Review of 2017 reviews

The year is done, and the darkness

Falls from the wings of Night.

As we've done since 2012, Practical Fragments is using the last post of the year to highlight conferences as well as reviews not previously discussed.

Significant events included the venerable CHI FBDD meeting in San Diego, the NovAliX Biophysics conference in Strasbourg, and the first-ever fragment conference in Shanghai. We discussed a special issue of Essays in Biochemistry devoted to structure-based drug design, and Teddy came out of retirement to provide an entertaining summary of his experience putting together a book on biophysics in drug discovery - well worth reading if you're ever tempted to edit one yourself.

As in years past, several reviews were devoted to the broad topic of FBDD. Below, I’ll outline the general reviews, followed by those focusing on particular targets, techniques, and other topics.

György Keserű (Hungarian Academy of Sciences) and Mike Hann (GlaxoSmithKline) ask “what is the future for fragment-based drug discovery?” in Fut. Med. Chem. After a concise summary of the topic, they answer that it “includes target discovery and validation, the development of chemical biology probes, pharmacological tools and more importantly drug-like compounds.” In other words, the future looks bright.

FBDD is more comprehensively covered by Ben Davis and Stephen Roughley (Vernalis) in Ann. Reports Med. Chem. This is a complete, self-contained guide to the field, covering everything from history, theory, fragment library design, and fragment-to-lead approaches. It is ideal for a newcomer, but there are enough insights throughout that it makes a rewarding read for experts too.

Of the thirty-plus fragment-derived drugs that have made it to the clinic, none are directed against neglected diseases. Gustavo Henrique Goulart Trossini and colleagues at Universidade de São Paulo review some of the work that has been done in this area in Chem. Biol. Drug Des.

And rounding out general reviews, Christopher Johnson (Astex) and collaborators examined all 28 successful fragment-to-lead programs published in 2016, defined as at least a 100-fold improvement in affinity to a 2 µM or better compound. This is a sequel to our analysis of the 2015 literature, also published in J. Med. Chem., and many of the trends are similar. Interestingly, many leads maintained high ligand efficiencies, and there was no correlation between the “shapeliness” (deviation from planarity) of fragments and that of the resulting leads. Consistent with our recent poll on the importance of structural information, 25 of the 28 examples used crystallography at some point.

Targets

Three of the success stories from 2016 involved bromodomains, the subject of an entire month of Practical Fragments’ posts last year. In Arch. Pharm., Mostafa Radwan and Rabah Serya (Ain Shams University, Cairo) review this target class, with a particular emphasis on the four BET family proteins.

More than 30% of enzymes are metalloenzymes, yet these are targeted by fewer than 70 FDA-approved drugs. One of the first published examples of FBDD involved a metalloenzyme, but most efforts have been focused on a limited set of metal-binding pharmacophores, such as hydroxamic acids. Seth Cohen (University of California, San Diego) has been steadily building libraries of metallophilic fragments, and in Acc. Chem. Res. he describes how this approach can lead to new classes of inhibitors.

Protein-protein interaction inhibitors are another underrepresented class of drugs, though one approved FBDD-derived molecule falls into this category. In Methods, Daisuke Kihara and collaborators at Purdue University look at in silico methods to discover PPI inhibitors, including fragment-based approaches.

Unlike PPIs, kinases have been highly successful drug targets. We recently highlighted one review of cyclin-dependent kinases (CDKs), and in Eur. J. Med. Chem. Marco Tutone and Anna Maria Almerico (Università di Palermo) provide another. Although the main focus is on in silico methods, there is a section on FBDD.

Techniques

As noted above, X-ray crystallography has played a role in most successful fragment to lead programs. In the open-access journal IUCrJ, Sir Tom Blundell (University of Cambridge) provides an engaging and personal view of protein crystallography, a field in which he has played a starring role, starting with his early involvement in determining the crystal structure of insulin. He also notes that the interchange of ideas and techniques between academia and industry has long been a crucial driver of advances.

NMR was the first practical method used for FBDD, so it is not surprising that there are several reviews on the topic. In Arch. Biochem. Biophys., Michael Reily and colleagues at Bristol-Myers Squibb provide a detailed overview of NMR in drug design. This covers not just the ligand- and protein-detection methods often used in fragment screening, but also more intensive techniques to characterize protein-ligand interactions.

A briefer look at many of these topics is provided by Yan Li and Congbao Kang (A*STAR) in Molecules. This review also highlights more unusual approaches such as NMR experiments on living cells.

Artifacts are a fact of life in both FBDD and HTS, and it is always important to recognize these early. In J. Med. Chem. Anamarija Zega (University of Ljubljana) discusses how NMR can help. This includes methods to detect aggregators and covalent modifiers. Of course, NMR methods can introduce their own artifacts, and these are also covered.

Other topics

Speaking of artifacts, PAINS are responsible for quite a few. The term “PAINS” has also been somewhat controversial, and in a new paper in ACS Chem. Biol. Jonathan Baell (Monash University) and J. Willem Nissink (AstraZeneca) examine the “utility and limitations” of the term Jonathan coined seven years ago. As they acknowledge, the PAINS filters were derived from just 100,000 compounds run in a limited set of assays. This means that not every bad actor will be recognized by PAINS filters, and some compounds that are may only be PAINful in certain assay formats. Like Lipinski’s rule of 5, it is important to recognize the limits of applicability. As the authors note, “the key is to remain evidence-based.”

Another sometimes controversial topic is ligand efficiency and associated metrics, the subject of an analysis in Expert Opin. Drug Disc. by Giovanni Lentini and collaborators at the University of Bari Aldo Moro. This includes extensive tables of rules and metrics, both common and obscure. The authors note that, while metrics can be useful, it is important not to use them as a “magic box.” As they quote William Blake, “to generalize is to be an idiot.”

Shawn Johnstone and Jeffrey Albert (IntelliSyn Pharma) discuss pharmacological property optimization for allosteric ligands in a review in Bioorg. Med. Chem. Lett. As we recently noted, fragments are particularly suited for discovering allosteric sites, and this paper discusses how to characterize these.

Finally, Jörg Rademann and collaborators at Freie Universität Berlin discuss protein-templated fragment ligations in Angew. Chem. Int. Ed. Earlier this year we highlighted some of his work, and this review provides a thorough analysis of both reversible and irreversible approaches, with good discussions of detection methods, chemistries, and case studies.

That’s it for the year. Thanks for reading, and especially for commenting.

And may 2018 be filled with music, and light.

New tools for NMR: 2017 edition

NMR was the first practical fragment-finding method, and continues to be popular. Just over the past year we’ve discussed several new techniques, (here, here, and here), and this post highlights three more.

In Angew. Chem. Int. Ed., Jesus Angulo and colleagues at the University of East Anglia describe differential epitope mapping by STD NMR (DEEP-STD NMR). STD NMR, the most popular of ligand-detected methods according to our poll, can provide some information as to which portions of a ligand are close to a protein, but doesn’t show where on a protein the ligand binds. In DEEP-STD NMR, two separate NMR experiments are conducted and the results compared to provide this information.

The researchers provide two implementation of the technique. In the first, the protein is “irradiated” at two different frequencies; for example, the aliphatic and aromatic regions. Protein residues that are directly irradiated will show a stronger STD to ligand protons than those that are indirectly irradiated, thus revealing whether one region of the ligand is closer to an aromatic or an aliphatic amino acid side chain. If the structure of the protein is known, this can then reveal the orientation of the ligand within the binding site. A similar experiment can be done using H₂O vs D₂O to determine whether a portion of a ligand is in close proximity to polar residues in the protein.

Water is the subject of the second paper, in J. Med. Chem., by Robert Konrat and colleagues at the University of Vienna and Boehringer Ingelheim. As we’ve previously noted, water often plays a critical role in protein-ligand interactions. The new method, called LOGSY titration, involves doing a series of WaterLOGSY experiments at different protein concentrations and plotting the signals for each proton in the ligand as a function of protein concentration; ligand protons close to the protein show steeper slopes. The researchers examine pairs of bromodomain ligands and demonstrate that LOGSY titration can confirm changes in binding mode previously seen by crystallography. The technique could also reveal what portions of the ligands make interactions with disordered water molecules, which are more difficult to detect in crystal structures.

Both of these techniques provide useful but incomplete information about ligand binding modes. A paper in J. Am. Chem. Soc. by Andreas Lingel and his Novartis colleagues describes how to generate more detailed models. The researchers used a deuterated protein in which all methyl groups (in methionine, isoleucine, leucine, valine, alanine, and threonine) were ¹³C-labeled. Multiple intermolecular NOEs between the protein and several previously characterized ligands were collected and the resulting distances fed into modeling software to produce good agreement with the known structures. More significantly, the researchers were able to use the method prospectively with two weak (0.9 and 2.8 mM) fragments. The binding models were sufficiently accurate to guide chemical optimization, resulting in molecules with 30-50 µM affinities. Subsequent crystal structures revealed that these bound as predicted. Impressively, this was done on a protein that forms 115 kD hexamers – larger than those typically tackled by NMR.

Teddy would normally close his NMR posts by stating – usually quite forcefully – whether he felt the technique was practical or not. I’m no NMR spectroscopist, so I’ll throw this question out to readers – do you plan to try any of these approaches?

Flipping fragments in PDE2

A common assumption in fragment growing is that the binding mode of the fragment remains the same throughout optimization (for example here, here, and here). However, this is not always the case (as described here, here, and here). A recent paper in Bioorg. Med. Chem. Lett. by Ashley Forster and colleagues from Merck falls into this latter category.

The researchers were interested in phosphodiesterase 2 (PDE2), which hydrolyzes the cyclic nucleotides cAMP and cGMP. PDE2 is highly expressed in the frontal cortex and hippocampus and has been implicated in cognition and proposed as a target for Alzheimer’s Disease. But because PDE2 is just one member of a large class of enzymes, selectivity is important. Indeed, Merck researchers previously used fragment-based methods to discover selective inhibitors of another member of the family, PDE10A.

In this case the researchers used both high-concentration biochemical screens as well as an SPR screen of a library of 1940 fragments, all with molecular weights < 250 Da. This resulted in 54 competitive inhibitors of PDE2 with affinities better than 200 µM. (No details were provided on numbers of hits from each screen.) Compound 1 was progressed into lead optimization due to its high ligand efficiency and attractive physicochemical properties.

A crystal structure of compound 1 bound to PDE2 revealed the potential to grow into a hydrophobic pocket exploited by previously reported molecules, leading to compound 5. Modeling suggested that bulking up the benzylic linker could improve the binding mode, and indeed compound 8 had submicromolar affinity. Surprisingly however, a crystal structure of a related molecule (having a single methyl group off the linker instead of two) revealed that the initial fragment had flipped orientation.

Further modeling suggested replacing the two methyl groups with a cyclopropyl group, as in compound 12. This simple change gave a 100-fold boost in potency, which was attributed to the free form of the compound more closely matching the bound form. Finally, the remaining methyl group was removed to reduce lipophilicity and remove a potential metabolic liability, leading to compound 16. Crystallography revealed that this binds as expected (gray), with the fragment moiety in the “flipped” conformation.

Compound 16 is at least 100-fold selective for PDE2 against a panel of other PDEs. The attention to physicochemical properties paid off in the form of good oral bioavailability, low clearance, and a satisfactory half life in rats. Although the paper does not mention how long the program took, it does state that only 25 analogs were made to get from the initial fragment to compound 16, and also mentions further optimization. This is another nice example of how the union of crystallography, modeling, and medicinal chemistry can rapidly lead to useful molecules.

Fragment activators of AMPK

Kinase inhibitors are common. Some 40% of the fragment-derived clinical compounds in our latest list target kinases. Kinase activators, on the other hand, are rare. It is easier to interfere with something than to enhance it, and of the 630+ posts on Practical Fragments, I believe only two discuss enzyme activators. A new paper (here) by Ping Lan, Iyassu Sebhat, and colleagues at Merck and Metabasis provides a third example.

The researchers were interested in adenosine monophosphate-activated protein kinase (AMPK), which plays a critical role in metabolism. As its name suggests, this kinase has naturally occurring activators, though these are nucleotides and thus not particularly useful as chemical probes. It also has fiendishly complex biology: the active enzyme is a heterotrimer of three distinct proteins, each of which comes in two or three flavors, leading to 12 different isoforms with their own unique tissue distributions – which vary among different animals.

After multiple HTS screens failed to produce anything of value, the researchers turned to fragments. Realizing that AMPK was a tough target, they assembled a library of 25,000 highly diverse fragments tending towards super-sized (all of them were greater than 200 Da, and they had up to 22 non-hydrogen atoms). A biochemical screen yielded just three hits, including compound 4.

Despite the generally larger size of fragments in the library, it is interesting that compound 4 follows the rule of three, with just 16 non-hydrogen atoms. Although only modestly active, the small size gave an impressive ligand efficiency, and the activation was nearly 80% that of the natural ligand AMP.

Rigidification of the linker between the benzimidazole and the acid moiety led to compounds such as 27, with low micromolar potency, while growing from the benzimidazole itself led to high nanomolar compounds such as compound 36. Combining these two modifications and further optimization for pharmacokinetic properties led to MK-3903, which was chosen as a development candidate.

MK-3903 activates 10 of the 12 AMPK isoforms and is fairly selective against a panel of off-targets. As predicted mechanistically, administering the compound to mice increases the phosphorylation of downstream substrates of AMPK. It also causes decreased fatty acid synthesis and increased insulin sensitivity. However, a related molecule causes cardiac hypertrophy in rats and monkeys.

In addition to the fact that MK-3903 is an enzyme activator, there are several other notable features about this story. First, despite the difficulty of the target, the team made rapid progress, moving from the initial screen to useful tool compounds in less than a year. Second, as near as I can tell, this optimization was done in the absence of direct structural information on how the compounds bind. (A publication by a separate team, who was closely monitoring the patent literature, describes the crystal structure and mechanistic analysis of a related molecule.) Third, all of this work stemmed from a single fragment: although more ligandable targets may produce lots of hits, in the end you only need one.

Finally, this paper illustrates the lag time that can occur between research and publication: several of the authors are from Metabasis, which was acquired by Ligand Pharmaceuticals way back in 2010. That was also when the patent publication describing these molecules was filed, suggesting the work could have been done a decade ago. That’s something to keep in mind when using the literature to guess who is working on fragments.