The FBDD track is just one of six within the CHI Drug Discovery Chemistry Conference. One indication of the success of the field is its
appearance in several of the other tracks: attendees were likely to hear about
fragments without going to the FBDD track at all.
In the GPCR track, Robert Cooke from Heptares discussed the
application of fragments to the β1-adrenergic receptor (see also here). In the
kinase track, Hongtao Zhao presented in
silico fragment work (see also here). And in the protein-protein
interaction track, David Fry from Roche described a deconstruction of the
p53-HDM2 inhibitor RG7112 into its component fragments to see whether the
molecule could have been identified from FBLD. RG7112 consists of a central
core with four appendages, and although the mono-substituted core was too weak
to detect, some of the cores with two substituents could be identified and
bound to the protein in the same manner as the parent compound. However, these
did tend to be super-sized fragments, with molecular weights in the 300-350 Da
range.
Protein-protein interactions were also a theme of Richard
Taylor, from the company UCB. They built a sizable fragment library of about 23,000 (mostly
commercial) compounds designed to cover molecular frameworks found in known
drugs. UCB has invested heavily in SPR technology, and with a stable of four
Biacore 3000 instruments could rapidly screen this entire library against a
dozen protein-protein interaction targets. Not surprisingly, given the
difficulty of this target class, the hit rate was much lower than in
conventional fragment screens, averaging just about 1%. What was interesting is
that only 964 fragments hit any target – at less than 5%, this is much lower
than the roughly 33% hit rate seen in other fragment libraries. Most of these
fragments were reasonably specific, though; 908 hit ≤ 8
targets. It will be interesting to see whether anything can be learned about
“privileged” protein-protein interaction fragments from this set.
Of course, extracting general trends from collections of
fragments is not necessarily straightforward. Teddy has already brought up the
difficulties of describing molecular shape; as he pointed out in his presentation,
Fsp3 is not the best measure of “three-dimensionality” for several
reasons. For example, even toluene has an Fsp3 = 0.14, and while
Pete Kenny correctly points out that aromatic molecules do have volume, most
chemists would think of this as a very “flat” compound. Principal moment of
inertia (PMI) is better, but is harder to calculate. Happily, as Justin Bower
described in his presentation, the Beatson Institute is allowing other
researchers to use their 3DFIT software to calculate PMI and other properties.
One of the criticisms of 3D fragments is that, as Rod
Hubbard pointed out, they can be a “pain in the neck” for chemistry. One
solution that researchers at Vernalis took was to do analog work on a simpler
molecule, then scaffold-hop back to the original fragment once the SAR was
sufficiently understood to justify investment in more challenging chemistry.
Finally, the question of what to do with fragment hits that
don’t reproduce in different assays was the topic of at least one breakout
discussion and was also extensively discussed by Peter Kutchukian, who
presented an analysis of 134 fragment screens using a variety of techniques
against 34 different targets at Novartis. Some of this was presented at FBLD 2012, but one interesting finding was that hits from biophysical screens (such
as SPR, NMR, or DSF) tended to cluster separately from hits in biochemical
assays. Given the number of ways to find fragments, pursuing hits that confirm
in both a biochemical and a biophysical method may help to weed out artifacts,
though at the risk of increasing false negatives.
Feel free to chime in with your thoughts and impressions,
whether or not you were there. And if you are kicking yourself for not
attending, next year’s meeting is scheduled to return to San Diego from April 22-25.
3 comments:
The Biacore model UCB uses must be 4000!
I like your comments on Fsp3. I wonder if you have seen this paper , which looks at 3D methods.
Also aside from the misuse of this metric by some people, there is an interesting paper describing some issues with the Fsp3 paper itself.
Thanks for the plane of best fit paper - I'll take a look at it. I did see the correlation inflation paper, which is covered here. It's a good reminder that, as the 3D fragment library consortium prominently displays on their 3DFIT page, "parameters are guidelines."
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