CHI’s annual FBDD meeting took place in San Diego this week, and since this was the first time in a while both Teddy and I have been in the same place we’ve decided to make this a joint post. As with last year this does not aim to be comprehensive.
One of the highlights of the conference was a set of three talks on BACE1 inhibitors from Amgen (Ted Judd), Lilly (David Timm), and Pfizer (Ivan Efremov), the first two of which have been discussed here and here. It’s nice to see fragments playing a pivotal role in delivering advanced leads and – at least in the case of Lilly and Merck – clinical candidates against what has been one of the most difficult drug targets in industry.
Speaking of difficult targets, Till Maurer of Genentech gave a lovely presentation on using NMR-based fragment screening to discover inhibitors of the holy grail of oncology, Ras. They’ve recently published some of this story, which we’ll highlight in an upcoming post.
A common question is ‘how often do you find the same fragment using different methods?’ (see here for an ongoing discussion on LinkedIn). Cynthia Shuman from GE gave a nice case study in which she screened the protein PARP15 against 987 fragments using a Biacore T200. Of the 15 fragments with shapely, well-behaved sensorgrams, 14 were confirmed by NMR. On the other hand, only one of these hits was detected in a differential scanning fluorimetry (thermal melt) assay.
Marcel Verdonk at Astex described general trends from mining in-house and published data. After looking at 43 in-house targets, he found that 8000 compounds had been tested against 2 or more proteins, and after plotting by molecular weight found that, consistent with the original Hannian model, larger compounds are more selective. In a separate analysis of 53 fragments that had been advanced to leads, he found that in most cases the initial fragment maintained roughly the same position and orientation from start to finish.
Rod Hubbard, Teddy and I all ran round-table discussions, but only Teddy kept notes, which are summarized here.
The topic started as a discussion of 2D vs. 3D fragment libraries. In the recent Pfizer fragment build, a group of diverse chemists eyed every compound, and at least five had to agree to each molecule before it went into the library.
The discussion went briefly to the old fight: Are nitros masked amines or noxious moieties? The table ended up agreeing that if you would remove the nitro group or change it anyways, why put it in the first place?
We then dove right back into the 2D vs. 3D debate. Kinases seem to love 2D fragments, while other classes of targets seem to NEED 3D fragments. One idea discussed was 3D fragments as complements to 2D fragments. It was mentioned that 3D fragment libraries would need to be MUCH larger to cover equivalent chemical space. I thought the idea that 3D fragments would be exploring “vector” space rather than “chemistry” space would mean that you could go with a much smaller library, if you want to use it for vector space searching. It was also proposed that 2D fragments tend to be much smaller (~150-180Da-ish) and 3D fragments would be, by necessity, bigger (~250 Da).
The topic then changed to SBDD (structure-based drug discovery) as part of FBDD. Most people at the table were of the opinion that they wouldn’t use FBDD (on a normal priority target) without SBDD. And with SBDD, you don’t need 3D fragments to explore vector space since you will have the X-ray to guide you.
The point was made that 3D fragments also HAVE to be scaffolds which would end up in the final compound. If you are simply using a scaffold to explore vector space without any hope of it ending up in the final product, why bother. [TZ Note: I think this is very shortsighted and people do not understand that targets will most likely NOT have SBDD to guide them, at least in the fragment-based lead generation stage.]
The question was asked to the table: is FBDD a valid approach in the absence of structure? Three people said yes, the rest (~8) said no. All three who said yes were small company/ CRO people. Everyone agrees if you do go with FBDD without structure you need to have a HEAVY investment in biophysics to characterize the protein and the hits.
One person asked about low confirmation hits following a fragment screen: the table agreed that this is most likely the result of the library being “wrong”. We finished the discussion by asking if 2D fragments are more pan-class (not targeted to a specific class of targets) and 3D fragments may be more target-focused. The resounding answer was “Who knows, but why would they be?”
As this post is already getting long we’ll stop here, but for those of you who were also at the conference please add your comments. And if you missed this one, there are still several exciting upcoming events this year!