Fragments and kinases at Abbott

Of the fragment-derived drugs that have entered the clinic, roughly half target protein kinases. Phil Hajduk (of SAR-by-NMR fame) and Irini Akritopoulou-Zanze provide a nice overview in a recent paper of how Abbott applies fragment-based approaches to this target class.

As anyone who works in the field of kinases can attest, there’s a lot of competition: the authors state that, since 2001, more than 10,000 patents or patent applications describing protein kinase inhibitors have been published. With so many inhibitors already identified, developing novel molecules is a particular challenge. This is somewhat due to the fact that most kinase inhibitors bind at least in part to the conserved purine binding site, or hinge-region. This is a thermodynamic hot-spot, usually accounting for 40-60% of the total binding energy for fully elaborated molecules. It is straightforward to carve out fragments that bind in this site from existing molecules, as shown in the figure.


But as also shown in the figure, this approach can create complicated IP, with dozens or even hundreds of overlapping patents covering the fragments. Of course, this doesn’t mean that clever medicinal chemistry can’t navigate the IP minefield, as examples described on this site from SGX and Astex have shown.

Nonetheless, the Abbott researchers decided to steer away from this hazard. They have designed and synthesized about 50 novel hinge-binders and over 5000 more elaborated molecules, and used these in their screens against kinases as well as other targets. The results are quite interesting.

First, many of the fragments show quite a bit of selectivity, hitting only one or two kinases out of a panel of 11 different kinases. In other cases, selectivity could be achieved through subsequent optimization, though in these cases the process was more often driven empirically than by structure-based design.

Another interesting observation is that the same fragment sometimes bound to different kinases in different fashions, or changed its binding mode during elaboration. This phenomenon has been previously reported by researchers at Vernalis.

The third observation is that, while these molecules exhibited a 10-fold enrichment against 13 different kinase targets compared to the generic Abbott screening collection, they also exhibited a 3-fold enrichment for 20 non-kinase targets. The authors suggest this is due to the fact that they may be acting as adenine mimetics, but it is also consistent with the Hann model of less complex fragments being able to bind to more targets (as discussed here and here).

Of course, fragment-based methods are not the only way to identify kinase inhibitors. As the authors note, “there has been almost universal success in the design and identification of potent kinase inhibitors.” Still, this brief review provides some practical advice on how fragment-based philosophies can complement more traditional lead discovery approaches.

Fragments in silico, confirmed by X-ray

I’ve always been something of an empiricist, and have therefore been wary of computational fragment screening. It’s not that I think it’s impossible, just that the algorithms and parameters developed to date have not often shown themselves up to the task. A paper just published in Nature Chemical Biology from Brian Shoichet’s group at UCSF has caused me to reconsider my skepticism.

Shoichet and Yu Chen used the program DOCK to screen 67,489 commercially available fragment-sized molecules contained in the database ZINC against the active site of the beta lactamase CTX-M, a bacterial enzyme responsible for resistance to penicillin and cephalosporin. Of 69 top hits, 10 actually inhibited the enzyme when tested experimentally. In contrast, of 37 high-scoring hits from a similar computational screen of 1,147,326 larger lead-like molecules, none showed any inhibition up to the limit of their solubilities.

Interestingly, each of the ten active fragments contained an anionic group: 3 carboxylates, 2 sulfates, and 5 tetrazoles among the set. A reexamination of the docked lead-like molecules revealed a relatively high-scoring tetrazole, which exhibited an experimental Ki value of 21 micromolar (see figure). Although this was an in silico hit, it was swamped by the number of (inactive) hits and so had not been selected for experimental follow-up until the fragment results revealed tetrazoles to be privileged pharmacophores. Additional similarity searching of the lead-like molecules led to two additional low micromolar inhibitors.



Five of the inhibitory fragments and one of the lead-like molecules were characterized crystallographically, and the results were remarkable: all of them bound in a similar manner to that predicted by docking.

Chen and Shoichet also investigated the specificity of the fragments compared to the lead-like compounds, and the results agreed well with those predicted by Hann and colleagues (as discussed on our sister blog FBDD-Lit here). Namely, while the fragments had relatively low specificity against a mechanistically distinct beta lactamase (AmpC), the lead-like molecule exhibited roughly 100-fold tighter inhibition of CTX-M. In other words, fragments likely have a higher hit rate (and correspondingly lower specificity) due in part to their simplicity, but as fragments are elaborated, specificity can be readily built into the molecules.

So does this mean the era of computational fragment-based screening has arrived? While these results are impressive, it is important to keep them in perspective. CTX-M has a relatively rigid active site, while many proteins of interest show a level of flexibility that confounds modeling. Moreover, Chen and Shoichet were working with an ultra-high resolution (0.88-Angstrom) crystal structure of CTX-M in which they could actually see density for hydrogen atoms on some polar groups. Needless to say, this is atypical. Still, the paper does give hope that the computational tools are ready, as long as they are applied to appropriate systems.

Fragments on Glass

I’m always a fan of new fragment technologies, and Hioryuki Osada and colleagues at RIKEN have just published a very intriguing one which they call a “fragment combination array,” or FCA.

The approach involves immobilizing fragments onto a specially prepared glass slide using a photogenerated carbene reaction; this can be done as an array of microscopic spots. Next, the glass slide is treated with a fluorescently labeled protein and washed. If the protein sticks to the small molecule, it will show up as a fluorescent spot. Appealingly, if the protein of interest is genetically fused to a fluorescent protein, crude cell lysates can be used, simplifying the assay. The researchers previously demonstrated that natural products and drugs could successfully be immobilized to a treated glass chip using this method, and that the molecules retained their ability to bind to protein targets, despite the covalent linkage to the chip.

Of course, binding interactions between drugs and their targets are generally much stronger than between fragments and their targets. Also, because fragments are so small, there is a higher probability that the part of the fragment used to attach to the glass will be critical to but inaccessible for binding. Fortunately, the carbene chemistry is fairly non-selective, inserting into C-H and O-H bonds at random; thus, the likelihood is that at least some of the fragments will bind in a productive fashion. The technique is conceptually similar to the SPR-based methodology used by Graffinity, though to my knowledge Graffinity screens individual fragments as opposed to binary pairs.

But does it actually work? An initial proof-of-concept used FKBP12 ligands, the same ones previously described in the first famous “SAR by NMR” paper. In that example, a low micromolar pipecolinic acid derivative was linked to a high micromolar benzanilide derivative to generate a nanomolar binder to FKBP12. In the current case, the immobilized pipecolinic acid derivative was able to capture fluorescently-labeled FKBP12, while the benzanilide was not. However, co-spotting the two fragments led to a much stronger signal (more fluorescence) than the pipecolinic acid spot alone, suggesting synergy between the two immobilized fragments.

Having shown this, the researchers next turned to the protein carbonic anhydrase II (CAII), which has a predilection for sulfonamides. They created an array from four aromatic sulfonamide-containing fragments (and one negative control) and ten diverse non-sulfonamide-containing fragments. A screen of these 50 different mixtures against fluorescently-labeled CAII revealed a number of hits, and by merging elements of one of the diverse compounds onto a sulfonamide “anchor” fragment, the researchers were able to improve the potency of the sulfonamide from 435 nM to 29 nM.

Of course, there are limits: clearly the technique is not as sensitive as many other fragment-detection methods, as illustrated by the inability to detect benzanilide binding to FKBP12, an interaction with a Kd in the mid to high micromolar range. In fact, both test cases involve protein targets that have been shown to be highly amenable to fragment-based methods, and both start with known fragments with relatively high affinities. Moreover, the covalent immobilization methodology won’t work for all fragments; acetazolamide, a fragment-like high-affinity binder of CAII, didn’t work in this assay, likely due to poor geometry or sterics of the immobilized fragment.

Still, FCA is a neat and potentially very rapid method for finding a second fragment once a first has been identified. It will be fun to watch how the technique evolves.

Fragments 2009

Just a few quick thoughts on RSC BMCS Fragments 2009, which I had the pleasure of attending at AstraZeneca’s beautiful new conference center in Alderley Park, UK. The quality of the talks and posters was very high, and in many cases speakers presented unpublished and exciting research, so I don’t want to steal their thunder here (though see the FBDD-Lit blog for some nice summaries).

One striking observation was the number of speakers from big pharma. Of the 16 oral presentations, almost a third were from AstraZeneca, Pfizer, GlaxoSmithKline, or F Hoffmann-La Roche. Biotech represented about half the talks, with the remainder from academia.

Attendees were similarly diverse, both by employer as well as geography. Besides the UK and USA, many European countries were represented, as were China, Japan, and Korea. I remember recently it was rare to find anyone exploring fragments outside of the US and the UK.

Rod Hubbard observed in his closing talk that just a few years ago fragment-based drug discovery was seen as the domain of “exotic eccentrics.” No longer. The concept has gone mainstream, there has been a convergence as to the methods (particularly a rapid adoption of surface plasmon resonance), and large pharmaceutical companies are investing substantial resources in FBDD. I think the field can look forward to a wealth of new discoveries.

And for those of you who missed it, feedback was sufficiently positive that there will likely be a sequel: Fragments 2011.

Guest Blogger: Brian Stockman

[DrZ: Most of you probably know Brian and his excellent work in NMR and drug discovery, especially fragments. I have asked Brian to summarize his most recent paper for us. Below is his contribution. The Editors would welcome others to do the same if they are so inclined.]


A recent paper from Pfizer [Chemical Biology & Drug Design 73, 179-188 (2009)] described the concerted use of NMR screening, competition binding, TROSY-based binding site mapping, and NMR-based activity assays to identify allosteric fragment activators of 3-phosphoinositide-dependent kinase-1 (PDK1). This protein kinase presented an interesting challenge since, in addition to the ATP site typically targeted by structure-based drug design efforts, it was known to have an allosteric site that could activate (or potentially inhibit) activity.

An STD-based NMR screen resulted in 372 fragment hits out of 10,237 fragments screened. Testing the compounds in an activity assay would normally eliminate the many false-positive artifacts of the STD assay. A first pass of the hits through a Kinase-Glo assay revealed that many were in fact inhibitors. Fragments without activity in this assay, however, could not be discarded since this assay was not capable of monitoring events at the allosteric site and could not distinguish ‘non-inhibitors’ from activators. Thus fragments that did not inhibit in the Kinase-Glo assay were also run in a Caliper assay. This assay uses a shorter peptide substrate and is capable of detecting inhibition and activation. Ultimately, a subset of the original fragment hits that were either inhibitors with high ligand efficiencies, activators, and/or had very novel chemical structures were chosen for further studies.

STD competition binding experiments using the known ATP-site binder staurosporine or a short peptide known to bind in the allosteric pocket were very useful to distinguish these two binding sites. TROSY-based binding site mapping, using 15N-labeled PDK1 expressed in baculovirus, was used to confirm the binding site for several key compounds. Finally, the biochemical assay data was complemented with 19F NMR-based activity assays. These assays used the 2-fluoro-ATP method described in a previous paper from Pfizer [Journal of the American Chemical Society 130, 5870-5871 (2008)].

NMR-based activity assays proved very valuable since they could easily handle high fragment concentrations, and, since they directly monitor conversion of substrate to product, were capable of detecting both inhibition and activation. NMR-based activity assays are single-enzyme assays. As such, they are quite useful as both primary fragment screening assays and as orthogonal HTS-triage assays. NMR-based activity assays have been characterized as the ‘uncola’ of biochemical assays because, as opposed to many HTS and bench top assays, they do not rely on any coupling enzymes for their detection. NMR-based activity assays should prove very valuable for accurately evaluating compounds in the 10 uM to 1 mM dynamic range of activity typical of fragments.

Fragments in the clinic: How many?

At the Tri-Conference last week, Maria M. Flocco of Pfizer stated that a search of the IDDB3/Prous databases yielded 30 examples of compounds that had made it into the clinic from fragment-based approaches, of which 23 are still active, and 4 are in Phase II testing.

And not just in the clinic. According to her, tipranavir, an HIV protease inhibitor approved by the FDA in 2005, was derived from a 30 micromolar hydroxycoumarin fragment, back before people really thought in terms of fragments. This leads to the question, how many approved drugs could be considered the result of fragment-based drug discovery? I have argued that sorafenib fits the bill, having started from a relatively weak (17 micromolar) fragment-like screening hit. Any others?

BTW: Readers of Practical Fragments had previously identified 17 clinical compounds discovered through fragment-based methods. You can read that discussion here.