have at least some level of binding, you may not have a med-chem project. And while from the outside, you might think that understanding how and why compound A binds to a given target while compound B doesn’t is the first thing that medicinal chemists must be able to tell you, that just isn’t the case. We would very, very much like to be able to tell you that – and tell you that before we go to the trouble of making and testing compound B at all – but we can’t quite do it.
Here’s a surprising new paper that shows some of the complexity. You can understand a lot about compound binding to a protein target – if not predict it – by breaking apart the two terms of the free energy equation. Favorable binding means that free energy (delta-G) has to go down, otherwise it ain’t favorable, and it is of course made up of delta-H (enthalpy) minus delta-S (entropy) terms (that second one multiplied by the temperature, which for drug molecules in the body is always pretty much the same and can be neglected). And that’s where things get spectacularly hairy, because there are a lot of things that can contribute to both terms, both positively and negatively, and they are both wildly variable and computationally difficult to address reliably.
For example: a classic med-chem trick is to take a ligand, one that you know has some binding affinity for your target, find flexible parts of its structure, and restrict their movement. You can do that by adding some bulk near rotatable bonds, or tying two parts of the structure together to form a ring, and so on. Ring formation can be a death-or-glory move: it tends to either make binding quite a bit better or quite a bit worse. If your new ring keeps the compound from achieving the shape it needs to be in to bind, your affinity might just disappear. But if you’ve locked the molecule from the start into the conformation that it needs, you’ve gotten rid of the need for it to do that itself. Other things being equal, then, that means a better entropic term: instead of the molecule going from loose, floppy, and rotating to a single conformation (loss of entropy, which makes the overall free energy change less favorable), you’ve preorganized it so it doesn’t really lose any entropy at all in the binding event. Everyone’s happy!
Maybe not. What I’ve just given is the classic med-chem explanation for conformational restriction, and to be fair, there are many examples of it working in just that way. But not always. In this new paper (from a multicenter team at Marburg, Frankfurt, and Florence), the authors have taken a known kinase inhibitor, fasudil, and varied part of its structure (a homopiperazine ring) in just the way that you’d imagine a project team doing: they go to six-membered rings instead of seven, or break the homopiperazine ring open in different ways. They have X-ray crystallographic data on all of these variations, and they all have the same binding mode of the quinoline/sulfone part of their structures, which interacts with the hinge region of the kinase. They all have similar affinity as well.
But when you break down the thermodynamic profile of the compounds (via calorimetry) you find that they’re all over the place enthalpically and entropically, taking many different routes to roughly the same overall free energy change. That’s not so uncommon, although we don’t always take the trouble to see it. Weirdly, though the most flexible ligand of the bunch (compound 5 above) is actually the most entropically favorable, which is not what rule-of-thumb med-chem would predict at all. It’s actually the least enthalpically favorable as well, but that’s offset completely by the entropic term.
Bearing down on the problem with NMR relaxation measurements and calculations, it appears that it comes down to water molecules. If you’re looking for something to blame for an odd thermodynamic result in compound binding, that’s actually a good all-purpose answer, because they really are (1) crucial and (2) capable of all sorts of behavior. Releasing a bound water from a protein active site can, for example, be entropically good. Or entropically bad. Enthalpically bad. Or enthalpically good. It all depends, sadly, and it depends on things like the structure and motion of the rest of the protein, how it interacts with itself, the ligand, and the other water molecules in play, as well as the water molecules that were formerly around the ligand molecule and have to get out of the way for it to get into the binding site.
It’s a mess, and this paper is a pretty clear example of the reasons. It appears that ligand 5 has a conformation in solution that folds back and tends to partly trap some of its associated water molecules. Its hydration pattern is different than any of the others, and when it sheds those more-bound-than-usual waters, there’s a larger-than-usual gain in entropy as they leave. And this totally cancels out the mental picture that most of us med-chem types have, which depends on the entropy of the ligand structure and not of the water molecules around it.
So once again, there’s nothing simple about the thermodynamics of compound binding, and there are no details of it that cannot be important under one condition or another. Even quite similar compounds can display very different behavior, and depending on how closely you look, you may not even realize that they’re doing so. So if you’d like to know why we can’t just look at a big list of compounds and predict which ones will be the winners in a binding assay: this is why. And as I mentioned at the start of all this, binding affinity is just the beginning of what it takes to make a drug.
Some years ago, I asked a former med-chem colleague of mine who’d gone off to work as an analyst on Wall Street why, if each of us was supposed to be so smart and all, we’d picked professions where intelligence was necessary but nowhere near sufficient for success. Good question!
Update, via the comments: for more on this topic, see this earlier paper from Steve Martin’s group, and this review (free access) from the Chodera lab.