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October 26, 2010
Enthalpy and Entropy Again
Earlier this year, I wrote here about using calorimetry in drug discovery. Years ago, people would have given you the raised eyebrow if you'd suggested that, but it's gradually becoming more popular, especially among people doing fragment-based drug discovery. After all, the binding energy that we depend on for our drug candidates is a thermodynamic property, and you can detect the heat being given off when the molecules bind well. Calorimetry also lets you break that binding energy down into its enthalpic (delta-H) and entropic (T delta-S) components, which is hard to do by other means.
And there's where the arguing starts. As I mentioned back in March, one idea that's been floating around is that better drug molecules tend to have more of an enthalpic contribution to their binding. Very roughly speaking, enthalpic interactions are often what med-chemists call "positive" ones like forming a new hydrogen bond or pi-stack, whereas entropic interactions are often just due to pushing water molecules off the protein with some greasy part of your molecule. (Note: there are several tricky double-back-around exceptions to both of those mental models. Thermodynamics is a resourceful field!) But in that way, it makes sense that more robust compounds with better properties might well be more enthalpically-driven in their binding.
But we do not live in a world bounded by what makes intuitive sense. Some people think that the examples given in the literature for this effect are the only decent examples that anyone has. At the fragment conference I attended the other week, though, a speaker from Astex (a company that's certainly run a lot of fragment optimization projects) said that they're basically not seeing it. In their hands, some lead series are enthalpy-driven as they get better, some are entropy-driven, and some switch gears as the SAR evolves. Another speaker said that they, on the other hand, do tend to go with the enthalpy-driven compounds, but I'm not sure if that's just because they don't have as much data as the Astex people do.
So as far as I'm concerned, the whole concept that I talked about in March is still in the "interesting but unproven" category. We're all looking for new ways to pick better starting compounds or optimize leads, but I'm still not sure if this is going to do the trick. . .
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