One Fragment to Rule them All

Recently, I have been riffing on the ontology of FBDD.  FBDD has become so popular that we are now seeing appropriation of the term in many papers that don't really mean it.  So, I came across this paper.  Now, don't be fooled by the title, this is about fragments, the abstract promises me so.  Let me skip the science, which to my eyes is actually quite boring, and get right to the heart of their fragment case.  

How is this paper fragments you ask?  Well, this is not about scaffold hopping or innovative uses of fragments to develop SAR.  This is not about interesting approaches to screening.  It is most certainly not about in silico approaches.  This is most certainly about fragment library design.  We often discuss here the sizes of fragment libraries and what they should look like.  One important concept we often tackle here is how big should the libraries be and what size should fragments be.  More importantly we often discuss how much of chemical space a fragment library should cover.  This paper takes an anti-Reymond approach to address that question. 

The Reymond approach tries to determine how big chemical space is, what it looks like, and what portion of it is available.  The Anti-Reymond approach identifies what is available and validates its inclusion in a fragment library.  Here is the last sentence of this paper:

"These findings...verify the value of the benzamide fragment in drug design."

Now, I was worried that benzamidine was not a valuable fragment.  This paper has removed all doubt in my mind.  Now that is settled, we can go on an validate the other 165, 999, 999,999 other possible fragments. 

Fragments vs PI3K – AstraZeneca’s turn

Last year we highlighted a paper from AstraZeneca in which they used virtual screening to identify fragments that inhibit the p110β isoform of phosphoinositide 3-kinase (PI3K), a potential anti-cancer and antithrombotic target. In two recent papers in Bioorg. Med. Chem. Lett., Fabrizio Giordanetto and colleagues describe the optimization of one of these fragments to a potent, selective molecule with in vivo efficacy.

The first paper describes the initial fragment-to-lead work. A variety of changes to fragment 1 were explored, including adding a lipophilic phenyl group to increase potency (compound 2). At the same time, modifications were explored in the central pyrimidinone ring. Although compound 3 was less active than compound 2, it also had a considerably lower logD. Many additional changes were explored, and ultimately one of the most potent compounds was compound 16. The isomeric compound 22 was less potent, but had significantly better solublility and stability in a microsomal assay.

The second paper describes subsequent optimization, ultimately yielding compound (S)-21. There’s a lot of good medicinal chemistry that I can’t do justice to here, so definitely check out the two papers themselves. Compound (S)-21 is potent, selective against the related kinase p110α, and shows good activity in a dog model of platelet aggregation without causing an increase in bleeding time.

One of the nice things about this work is the fact that the researchers used a fragment-hopping approach and were not focused on potency to the exclusion of all other properties. Although one could argue that this is simply good medicinal chemistry, it can sometimes fall into the category of what Mike Hann has memorably christened “unknown knowns,” a trap this team avoided.

Fragments vs PI3 kinase

The phosphatidylinositol-3 kinases (PI3Ks) comprise a family of lipid kinases that are important in a variety of biological pathways and have thus become popular targets for drug-discovery; earlier this year we highlighted a fragment screen out of AstraZeneca against four members of the family. In the most recent issue of Bioorg. Med. Chem. Lett., researchers from Pfizer have published their approach to one of these targets.

Samantha Hughes and colleagues first tested 5960 fragments in a biochemical assay (at 0.5-1.5 mM) to find molecules that inhibited PI3gamma. Hundreds of hits resulted, of which 150 were confirmed in full dose-response curves. These were further triaged using orthogonal methods, ultimately resulting in five X-ray structures of co-complexes, including compound 1, which binds to the hinge region of the kinase. Virtual screening of the larger Pfizer library led to the discovery of additional compounds such as compound 2. Growing compound 1 by adding an acetyl group generated compound 9, improving both potency and ligand efficiency, but synthetic challenges stymied further work. However, a closer examination of the crystal structure of compound 1 suggested a merging strategy with the previously reported compound 10 to generate compound 12, with high potency and ligand efficiency.

Astute (or paranoid) readers will notice that compound 12 contains a Michael acceptor that looks suspiciously reactive. In fact, it is closely related to the notorious rhodanines, many of which form covalent bonds with proteins and, because of the resulting promiscuity, have been accused of “polluting the literature.” Nonetheless, crystallography revealed that the compound binds (noncovalently) to PI3gamma exactly as designed. Moreover, it is fairly selective for other kinases, inhibiting only 3 out of 43 tested at 1 micromolar compound. Compound 12 is also metabolically stable, permeable, and cell active. This is a good example of why it is important not to be overly dogmatic in compound triaging, particularly at an early stage in a project.

Finally, it is worth noting that this paper comes from the storied Sandwich Laboratories, which are being closed down. If there is a silver lining to this tragedy it is that the closure has resulted in a flurry of nice publications from the site. Still, such papers hardly offset the opportunity cost of the drugs that would otherwise have been discovered there – nor the disruption caused to hundreds of scientists. Practical Fragments wishes the best of luck to all of them.

18 PI3K fragments

As we’ve noted before, kinases are a fertile field for fragment finding, but most of the targets have been protein kinases. Lipid kinases such as the phosphatidylinostide 3-kinases (PI3Ks), which mediate signal transduction by transferring a phosphate group to lipids, are also popular targets for a variety of diseases, but less has been disclosed about their suitability for fragment-based lead discovery. A paper in a recent issue of Bioorg. Med. Chem. Lett. remedies that.

Fabrizio Giordanetto and colleagues at AstraZeneca started with a homology model of p110beta (no crystal structure of this enzyme has been reported). They then used commercial software to dock 183,330 fragments selected from their corporate collection. All fragments that made at least two hydrogen bonds with the protein were organized into clusters of similar molecules and representatives of each cluster were visually inspected. This led to the selection of 210 fragments to be screened against the protein, of which 18 showed measurable activity. Structures of these fragments are provided in the paper; they range from kinase workhorses such as compound 1 to known PI3K motifs such as compound 10 to more unusual molecules such as compound 18. These hits were also tested on other members of the PI3K family, and while most showed activity across the board, others (such as compound 18) showed some selectivity.

There are some interesting structures in here; if I were starting a PI3K program I would definitely take a close look at them. Although the researchers have likely developed some of these into attractive leads, one of the virtues of fragments is that they are often so protean that different teams can start with the same fragment and end up in very different places.