I'm an unabashed fan of phenotypic screening. (For those outside the field, that means screening for compounds by looking for their effects on living systems, rather than starting with a molecular target and working your way up). Done right, I don't think that there's a better platform for breakthrough drug discovery, mainly because there's so much we don't know about what really goes on in cells and in whole organisms.
Doing it right isn't easy, though, nor will you necessarily find anything even if you do. But there's a recent paper in Nature that is, I think, a model of the sort of thing that we should all be thinking about. A collaboration between the Shokat group at UCSF and the Cagan group at Mt. Sinai, this project is deliberately looking for one at the trickiest aspects of drug discovery: polypharmacology. "One target, one drug" is all very well, but what if your drugs hit more than one target (as they generally do?) Or what if your patients will only be served by hitting more than one target (as many diseases, especially cancer, call for)? The complexities get out of control very quickly, and model systems would be very helpful indeed.
This work goes all the way back to fruit flies, good ol' Drosophila, and the authors picked a well-characterized cancer pathway: multiple endocrine neoplasia type 2 (MEN2). This is known to be driven by gain-of-function mutations in the Ret pathway, and patients with such mutations show a greatly increased rate of endocrine tumors (thyroid, especially). Ret is a receptor tyrosine kinase, and the receptor is one that recognizes the GDNF family of signaling peptides. As oncology pathways go, this one is fairly well worked out, not that it's led to any selective Ret inhibitor drugs so far (although many have tried and are trying).
Using this Ret-driven fly model, the teams ran a wide variety of kinase inhibitor molecules past the insects, looking for their effects, while at the same time profiling the compounds across a long list of kinase enzymes. This gives you a chance to do something that you don't often get a chance to do: match one kind of fingerprint to another kind. And what they found was that you needed "balanced polypharmacology" to get optimal phenotypic effects. The compounds that inhibited the Drosophila equivalents of Ret, Raf, Src and S6K all at the same time made the flies survive the longest. That's quite a blunderbuss list. But some very similar compounds weren't as good, and that turned out to be due to the activity on Tor. Working these combinations out was not trivial - it took a lot of different strains of flies with different levels of kinase activity, and a lot of different compounds with varying profiles.
Now, these kinases cover an awful lot of ground, as you'll know if you've worked in the field, or if you just click on those links and look at some of the pathway diagrams. There is, I think it's fair to say, no way that anyone could have identified these particular combinations with certainly without running the experiment in a real system; there are just too many branching, intersecting, ramifications to get a clear picture of what would happen. Thus, phenotypic screening: let the real system tell you.
So, you may be thinking, fruit flies. Great. Does that tell us anything real? In this case, it looks like it does. The compound profiles that were seen in the model system translated to human cell lines, and to mouse xenograft models. And while neither of those is a perfect indicator (far from it), they're about the best we have, and many are the compounds that have gone into human trials with just such data.
I look forward to more applications of this technique, to see how far it can be pushed. Ret looks like a well-chosen test case - what happens when you go on to even trickier ones? It won't be easy, but being able to unravel some of the polypharmacology when you're still back at the fruit-fly stage will be worth the effort.