Molecular modeling is a technology with a past. Specifically, it's a past of overoptimistic predictions (often made, to be fair, by people who didn't understand what they were talking about.) Back in the late 1980s, when I started in the drug industry, modeling was going to take over the world and pretty darn soon, too. Several companies were founded to take advantage of this brave new world that had such software in it, and they raised serious money with tales of how they were just going to zzzzzip right to the drug structures. No dead ends, no detours, no cast of thousands - just a few chemists standing by to make the structure as it printed out for them. This has not quite worked out.
For those not in the business, modeling is the attempt to figure out molecular shapes, properties, and interactions by computation. There are many levels, some more successful than others. The ones I'm speaking of involve predicting three-dimensional shapes of molecules (and their target binding sites), and deciding which ones are more likely to fit well. It sounds like just what we need. It also sounds reasonably doable, in the same way that Hercules was probably told at first that he was going to just have to round up a few stray animals.
Predicting the shapes involves modeling the individual chemical bonds, and the interactions as the atoms and functional groups rotate around them, banging into each other or sticking through various forces. Originally, these things were calculated as if they were in interstellar space, with nothing around them. Later (and ever since) a number of methods to add some real-world solvent effects have been tried.
Another set of programs evaluates intermolecular fits, trying to work out the energies in play when a drug molecule slides into its binding site. Many tricky refinements have been added to those packages over the years, too, taking advantage of the latest insights into how various groups stack, pack, and interact.
And often enough, it just isn't enough. Many times the structures we have for our binding sites aren't accurate - the best ones are from X-ray crystallography, and plenty of good stuff just doesn't crystallize. (There are other cases where the crystal structure doesn't bear much relation to what's going on inside the real system, too, just to keep everyone on their toes.) Modeling goes haywire for all kinds of reasons.
One of the companies that emerged back in the change-the-world era of modeling was Vertex, up in Cambridge. It was founded by Joshua Boger, a Merck chemist who wanted a piece of the new thing and wasn't sure that Merck was taking it seriously enough. Well, coming soon in the Journal of Medicinal Chemistry (it's in the web preprint section now) is a paper from Vertex which gives us all some idea of why things didn't work out quite as planned.
The Vertex guys went back over about 150 cases, and found that in the majority of them, the structure of the small molecule in its binding pocket wasn't the structure you would have predicted as the best (read: lowest-energy.) In many of them, it isn't even close. You'd literally never have picked some of these conformations to start a modeling effort - they look very disfavored, and if you're going to pick things that far from the ground state then there's no end to it. The number of structures gets worse very rapidly as you move away from the local energy minima.
We in the business had suspected as much, and everyone knew of an example or two, but this is a quantitative look at just how bad the situation is. When you add in the cases where the binding site changes its conformation unexpectedly in response to the ligand, it's a wonder that any modeling efforts work at all. (Frankly, in my experience, they mostly don't, but I'm willing to stipulate that my experience has been more negative than the average.)
I like to say that molecular modeling is a magic wand, one that we keep waving in the hope that sparks will eventually start to shoot out of it. Someday they will. But there's a lot more hard work ahead, and no shortcuts in sight.