ACS Fall Meeting 2012

I recently returned from Philadelphia, where the American Chemical Society held its 244^th national fall meeting. As always this was a massive affair, but fragments were well-represented, particularly in a nice session organized by Percy Carter, Debbie Loughney, and Romyr Dominique.

I opened the session by giving an introduction to fragment-screening, as well as an overview of some of the work we’re doing at Carmot. Andrew Good had perhaps the best title (“Fragment fat wobbles too”), and discussed some of the work done at Genzyme on Pim-1 kinase. Eric Manas next described some of the computational tools being used at GlaxoSmithKline, in particular strategies to deal with water. He also discussed the utility of looking for fragment analogs early in a project. In the last talk before the intermission, Chris Abell from the University of Cambridge described a number of projects from his group, starting with antimicrobial targets (such as this one); we’ll cover another in a separate post. Chris is unabashedly going after difficult targets, not just protein-protein interactions, but oligonucleotides – specifically riboswitches. There is only limited precedent for targeting RNA with fragments, so it will be fun to see how this progresses.

Francisco Talamas next described a nice example from Roche using FBLD to discover hepatitis C NS5B Palm I allosteric inhibitors. An HTS campaign of around 900,000 molecules yielded just 3 hits, none of which were advanced. A fragment screen of about 2700 fragments gave a better hit rate (5.9%), but of the 29 co-crystal structures attempted only a single structure was obtained. However, by combining the information from this crystal structure with information from other crystal structures, both proprietary and public, the researchers put together a set of rules to design a de novo fragment library tailored to this protein. This effort ultimately yielded compounds that were optimized to a clinical candidate.

Next, Nick Wurtz from Bristol-Myers Squibb described his company’s approach to discover neutral Factor VIIa inhibitors. The researchers used a combination of computational, functional, and biophysical approaches to find uncharged fragments that would bind in the P1 pocket, leading to a couple dozen crystal structures. Despite the low affinities of these fragments (typically mM), many of them could successfully be merged onto an existing series, replacing a positively charged moiety to yield potent molecules with better permeability. This is the first time I’ve seen a fragment story out of BMS, so I'm glad to see that they’re active in this area. This is also a prime example of what has been described as fragment-assisted drug discovery.

Finally, Prabha Ibrahim of Plexxikon gave a lovely overview of the discovery and development of vemurafenib, including a more detailed description of the SAR than has been presented in their earlier papers.

In addition to this dedicated session, there was a scattering of other talks and posters, including a notable poster from Timothy Rooney at the University of Oxford using fragment-based approaches to discover bromodomain inhibitors, a target class we’ve previously discussed.

A session entitled “A medicinal chemist’s toolbox” ranged over several topics of interest. Ernesto Freire of Johns Hopkins gave a great overview of thermodynamics in drug discovery, a topic we’ve previously covered. Most readers are probably familiar with the concept of enthalpy-entropy compensation, in which (for example) an added hydrogen bond fails to achieve the desired boost in potency due to unfavorable entropy. Recognizing this, he suggested that one should target groups in proteins that are already well-structured, so you don’t have to pay the cost of structuring a disordered part of the protein. He also suggested that if you introduce one hydrogen bond, you might be better off introducing a second one too, as the incremental entropic cost is likely to be low.

György Keserű of Gedeon Richter discussed the importance of avoiding lipophilicity by using tools such as LELP, which we’ve covered here and here. Continuing this theme, Kevin Freeman-Cook of Pfizer described two examples of using LLE in lead discovery programs, in particular calculating LLE values before making compounds. Although this may seem obvious, what was quite striking was the dramatic effect subtle changes in structure could make to ClogP values.

Of course, these are just a few of thousands of presentations. Please feel free to point out any that caught your eye, or expand on some of those mentioned above. And just a reminder, it’s only 4 weeks to FBLD 2012 in San Francisco – the biggest fragment event of the year!

Fragment docking: promiscuous but good enough?

Computational docking of fragments can be difficult, partly because the energetic differences between possible binding modes can be so small that it’s impossible to select the best one. In a recent paper in J. Med. Chem. Andrew Good and colleagues at Genzyme ask whether docking results are nonetheless good enough to act on.

The researchers were interested in the kinase Pim-1; we’ve previously highlighted their success using SPR-discovered fragments to generate nanomolar inhibitors of this target. In the current paper, they use the program Glide to virtually screen 13,888 fragment-sized molecules from their general collection against Pim-1. About 3% (462) of these were tested in a functional assay at 125 micromolar concentration, resulting in 46 fragments with IC50 better than 100 micromolar. Five diverse representatives of these fragments were then soaked into crystals of Pim-1, and their structures were compared with those from docking.

Overall, only two of the fragments showed a good correlation between the in silico and crystallographic models (rmsd 1.0 Å or better). However, two of the “failures” do make key hydrogen-bond interactions seen in the crystal structures, though some of the hydrophobic interactions are quite different.

As the researchers note:

Fragments that do not fill their binding pocket can exhibit promiscuous hydrophobic interactions due to the lack of steric constraints imposed on them by the boundaries of said pocket. As a result, docking modes that disagree with an observed crystal structure but maintain key crystallographically observed hydrogen bonds still have potential value in ligand design and optimization.

This seems reasonable, and is consistent with the notion that polar interactions are more directional – and thus perhaps easier to correctly dock – than more generic hydrophobic interactions.

But there may also be something more fundamental going on: the assumption seems to be that the observed crystallographic structures are definitive, but is this an oversimplification? After all, a crystallographically-derived model seldom provides more than one binding mode (though a notable exception led to the first approved fragment-based drug). Perhaps the reason it’s so difficult to score docked fragments is that fragments really can assume multiple binding modes, and our insistence on one single best model is the problem. If this is true, docking models are telling us more about reality than we are giving them credit for. NMR-based models are often presented as an ensemble of structures; perhaps the same should be done for docking? At any rate, NMR studies on Pim-1 with these fragments could prove interesting.

Fragments vs Pim-1

The three members of the Pim family of serine/threonine kinases help cancer cells proliferate and survive, and are thus interesting as potential anti-cancer targets. Structurally the kinases are also intriguing because they have a proline residue in the “hinge” region of the purine binding site, differentiating them from the other 500+ kinases in the human genome. Two recent papers describe different fragment-screening approaches against Pim-1: one case rediscovers fragments of a previously reported compound and the other identifies a new series of potent inhibitors unlike other reported kinase inhibitors.

In the first paper, published in Acta Cryst. Section D, researchers from Bayer Schering Pharma AG performed a crystallographic screen of just 36 fragments against Pim-1. Despite the small library size, a dozen of the fragments produced interpretable electron density, although only 4 of these showed activity better than 10 mM. Fragment 3, with an IC50 of 130 micromolar in an enzymatic assay, was the most potent. Interestingly, a close analog of this cinnamic acid fragment was also part of a Pim-2 inhibitor previously identified through HTS by a group from Boehringer Ingelheim. The Bayer folks synthesized this molecule (compound 1), confirmed that it is also potent against Pim-1, and found that, crystallographically, it overlays beautifully with the fragment.

The second paper, published in Bioorg. Med. Chem. Lett., describes how researchers at Genzyme used a fragment-based approach to develop potent Pim-1 inhibitors. The researchers used SPR to screen a library of about 1800 fragments at 75 micromolar concentration and then used a biochemical assay to characterize the active molecules. Benzofuran-2-carboxylic acids such as compound 10 (below) were particularly interesting: not only did they have high ligand efficiencies, they don’t look anything like typical kinase inhibitors. X-ray crystallography revealed that the bromine atom is binding in a hydrophobic pocket, while the acid is making hydrogen bond contacts with the catalytic lysine and other residues. A related fragment with comparable potency had a methoxy substituent in the 7-position, and by transforming this into a positively charged moiety the researchers were able to improve the potency to low nanomolar with a dramatic increase in ligand efficiency.

What’s also interesting is that if you overlay the two fragments from the two papers, they superimpose almost exactly on top of one another, with the carboxylic acid moieties making the same interactions – clearly a hot spot.

On a side note, as most readers are probably aware, sanofi-aventis has recently acquired Genzyme. Practical Fragments wishes all the folks in Massachusetts well during the integration.