After yesterday's post on pathway patents, I figured that I should talk about high-throughput screening in academia. I realize that there are some serious endeavors going on, some of them staffed by ex-industry people. So I don't mean to come across as thinking that academic screening is useless, because it certainly isn't.
What is probably is useless for is enabling a hugely broad patent application like the one Ariad licensed. But the problem with screening for such cases isn't that the effort would come from academic researchers, because industry couldn't do it, either: Merck, Pfizer, GSK and Novartis working together probably couldn't have sufficiently enabled that Ariad patent; it's a monster.
It's true that the compound collections available to all but the very largest academic efforts don't compare in size to what's out there in the drug companies. My point yesterday was that since we can screen those big collections and still come up empty against unusual new targets (again and again), that smaller compound sets are probably at even more of a disadvantage. Chemical space is very, very large. The total number of tractable compounds ever made (so far) is still not a sufficiently large screening collection for some targets. That's been an unpleasant lesson to learn, but I think that it's the truth.
That said, I'm going to start sounding like the pointy-haired boss from Dilbert and say "Screen smarter, not harder". I think that fragment-based approaches are one example of this. Much smaller collections can yield real starting points if you look at the hits in terms of ligand efficiency and let them lead you into new chemical spaces. I think that this is a better use of time, in many cases, than the diversity-oriented synthesis approach, which (as I understand it) tries to fill in those new spaces first and screen second. I don't mind some of the DOS work, because some of it's interesting chemistry, and hey, new molecules are new molecules. But we could all make new molecules for the rest of our lives and still not color in much of the map. Screening collections should be made interesting and diverse, but you have to do a cost/benefit analysis of your approach to that.
I'm more than willing to be proven wrong about this, but I keep thinking that brute force is not going to be the answer to getting hits against the kinds of targets that we're having to think about these days - enzyme classes that haven't yielded anything yet, protein-protein interactions, protein-nucleic acid interactions, and other squirrely stuff. If the modelers can help with these things, then great (although as I understand it, they generally can have a rough time with the DNA and RNA targets). If the solution is to work up from fragments, cranking out the X-ray and NMR structural data as the molecules get larger, then that's fine, too. And if it means that chemists just need to turn around and generate fast targeted libraries around the few real hits that emerge, a more selective use of brute force, then I have no problem with that, either. We're going to need all the help we can get.