Fluorine NMR meets make-on-demand libraries

Last month Practical Fragments wrote about make-on-demand libraries, such as those offered by Enamine. We’ve also written about fluorine-detected NMR screening of fragments, which is both rapid and particularly sensitive for low affinity binders. A new paper in ChemMedChem by Patrick Penner, Anna Vulpetti, and colleagues at Novartis combines these two concepts.

 

The researchers had previously built a library of 5472 fluorinated fragments. These were compared with the 77 billion molecules then in Enamine REAL Space, which are based on a smaller set of building blocks that can be combined using validated chemistries. More than a third of the Novartis library members could be found in REAL Space, and nearly 80% had close analogs, supporting the notion that one could do rapid follow-up studies of fragment hits without requiring resource-intensive in-house chemistry.

 

To test whether this would work in practice, the researchers turned to embryonic ectoderm development protein (EED), an oncology target that Novartis has been pursuing for some time; here’s a 2017 post. An undisclosed number of known fragment ligands were screened against Enamine REAL Space using three computational methods: a search of the 180,000+ Enamine building blocks themselves, SpaceMACS to find close analogs, and FastROCS to find more distant analogs.

 

Of 150 compounds ordered across the three categories, 125 arrived: 66 building blocks, 30 close analogs, and 29 distant analogs. All of these were first tested by SPR, and nine (mostly close analogs) showed at least double-digit micromolar binding.

 

To assess whether ¹⁹F NMR could identify weaker binders, the remaining 116 compounds were screened in mixtures of nine each. This led to 43 additional hits, of which several were characterized in more detail by competing them in a dose-response format against a reporter molecule to calculate dissociation constants. One of these came in at sub-micromolar affinity, though it was a close analog of a known binder; the others were high micromolar.

 

Two of the more novel (and less potent) molecules were used as starting points to select new molecules from Enamine REAL space, and 74 of the 81 selected were delivered and tested by SPR or DSF. Two of these were more potent than the starting molecules, one of them by more than an order of magnitude.

 

In the end, although the results are modest, the paper provides a detailed framework for applying fluorine NMR to make-on-demand libraries. And with only four authors, it seems to be a low-effort approach. Although this work was done at Novartis, it should be suitable for smaller companies or academic labs that have access to an NMR.

Noncovalent fragments vs WRN

Werner syndrome helicase, or WRN, is an interesting target both for its biological mechanism and its flexible structure. Two years ago we highlighted work out of Vividion describing the discovery of a clinical-stage covalent WRN inhibitor. In a Nat. Commun. paper published earlier this year, Sandra Gabelli, Daniel Wyss, and collaborators at Merck and Proteros describe their noncovalent efforts against this target.

 

Inhibiting WRN kills cancer cells that are already defective for certain DNA repair pathways. It is an example of a “synthetic lethal” approach to drug discovery that expands the number of cancer targets by focusing on oncogenic cells rendered vulnerable by pre-existing mutations. As an ATP-dependent helicase, WRN acts as a molecular machine to unwind DNA. This requires the multidomain protein to undergo dramatic conformational changes, which makes finding ligands challenging: how do you know which conformation(s) to target? Moreover, WRN enzymatic assays are particularly prone to false positives; a paper published in 2024 demonstrated that some previously disclosed inhibitors are at best nonspecific, and at worst downright artifacts. Thus, the researchers chose to use biophysics to identify fragments.

 

A library of 1020 fluorine-containing fragments was screened in pools of up to 21 compounds using ¹⁹F NMR T₂ CPMG experiments. The 31 primary hits were re-screened as pure compounds in this assay as well as three more ligand-detected NMR assays, leading to seven hits taken into crystallography, of which three yielded structures. A separate SPR screen of 500 non-fluorinated fragments followed by confirmation by NMR led to three additional fragments characterized crystallographically. None of the validated fragments from either screen showed functional activity in an enzymatic assay.

 

The fragments bound in three different sites on the protein, which itself underwent significant conformational changes to accommodate the fragments. Fragments 1 and 2 bound in the same site and could be partially superimposed on one another, and these were used to generate a virtual library, of which 17 compounds were made and tested. Compound 4 had the best affinity as assessed by SPR and was also active in a functional assay.

Crystal structures of some of the other compounds bound to WRN were also determined, and these showed significant protein domain rearrangements, even when the compounds themselves were structurally similar. The researchers include a nice movie (link to download here) and suggest that “these structures capture only a few states of WRN as it translocates along the DNA and conducts its helicase and exonuclease functions.”

 

This paper nicely illustrates the challenges of finding ligands, particularly noncovalent ones, against conformationally flexible proteins. We’ll revisit this topic next week.

Fragment merging – and flipping – on the leucine zipper of MITF

Transcription factors can be difficult drug targets, particularly those whose primary structure is a “leucine zipper” in which two α-helices gently coil around each other. Their three-dimensional structure provides few pockets suitable for binding small molecules. In a new (open-access) paper in Nat. Commun., Deborah Castelletti, Wolfgang Jahnke, and a large group of multinational collaborators at Novartis and elsewhere present progress toward one of these, microphthalmia-associated transcription factor (MITF), which has been implicated in melanoma.

 

Most of MITF is believed to be disordered, but the DNA-binding domain (DBD) homodimerizes as a basic helix-loop-helix leucine zipper. Unlike related transcription factors, the helices in MITF contain a small kink that keeps them from heterodimerizing and also creates a small “kink pocket.”

 

The researchers expressed the DNA-binding domain of MITF and screened it using ¹⁹F NMR against the LEF4000 library, which we described here. This yielded just 9 hits that confirmed in protein-observed NMR, a hit rate the researchers note “is amongst the lowest that we have observed across multiple FBS campaigns,” consistent with expectations for a difficult target. Two chemical series, represented by compounds 1 and 2, were prioritized, and analogs from the Novartis compound collection were screened to find more-potent compounds 3 and 4.

 

Crystallography revealed that compounds 3 and 4 both bound in the kink pocket. Excitingly, the binding modes are similar and overlapping, inviting fragment merging. This proved successful, yielding a compound that bound 100-fold more tightly than either fragment. Further optimization ultimately led to compounds 7 and 8, with low or sub-micromolar affinity as assessed by isothermal titration calorimetry (ITC).

 

The bound structures of compounds 7 and 8 were determined by crystallography. Compound 7 (gray, left) superimposes nicely onto compounds 3 (cyan) and 4 (magenta), showing successful fragment merging. Compound 8 (green, right), however, is flipped 180 degrees compared to compound 7, despite having similar structure and affinity. Although surprising, this is not too uncommon; we’ve written about previous flippers here, here, and here.

The MITF homodimer is asymmetric, with one helix kinked and the other straight. NMR experiments and molecular dynamics show that both compounds 7 and 8 slow the interconversion between kinked and straight forms, though it is unclear whether this has functional implications. The compounds do not seem to affect DNA binding, and with at best high nanomolar affinity towards MITF no cell data are reported with the molecules.

 

Nonetheless, the successful identification of ligands against a leucine zipper is exciting. The binding pocket is small; as shown in the figure above, the best compounds already stick out on either side of the helices. Further affinity improvements may be difficult, though perhaps covalent approaches could help. Alternatively, perhaps these molecules could be starting points for induced proximity strategies such as PROTACs. It will be fun to watch this story develop.

NMR for SAR: All about the ligand

In last week’s post we described a free online tool for predicting bad behavior of compounds in various assays. But as we noted, you often get what you pay for, and computational methods can’t (yet) take the place of experimentation. In a new (open-access) J. Med. Chem. paper, Steven LaPlante and collaborators at NMX and INRS describe a roadmap for discovering, validating, and advancing weak fragments. They call it NMR by SAR

 

Unlike SAR by NMR, the grand-daddy of fragment-finding techniques which involves protein-detected NMR, NMR for SAR focuses heavily on the ligand. The researchers illustrate the process by finding ligands for the protein HRAS, for which drug discovery has lagged in comparison to its sibling KRAS.

 

The researchers started by screening the G12V mutant form of HRAS in its inactive (GDP-bound) state. They screened their internal library of 461 fluorinated fragments in pools of 11-15 compounds (each at ~0.24 mM) using ¹⁹F NMR. An initial screen at 15 µM protein produced a very low hit rate, so the protein concentration was increased to 50 µM. After deconvolution, two hits confirmed, one of which was NMX-10001.

 

The affinity of the compound was found to be so low that ¹H NMR experiments could not detect binding. Thus, the researchers kept to fluorine NMR to screen for commercial analogs. They used ¹⁹F-detected versions of differential line width (DLW) and CPMG experiments to rank affinities, and the latter technique was also used to test for compound aggregation using methodology we highlighted in 2019. Indeed, the researchers have developed multiple tools for detecting aggregators, such as those we wrote about in 2022.

 

Ligand concentrations were measured by NMR, which sometimes differed from the assumed concentrations. As the researchers note, these differences, which are normally not measured experimentally, can lead to errors in ranking the affinities of compounds. The researchers also examined the 1D spectra of the proteins to assess whether compounds caused dramatic changes via pathological mechanisms, such as precipitation.

 

The researchers turned to protein-detected 2D NMR for orthogonal validation and to determine the binding sites of their ligands. These experiments revealed that the compounds bind in a shallow pocket that has previously been targeted by several groups (see here for example). Optimization of their initial hit ultimately led to NMX-10095, which binds to the protein with low double digit micromolar affinity. This compound also blocked SOS-mediated nucleotide exchange and was cytotoxic, albeit at high concentrations.

I do wish the researchers had measured the affinity of their molecules towards other RAS isoforms as this binding pocket is conserved, and inhibiting all RAS activity in cells is generally toxic. Moreover, the best compound is reminiscent of a series reported by Steve Fesik back in 2012.

 

But this specific example is less important than the clear description of an NMR-heavy assay cascade that weeds out artifacts in the quest for true binders. The strategy is reminiscent of the “validation cross” we mentioned back in 2016. Perhaps someday computational methods will advance to the point where “wet” experiments become an afterthought. But in the meantime, this paper provides a nice set of tools to find and rigorously validate even weak binders.

Fragments vs hIL-1β: Growing into a cryptic pocket to inhibit a protein-protein interaction

Protein-protein interactions have a well-deserved reputation for being difficult to drug with small molecules. This is particularly true for cytokine-receptor pairs, which are involved in a host of extracellular signaling functions. Human interleukin-1β (hIL-1β) plays a key role in inflammation by binding to its receptor IL-1R1. Biologics such as anakinra and canakinumab have been approved as drugs, but apart from some very low affinity fragments no small molecule inhibitors are known. In a new (open access) Nat. Commun. paper, Frédéric Bornancin, and collaborators at Novartis and University of Leicester report the first.

 

The researchers started by screening the 3452-compound LEF4000 library, which we described here, using ¹⁹F-NMR. After confirmation using protein-observed 2D NMR just a single super-sized fragment hit remained, consistent with the difficulty of the target. The individual enantiomers of this racemic compound were studied, and only (S)-1 was found to be active. Further characterization revealed that, despite weak affinity, this compound had both slow association and dissociation rates. More on that below.

 

Fragment growing in multiple directions led to mid-micromolar compounds such as 11 and 12. Combining elements from these molecules ultimately led to compound (S)-2, with low micromolar affinity as assessed by SPR. 

 

 

Compound (S)-2 specifically blocked the binding of hIL-1β with its receptor IL-1R1, but did not inhibit the binding of the related cytokine hIL-1α to IL-1R1. Even better, the compound blocked IL-1R-mediated signaling in cells at low micromolar concentrations in two different assays. The similar activity in biochemical and cell assays is likely due to the fact that the compound only needs to act at the cell surface, so permeability is not an issue, in contrast to our post last week.

 

A crystal structure of (S)-2 bound to hIL-1β revealed important interactions between the protein and both the phenol and lactam nitrogen, two contacts that were maintained during fragment optimization. The structure explains why only the (S)-enantiomer is active, as maintaining these contacts would cause clashes for the other enantiomer.

 

The structure also explains the mechanism of inhibition. (S)-2 binds to a cryptic pocket that forms in a region of hIL-1β important for interacting with IL-1R1, and formation of the pocket involves a loop movement that would be incompatible with the protein-protein interaction. The researchers argue convincingly that that the compound stabilizes the cryptic pocket, which naturally exists as a minor population within solution. This also explains the slow kinetics, which would be expected if the compound essentially has to wait until the cryptic pocket opens before it can bind.

 

There is still a long way to go to a drug. Not only is the affinity of (S)-2 modest, the two carboxylic acid moieties and the phenol are likely to impede oral bioavailability. Nonetheless, this is a lovely paper, and the researchers point out that cryptic pockets frequently involve “large movements of secondary structural elements” that could block biological function. Indeed, this is the case for approved drugs such as sotorasib. Don’t give up just because your protein of interest appears like a featureless billiard ball: there may well be opportunities hidden just beneath the surface.

RSC Medicinal Chemistry special FBDD issue

The Royal Society of Chemistry puts out RSC Med. Chem., and last year they asked David Rees (Astex), Anna Hirsch (Helmholtz Institute for Pharmaceutical Research Saarland), and me whether a special themed issue on FBDD would be useful for the community. Naturally we said yes, and the results have now been published. You can read our introduction here.

 

Unlike olden days, when special issues were bound between covers, this is a virtual special issue, with papers published over a period of several months. Indeed, we already wrote about two of them last year: one on combining DNA-encoded libraries (DEL) with FBLD and one on inhibitors of PRMT5/MTA. (Both of these were also topics at the CHI FBDD meeting earlier this month.) In the next few paragraphs we highlight the rest.

 

AstraZeneca has been doing FBDD since 2002, and has gained hard-won wisdom, some of which was shared in a 2016 review we wrote about here. After years of screening, their fragment library had started to deteriorate, so they rebuilt it entirely, as described by Simon Lucas and colleagues. Some of the starting fragments came from their previous library, but they also considered molecules from their larger collection. Rather than focusing on the rule of three, they developed their own multiparameter optimization function, “FragScore,” which incorporates logD_7.4, heavy atom count, number of rotatable bonds, and number of hydrogen bond donors. All compounds were inspected to make sure they would be synthetically tractable, and quality was assessed by SPR, NMR, redox activity, and solubility. The final set consists of 2741 fragments, with a subset of 1152 maximally diverse and attractive fragments for ligandability assessments or screening hard-to-make proteins. They also gathered 16,806 near neighbors for hit follow-up. So far the effort has paid off, with all four of the targets screened thus far yielding progressible hits. If you’re building or renovating a fragment library, you should read this paper.

 

Continuing on the theme of libraries, Bradley Doak, Martin Scanlon, and colleagues at Monash University describe their “MicroFrag” library, a set of 91 tiny (5-8 non-hydrogen atom) compounds similar to MiniFrags and FragLites. A crystallographic screen (at 1 M concentration!) of the MicroFrag library against the difficult E. coli target DsbA yielded a 52% hit rate, compared with a 2% hit rate with a conventional fragment library. Importantly, the MicroFrag screen identified the two main hot spots previously discovered from the conventional fragment library, along with ten others that may be less actionable. Interestingly, a crystallographic screen of 15 organic solvents at even higher concentrations (50-80%) was less informative: the primary hot spot did not distinguish itself from others. In the case of MicroFrags, not only did this hotspot bind the largest number of fragments, but all the molecular interactions seen for larger fragments were observed.

 

Fluorine NMR takes advantage of its own specialized library, the subject of a paper by Chojiro Kojima (Osaka University), Midori Takimoto-Kamimura (CBI Research Institute) and collaborators from several institutions. The researchers describe the construction of a 220-member library divided into pools of 10-21 compounds. This library was screened against four diverse proteins, yielding between 3 and 16 hits. The three hits against FKBP were characterized in more detail, including two-dimensional NMR and isothermal titration calorimetry. The researchers also discuss using ¹⁹F STD experiments to determine the binding mode of bound fragments.

 

Fluorine is not the only halogen of interest for library design. We’ve previously described the halogen-enriched fragment library (HEFLib, here and here), which consists of chlorine, bromine, and iodine-containing molecules. Frank Boeckler and collaborators at Eberhard Karls Universität Tübingen and the Max Planck Institute describe screening this library against the Y220C mutant of p53 in an expansion of work they first described back in 2012. Of 14 hits identified by thermal shift or STD NMR, ten confirmed by two-dimensional ¹H-¹⁵N-HSQC NMR. Four of these bound in the cleft created by the Y220C oncogenic mutation. Two other fragments turned out to be covalent binders, though they reacted with more than one cysteine residue. Although all the fragments have low affinities, they could potentially serve as starting points for optimization.

 

An ongoing debate is whether there is an advantage to screening more “three dimensional” fragments as opposed to planar aromatic fragments. If your taste tends towards the former, the synthetic chemistry can get tricky. According to an analysis we highlighted last year, the piperidine ring is the third most common scaffold found in drugs. Now, Peter O’Brien (University of York) and an international group of collaborators report efficient synthetic routes to all 20 cis- and trans-piperidines substituted with a methyl group and a methyl ester. A virtual library of 80 compounds in which the secondary amine is capped with simple substituents such as methyl or acetyl groups was found to be quite shapely, particularly compared with the disubstituted pyridyl starting materials. Moreover, the fragments are still reasonably sized, with no more than 15 non-hydrogen atoms and ClogP values < 2.

 

Machine learning is gaining prominence everywhere, not least in drug discovery. In 2021 we highlighted an “autoencoder” designed for constructing fragment libraries biased towards “privileged” fragments more likely to generate hits. However, the method required considerable programming savvy. Now Angelo Pugliese (BioAscent) and collaborators at the Beatson Institute have implemented their model in the open-source KNIME platform, making it accessible to a wider range of researchers. As an example they use the method to construct a GPCR-focused fragment library, with the structures of all the members provided in the supporting information.

 

On the subject of fragment libraries, please make sure to vote in our 6-question poll on library design (right side of page; you may need to scroll up).

 

Not all the papers in this special issue involve library design. Marko Hyvönen, David Spring, and collaborators at University of Cambridge and National University of Singapore describe allosteric inhibitors of the kinase CK2α, which has been implicated in cancer cell survival. We highlighted some of their work against this target in 2017, in which they used fragment linking to find high nanomolar inhibitors of the enzyme. In the new paper, the researchers describe additional fragment binders at the so-called αD pocket, distant from the ATP-binding site. Virtual screening for analogs led to a fragment with mid-micromolar activity in biochemical and cell assays, and fragment merging led to low micromolar inhibitors.

 

This is a nice collection of papers, and for those of you without easy literature access make sure to check them out soon: for the next six months all of them are free to read after free RSC registration. Enjoy!

Pacifichem 2021

Pacifichem, the last significant conference of 2021, has just ended. Traditionally held every five years, these meetings usually bring thousands of visitors from Pacific Rim countries to Honolulu. They are planned years in advance: symposia proposals were due in early 2018. Pacifichem 2015 saw the first symposium dedicated to FBLD, and that was so popular that a few of us planned one for 2020. The conference organizers decided to postpone the 2020 meeting in the hope that we could all meet in person. But SARS-CoV-2 had other plans, and instead of meeting in Hawaii we met on Zoom.

 

Time zones were challenging. Four-hour sessions started in the morning or evening Hawaiian time, which translated to 02:00 in Shanghai or 23:00 in Boston, respectively. In contrast to other virtual meetings almost all the presentations were live and not recorded, which meant that you only had one chance to see a talk.

 

Despite these challenges and universal Zoom-fatigue, the event came off quite well. With more than two dozen presentations I won’t attempt to cover everything but will instead just touch on a few themes.

 

Methods

Quite a few talks focused on methods, with NMR being especially well-represented. The symposium started with Will Pomerantz (University of Minnesota) discussing Protein-Observed Fluorine (PrOF) NMR, in which fluorinated amino acids are introduced into proteins. We’ve written about this previously, including Will’s longstanding interest in assessing shapely fragments. After reading about Mads Clausen’s fluorinated Fsp³-rich library, Will established a collaboration and has found 8 hits from 79 fragments screened against BET bromodomain proteins. He has also been able to optimize potent leads selective for either the BD1 or BD2 domains of BRD4.

 

Scott Prosser (University of Toronto) is also using NMR to study fluorine-labeled proteins, in this case GPCRs. And Michael Overduin (University of Alberta), one of the symposium organizers, is also studying membrane-bound proteins using NMR techniques.

 

On the extreme side of spectrometers, Chojiro Kojima described the 950 MHz NMR at Osaka University. This enables a ¹H-¹³C HSQC experiment on protein as dilute as 0.2 micromolar, which could be valuable for insoluble or hard-to-purify proteins. The facility is open to international collaborators. Chojiro also described isotopically labeling proteins with transglutaminase and ¹H{¹⁹F} STD NMR, which works even when the fluorine peak itself is broadened to invisibility.

 

But you don’t need a big magnet to do good science. Brian Stockman’s group at Adelphi University is composed entirely of undergraduates who use substrate-detected NMR to follow enzymatic reactions to find inhibitors of neglected parasitic infections.

 

All techniques can give false positives, and NMR can be very effective at weeding these out. As we described two years ago Steven LaPlante (NMX) has been developing methods to rapidly identify aggregators and has been assembling something of a taxonomy; more later.

 

But the conference was not all NMR all the time. Rebecca Whitehouse (Monash University) described a 91-compound “MicroFrag” library consisting of fragments containing 5-8 atoms, “somewhere in the land between solvents and fragments.” NMR and crystallographic screens of the difficult antimicrobial target DsbA gave very high hit rates, and both techniques successfully identified the large but shallow substrate-binding groove. In contrast, screening actual solvents or using the well-established FTMap computational approach did not clearly identify this groove.

 

The push in crystallography is towards increased speed, and Debanu Das described the high-throughput platform at Acclero BioStructures, which is capable of screening 1000 fragments per week, similar to XChem. But if even that is too slow for you, Marius Schmidt (University of Wisconsin-Madison) described mix-and-inject experiments using the European X-ray free-electron laser (XFEL). Much of the focus with this technique has been on high-speed enzymology, but since 100 datasets can be collected in 10 hours it can be used for high-throughput crystallographic screening too. An upgrade next year will increase this to 1000 datasets in 3 hours, though the resulting petabytes of data will no doubt create headaches for IT departments.

 

It’s not enough to find hits, you need to figure out what to do with them, and symposium organizer Martin Scanlon (Monash University) discussed a computational approach (GRADe, similar to Fragment Network) as well as the experimental (REFiL) approach we’ve discussed previously. Across 9 projects the techniques were successful at improving affinity, in some cases from unmeasurable levels.

 

Covalent Fragments

Several talks focused on covalent FBLD. Alexander Statsyuk (University of Houston) proposed five rules for covalent fragments: 1) ease of synthesis; 2) non-promiscuous electrophiles; 3) intrinsic reactivity should be the same within the library; 4) a given library should use the same electrophile; and 5) the electrophile should be on the end of the molecule with a minimal linker connecting it to the variable fragment. Some of these make sense, but it would have been fun to debate others over Mai Tais.

 

Dan Nomura (UC Berkeley) described using covalent fragments in chemoproteomic experiments, where he has identified more than 100,000 potentially ligandable hotspots in more than 16,000 human proteins. Among other applications, this allows him to make bifunctional molecules to bring two proteins together. A clear application is PROTACs, where the electrophilic fragment targets an E3 ligase, but he also described targeting the deubiquitinase OTUB1 to stabilize proteins.

 

Earlier this year we celebrated the approval of the KRAS^G12C inhibitor sotorasib. This target had long resisted drug discovery efforts; Ratmir Derda (University of Alberta) evocatively mentioned “waves and waves of medicinal chemists washing off its shore for 30 years.” Success was finally enabled using disulfide Tethering, and David Turner (Frederick National Laboratory) is now using this approach to interrogate nearly every surface-exposed residue by systematically mutating them to cysteines and screening against more than 1000 disulfide-containing fragments. He is well over half-way through the 85 mutants, and the resulting dataset should be valuable not just for drug discovery but for understanding molecular interactions.

 

Success Stories

With more than 50 drugs in the clinic derived from fragments, there were several success stories. Masakazu Atobe (Asahi Kasei) presented the discovery of the potent PKCζ inhibitors we wrote about here. And Chaohong Sun (AbbVie) described inhibitors of TNFα (see here), emphasizing the importance of robust biophysics and early committed chemistry.

 

Finally, Emiliano Tamanini (Astex) presented a nice fragment-to-lead effort to find a selective inhibitor of HDAC2. Despite some successes, histone deacetylase inhibitors tend to be non-specific and come with side effects. Emiliano described a fragment screen that identified a new metal chelator and used fragment merging to develop a molecule capable of crossing the blood-brain-barrier.

 

These last two stories in particular are examples of pursuing difficult targets, another theme throughout the conference. When asked about the challenges of targeting cancer-resistance-causing glucuronosyltransferases, Katherine Borden (University of Montreal) responded, “if you don’t try, where will you be?”

 

Bright words for these darkling days.

Fragment mixtures vs protein mixtures

In FBLD – as in most areas of research – speed and efficiency are prized. The faster you can find quality fragments, the faster you can advance them. NMR-based screening remains one of the most popular fragment-finding methods, and in a recent Molecules paper William Pomerantz and collaborators at the University of Minnesota and Gustavus Adolphus College provide an accelerated workflow.

 

The Pomerantz lab is well known for protein-observed ¹⁹F (PrOF) NMR, in which fluorine-labeled residues are incorporated into proteins. This is easily accomplished by supplementing the media with fluorine-containing amino acids during protein expression. To date more than 15 fluorinated amino acids have been tested in more than 70 proteins, ranging from 7 to 180 kDa in size. Because the chemical shift of fluorine is so sensitive to its environment, a fragment binding nearby can be readily detected by PrOF NMR.

 

When a single type of amino acid is fluorinated, the resulting protein spectrum is considerably simpler than in traditional protein-observed NMR methods. Taking advantage of this, the researchers mixed two different bromodomain proteins: the human oncology target BPTF and PfGCN5 from the malarial parasite Plasmodium falciparum. Both of these bromodomains contain a tryptophan in their N-acetyl-lysine binding sites, so each protein was labeled with 5-flurotryptophan. The proteins were then screened (at 50 µM each) against 467 fragments from Life Chemicals in pools of 4-5 (at 400 µM each). Chemical shift perturbations of the binding-site tryptophan were seen for half of the 98 pools. To determine which fragments were responsible for these shifts, the researchers tested their fragment mixtures against the relevant proteins using (ligand-detected) CPMG NMR. Since they had previously determined the ¹H NMR spectra of all their fragments, it was easy to pick out the binders.

 

Hit rates were similar for both BPTF (9.8%) and PfGCN5 (9.2%), and 4.1% of fragments hit both bromodomains. The researchers had previously screened this library, which is enriched for shapely fragments, against the bromodomain BRD4 D1 (see here) and obtained a similar hit rate. Statistical analyses revealed that the 3D-character for PfGCN5 hits is similar to the library as a whole, as had also been seen for BRD4 D1, while the BPTF hits tended to be flatter.

 

The researchers also followed up on several  fragments individually. One in particular had low micromolar affinity for PfGCN5 as assessed with both PrOF NMR and ¹H-¹⁵N HSQC NMR titrations. Interestingly, this fragment also caused a chemical shift in a different 5-fluorotryptophan residue some 22 Å away from the canonical binding site. Binding at this site could not be competed by a known high-affinity ligand, and a computational screen using FTMap suggested that this does appear to be a secondary binding site.

 

Overall this approach appears to be an appealing workflow as judged by comparing required time, protein, and ligand amounts to other NMR-based screening cascades. As the researchers note, it is advantageous to assess both protein and ligand behavior, as done here. Have you tried using PrOF, and if so how has it performed for you?

Fragments vs (lots of) RNA

RNA is hot. Hundreds of millions of dollars have gone to startups focused on finding small molecules that bind RNA, and plenty of large pharmaceutical companies are pursuing this class. As with all difficult targets, fragments have a role to play, as demonstrated by a paper just published (open access!) in ChemBioChem by Harald Schwalbe and collaborators at Johann Wolfgang Goethe-University Frankfurt and Saverna Therapeutics.

 

The researchers assembled a collection of 101 fluorine-containing fragments and pooled these into five sets of 20-21 compounds each. These were then screened (at 50 µM) against 14 different RNA targets, ranging from 14-nucleotide hairpins to a 127-nucleotide riboswitch. The primary screen was ligand-detected ¹⁹F NMR using CPMG, in which ligand binding causes a change in relaxation which is detected as a decreased signal. All hits from the mixtures were confirmed as single molecules. To assess selectivity, all the compounds were also screened against 5 DNA targets and 5 proteins.

 

The results are not entirely unexpected. Some of the fragments did not hit any targets, while others were rather promiscuous: a couple showed strong binding to 8 of the 14 RNA targets. That said, strong is a relative term; the highest affinity of any fragment measured was 375 µM.

 

The RNA targets spanned a variety of structures, but the most hit-rich were aptamers and riboswitches, which bind specific small molecules or ions. These had 7 to 26 hits each. In contrast, the other RNA targets tested all had six or fewer fragment hits. For the aptamers, competition experiments with the natural ligands suggested binding at the orthosteric sites in some cases but not others.

 

Hit rates against four of the five proteins were also high, with 16 to 55 hits each. The fifth protein, a challenging phosphatase, had only four hits. This was still better than the 24-nucleotide DNA duplex, with a single hit. The four G-quadruplex DNA targets had between 12 and 20 hits, consistent with prior research. Taken together, the results suggest that RNA riboswitches and aptamers may be reasonably ligandable, while RNA targets that do not normally bind small molecules may be more challenging.

 

The researchers also conducted cheminformatic analyses. Not surprisingly given the relatively small library, there were no strong correlations between molecular features and targets bound, though fragments that hit had a slight tendency towards more aromatic atoms and fewer sp³-hybridized carbons. This is consistent with a vigorously debated paper we highlighted in July.

 

Finding weak hits is one thing, but advancing them has been challenging for RNA targets. The researchers provide an example in which they link a fragment to an intercalator to generate a low micromolar binder, but intercalators are often nonspecific, and affinity would still need to be further improved. Practical Fragments first highlighted a fragment screen against RNA more than a decade ago, and earlier this year we noted a high nanomolar binder, but I have yet to see an attractive low nanomolar lead emerge.

 

Nonetheless, this paper provides a solid launching point for such an effort to succeed. In particular, the researchers laudably include structures of all the library members as well as the raw screening data of all the hits on all the targets in the Supporting Information. If you are feeling adventurous, you now have plenty of starting points to choose from.

Eighteenth Annual Discovery on Target Meeting

Last week CHI held Discovery on Target – virtually of course. There were 20 tracks over three days and more than 650 attendees, down from 1100+ last year. Because the event was more fragmented (pun intended) than the recent DDC, which had at most four parallel tracks, the Q&As and discussions seemed smaller, though that could have just been the ones I attended. On the other hand, one of the huge advantages of the format is being able to watch concurrently scheduled talks later. More thoughts on virtual conferences are here, and if you have not already done so please take our poll on the right side of the page.

 

This conference has always been more biology-focused than DDC, with tracks on antibodies, immunology, NASH, gene therapy, disease modeling, and fibrosis, among others. But there were also plenty of talks on targets and methodology, which is where I’ll focus most of this post. Please add your highlights and thoughts in the comments.

 

Julien Orts (ETH Zurich) presented an update on his NMR² method, which uses information from intermolecular NOEs to computationally determine protein-ligand structures without requiring full NMR assignment of the protein. We wrote about this technique in 2017 and at the time we questioned how applicable it would be to fragments due to low affinities, multiple binding modes, and fewer contacts. As it turns out, very: Julien described successes with proteins including HDM2, DsbA, bromodomains, and Pin1. Even with as few as 10-12 intermolecular NOEs he has been able to get good agreement with crystal structures. Currently he is applying this approach to SARS-CoV-2 proteins as part of the COVID-19-NMR project.

 

William Pomerantz (University of Minnesota Twin Cities) also presented NMR techniques. He is particularly known for his protein-observed ¹⁹F (PrOF) NMR screening, in which fluorinated tyrosine and tryptophan residues are introduced into proteins. Ligand binding changes the chemical shifts of the fluorine atoms, and by varying the concentration of the fragment, accurate dissociation constants can be determined. In early work, a screen of 930 fragments in pools of 5 against BRD4 took 11 hours (and another 11 hours for deconvolution) and provided multiple hits. We’ve covered some of his more recent work using shapely fragments here, and in unpublished work he has been screening the dual-domain construct of BRD4 and finding fragments that are ten-fold selective for one over the other bromodomain. He is further improving throughput by screening two proteins simultaneously.

 

Rounding out NMR, Andrew Petros (AbbVie) presented a beautiful fragment-to-lead success story on TNFα, a trimeric cytokine that has been the subject of numerous (often unsuccessful) lead-discovery efforts. A 2-dimensional NMR screen of 18,000 fragments gave just 11 hits. Crystallography of one showed two copies binding in close proximity, and linking these ultimately led to a low nanomolar binder. The series showed high clearance and no oral bioavailability, so they performed additional screens to identify different fragments that were ultimately advanced to potent compounds with animal efficacy. I look forward to reading the paper when it is published.

 

Finding fragments is important, but so is avoiding artifacts, the subject of a talk by Samantha Allen (Janssen). Around 2% of screening compounds can form small molecule aggregates that can interfere with assays, and if these aren’t weeded out they can quickly overwhelm an assay. Samantha described the use of resonance waveguide grating (RWG) technology, as used in the Corning Epic BT. This label-free technology is similar to SPR, but RWG can be run in 384 or 1536 well plates. Samantha showed that RWG compares favorably to dynamic light scattering for detecting aggregates. It is also 4-5 times faster and less prone to false-positives.

 

Covalent fragments were a theme of last month’s DDC, and they were prominent here as well. Four years ago we highlighted work out of Ben Cravatt’s lab doing covalent fragment screening in cells, but this was a rather time-consuming process. Steve Gygi (Harvard) has streamlined activity-based protein profiling and was able to screen 288 fragments in just 7 days and identify more than 1500 modified cysteine residues.

 

Dan Nomura (UC Berkeley) continued the theme with a wide-ranging presentation using chemoproteomics to discover covalent ligands for a variety of targets, including new E3 ligases, which can be used for developing targeted protein degraders. (Shameless plug/disclosure: Dan Nomura is a founder of my company, Frontier Medicines, and we are actively hiring across multiple positions and levels.)

 

Targeted protein degraders such as PROTACs were the subject of one track at last year’s DoT meeting, and this year two sequential tracks were devoted to the topic. As I suggested in 2018, fragments could be ideal starting points given that high affinity is not always necessary. This year, Stewart Fisher confirmed that he and his colleagues at C4 Therapeutics often “detune” chemical matter, lowering the binding affinity to get efficient degraders. That doing so can improve physicochemical properties is a nice bonus.

 

Finally, although not directly fragment-related, William Kaelin (Dana Farber Cancer Institute) gave an inspiring talk on the discovery and development of MK-6482, an allosteric HIF2α inhibitor in late-stage clinical trials for cancer linked to Von Hippel-Lindau disease; data released just last week shows durable responses in patients with kidney cancer. The science itself was lovely, but he reminded us of the ultimate stakes: “It’s not about what journal your paper is published in or whether you can fool reviewer 3, it’s about whether you publish things that are true and robust and can be built upon by others.”

 

Words to live by.

Broadening the scope of 19F NMR

Over the past decade, fluorine NMR has established itself as a powerful fragment-finding method due to the advantages Teddy laid out in his classic “fluorine fetish” post. One feature of ¹⁹F NMR is that the chemical shifts of organofluorine molecules span a very wide range, in theory allowing large mixtures to be screened. However, existing NMR methods do not work across such large spectral windows, thereby requiring multiple experiments to screen an entire library. This limitation has now been overcome as described in a paper just published in Angew. Chem. by Andreas Lingel, Andreas Frank, and collaborators at Novartis and Karlsruhe Institute of Technology.

The researchers developed an experiment based on “broadband universal rotation by optimized pulses” (BURBOP). I confess that the details evade me (though they are all there in the supporting information if you wish to try it at home), but the upshot is a type of CPMG experiment in which fluorine-containing fragments bound to a protein show decreased peak intensities. Crucially, a single experiment can cover the full frequency range of pharmacologically relevant fluorine-containing molecules, spanning about 210 ppm. Previously, this required four two separate experiments.

Such increased throughput led the researchers to revamp their library, increasing the size from 1600 to 4000 fragments in an augmented library dubbed LEF4000. The paper has a nice, broadly applicable description of their curation process. Candidate members were brought in from both commercial and in-house sources and chosen to complement existing library members in terms of diversity. A modified rule of three was applied, with trifluoromethyl-containing fragments allowed to go up to 350 Da.

An in-house analysis of 25,000 fragments revealed that only about half of those with a clogD_7.4 greater than 3 were soluble above 0.5 mM, so this was applied as an upper limit. Fragment solubilities were experimentally measured, and only compounds with solubilities above 0.2 mM were kept. (Although fluorine NMR is often done at low concentrations, complementary biophysical experiments are not.) Additional quality control measures included NMR and LC-MS purity assessments and removal of compounds that formed soluble aggregates as assessed by CPMG. Ultimately, 3969 of 5600 candidate molecules passed the gauntlet, and were combined in 131 mixtures of about 30 compounds each.

Having built their library, the researchers screened it against the antibacterial target CoaD, which is involved in coenzyme A synthesis. The screen took just two days, and automated hit identification took only a few hours on a standard laptop. The overall hit rate was ~6%, and some of the hits were confirmed using two-dimensional protein-observed NMR methods, revealing that they bind in the enzyme active site with affinities in the mid micromolar to low millimolar range.

Pushing the technique further, the researchers built a “Supermixture” of 152 compounds, including five of the hits spanning a wide range of chemical shifts, from -50 to -220 ppm. Even under these conditions the binders were readily identifiable, and the paper states that libraries exceeding 20,000 fragments could in principle be screened in a few days.

In 2009 I wondered why ¹⁹F NMR was not used more widely. How things change! At Novartis the LEF4000 library has been screened against “a wide variety of disease-related targets” and identified “tractable hits for each of the screened targets, among them many considered undruggable by small molecules such as transcription factors, a cytokine, a nuclear receptor, and a repeat RNA.” Practical Fragments looks forward to seeing some of these appear in the growing list of FBDD-derived clinical candidates.

Three dimensional fragments revisited

A long-running debate in the fragment world centers on the utility of “three dimensional” fragments. Proponents argue that these (often aliphatic) fragments may be more novel, have better physicochemical properties, and have more vectors for elaboration than “flatter” (mostly aromatic) molecules. Skeptics retort that hit rates are likely to be lower for these more complex molecules, and good luck making analogs. Two papers published late last year add more data to the debate.

The first paper, published in J. Med. Chem. by William Pomerantz and collaborators at the University of Minnesota and Eli Lilly, describes the results of a fragment screen against the bromodomain BRD4(D1), a popular member of the BET family. The 467 fragment library was enriched for shapely fragments as assessed by plane of best fit (PBF), which is the “average distance of a non-hydrogen atom from a plane drawn through the compound such as to minimize the average.” For example, "flat" benzene has a PBF of 0 while the cofactor NADPH has a PBF of 1.53.

The library was screened using ligand-observed (CPMG) NMR, and 34 hits were confirmed using protein-observed fluorine (PrOF) NMR. All of these were competitive with the known ligand (+)-JQ1, consistent with binding at the acetylated lysine recognition site. The average PBF of the hits was 0.44, essentially the same as the library itself (0.46). This is higher than the average PBF (0.36) of all fragments crystallized with BRD4 in the protein data bank.

Structures of all the hits are provided, and some of them are indeed quite unusual. The researchers characterized a substituted thiazepane crystallographically and were able to optimize this to a 32 µM binder with good ligand efficiency. This fragment was also selective against a handful of other bromodomains.

The researchers had previously screened BRD4(D1) under identical conditions with a more traditional, “flatter” library with an average PBF of 0.26. Interestingly, in that case the hits were less shapely than the library as a whole, with an average PBF of 0.17. The confirmed hit rate was also higher: 20% vs 7%. That said, the fragments in the traditional library tended to be smaller (averaging 180 Da vs 241 Da), so the molecular complexity of this library was likely to be lower, which could account for the higher hit rate.

The second paper, published in Bioorg. Med. Chem. Lett. by Ulrich Grädler and collaborators at Merck KGaA, EMD Serono, Edelris, and Proteros, focuses on cyclophilin D (CypD), which has been implicated in cardiovascular disease and multiple sclerosis. Unlike BRD4, this is a tough target: an HTS screen of 650,000 compounds in a biochemical assay yielded just 178 hits, none of which confirmed. Undeterred, the researchers screened 2688 fragments by SPR at 2 mM, resulting in 58 confirmed hits, all quite weak (millimolar). Crystallography was attempted on most of them, yielding six structures, including such shapely specimens as compounds 3 and 7.

Compound 3 binds in the lipophilic S2 pocket of CypD, overlapping with the aniline moiety of previously reported compound 2. Fragment merging led to compound 14, with nearly 40-fold improved affinity over compound 2. A similar strategy merging compound 3 with fragment 8 led to low micromolar compound 27, two orders of magnitude more potent than the starting fragments. Perhaps most impressively, fragment linking compound 3 with compound 7, a shapely fragment which binds in the S1’ pocket, led to submicromolar compound 39, with affinity more than 10,000-fold higher than either fragment.

So in the end, fanciers of shapely fragments and detractors alike can feel vindicated by these papers. Hit rates might be lower for three dimensional fragments, but the resulting hits are likely to be less precedented. In the case of CypD, a shapely fragment led to three different series for a target that had resisted HTS. Of course, there is still some way to go: no cell, permeability, or stability data are provided for any of the molecules, and medicinal chemists may blanch at the seven stereocenters in compound 39. But these are interesting starting points, and it will be fun to see where they end up.

Review of 2019 reviews

The year ends, and with it the awkward teenage phase of the twenty-first century. As we have done since 2012, we're using this last post of the year to highlight conferences and reviews over the previous twelve months.

There were some good events, including CHI’s Fourteenth Annual Fragment-based Drug Discovery meeting in San Diego in April, their Discovery on Target meeting in Boston in September, and the third Fragment-based Drug Design Down Under 2019 in Melbourne in November, which also saw the launch of the Centre for Fragment-Based Design. Our updated schedule of 2020 events will publish next week.

Turning to FBLD reviews, Martin Empting (Helmholtz-Institute for Pharmaceutical Research Saarland) and collaborators published a general overview in Molecules. This is a nice up-to-date summary, covering library design, methods to find, confirm, and rank fragments, and optimization approaches. It’s also open access so you can read it anywhere.

Targets

Protein-protein interactions can be particularly challenging drug targets, and these are covered in a Eur. J. Med. Chem. review by Dimitrios Tzalis (Taros Chemicals), Christian Ottmann (Technische Universiteit Eindhoven) and colleagues. The focus is on clinical compounds, and several of these – including venetoclax, ASTX660, mivebresib, onalespib – are discussed in detail. The article is particularly useful in discussing late-stage optimization of pharmacokinetic and pharmacodynamic properties. It also provides a nice summary of physicochemical properties for fragment hits and derived candidates.

Target selectivity is always important, and this is the focus of a review in Exp. Opin. Drug Disc. by Rainer Riedl and collaborators at the Zurich University of Applied Sciences and the Università degli Studi dell’Insubria. Although the broader topic is de novo drug design, fragment-based methods are prominent, and include case studies we’ve discussed on nNOS, pantothenate synthetase, and MMP-13.

In terms of specific targets, Fubao Huang, Kai Wang, and Jianhua Shen at the Shanghai Institute of Materia Medica provide an extensive review of lipoprotein-associated phospholipase A2 (Lp-PLA₂) in Med. Res. Rev. This serine hydrolase has been studied for four decades but – as the researchers note – “divergence seems to be ubiquitous among Lp-PLA₂ studies.” At least this is not for lack of good chemical tools, fragment-derived (see here, here, and here) and otherwise.

Methods

Although NMR has fallen behind crystallography in our latest poll, that is certainly not reflected in terms of reviews. In particular, ¹⁹F NMR is covered in three papers. CongBao Kang (A*STAR) manages to pack a lot (including 261 references!) into a concise review in Curr. Med. Chem. Topics include protein-observed ¹⁹F NMR, in which one or more fluorine atoms are introduced into a protein genetically, enzymatically, or chemically, as well as ligand-observed methods, in which fluorine-containing small molecules are directly observed or used as probes that are displaced by non-fluorine-containing molecules.

Protein-observed ¹⁹F NMR (PrOF NMR) is covered in Acc. Chem. Res. by William Pomerantz and colleagues at the University of Minnesota. Although the first example was published 45 years ago, only in the past few years has the technique been used for studying protein-ligand interactions. The researchers note that introducing fluorines into aromatic residues is ideal because they are relatively rare, simplifying interpretation, and overrepresented at protein-protein interactions, maximizing utility. Several case studies are described, and even proteins as large as 180 kDa are amenable to the technique.

Ligand-based fluorine NMR screening is simpler and more common than techniques that focus on proteins, and this topic is thoroughly reviewed by Claudio Dalvit (Lavis) and Anna Vulpetti (Novartis) in J. Med. Chem. After a section on theory, the researchers discuss library design, including a long section on quality control (which involves assessing solubility, purity, and aggregation of the molecule in a SPAM filter). Direct and competition-based screening approaches are covered in detail; for the latter, a new method for determining binding constants is provided. The paper concludes with more than a dozen case studies. Clearly much has changed in the ten years since I wondered “why fluorine-labeled fragments are not used more widely.” This perspective is a definitive guide to the topic.

Moving to less common methods for characterizing fragments, György Ferenczy and György Keserű (Research Center for Natural Sciences, Budapest) cover thermodynamic profiling in Expert Opin. Drug Disc. After discussing several case studies, they conclude that “thermodynamic quantities are not suitable endpoints for medicinal chemistry optimizations” due to the complexity of contributing factors. This is consistent with another recent paper on the subject (see here), though the information provided is still interesting for understanding molecular interactions.

And although you might have thought the 2017 VAPID publication was the last word on the limitations of ligand efficiency (LE), Pete Kenny has published a splenetic jeremiad on the topic in J. Cheminform. (see also his blog post on the topic, which includes a sea serpent). This is largely a retread of a 2014 article on the same topic (reviewed by Teddy in his inimitable manner here). Pete also describes a more complicated alternative to LE involving residuals, though unfortunately he provides no evidence that it provides more useful information. Pete is of course correct to remind us that metrics have limitations, but assertions that LE “should not even be considered to be a metric” are overwrought.

Chemistry

Two articles discuss virtual chemical libraries. In J. Med. Chem., W. Patrick Walters (Relay Therapeutics) describes efforts to measure, enumerate, and explore chemical space. He notes that false positives could quickly overwhelm a virtual screen of a hundred million molecules, but as we saw earlier this year, progress is being made. Indeed, Torsten Hoffmann (Taros Chemicals) and Marcus Gastreich (BioSolveIT) focus on navigating the vastness of chemical space in Drug Disc. Today. They note that the Enamine REAL Space is up to 3.8 billion commercially accessible compounds, more than double the number of stars in the Milky Way. But this pales in comparison to the 10²⁰ potential compounds in Merck’s MASSIV space. Just storing the chemical structures of these in compressed format would require 200,000 terabytes – and searching them exhaustively is beyond current technology.

Ratmir Derda and Simon Ng (University of Alberta) discuss “genetically encoded fragment-based discovery” in Curr. Opin. Chem. Biol. This involves starting with a known fragment that is then coupled to a library of peptides and screened to find tighter binders. The researchers provide a number of case studies, though adding even a small peptide to a fragment will generally have deleterious effects on ligand efficiency. And – Rybelsus not withstanding – oral delivery of peptides is challenging.

Finally, Vasanthanathan Poongavanam, Xinyong Liu, and Peng Zhang, and collaborators at Shandong University, University of Bonn, University of Southern Denmark, and K.U. Leuven review “recent strategic advances in medicinal chemistry” in J. Med. Chem. Among a wide range of topics from drug repurposing to antibody-recruiting molecules is a nice, up-to-date section on target-guided synthesis. As I opined a couple years ago, I still doubt whether this will ever be generally practical, but from an intellectual standpoint I’m happy to see work continue on the approach.

And with that, Practical Fragments says goodbye to the teens and wishes you all a happy new year. Thanks for reading and commenting. May 2020 bring wisdom, and progress.

A new library of fluorinated Fsp3-rich fragments

Among fragment-finding methods, ligand-based NMR ranks near the top in terms of popularity. Of its many variations, fluorine (¹⁹F) NMR appears to be gaining in popularity. Fluorine NMR has several advantages, including high sensitivity and the fact that many fragments can be screened simultaneously because of the wide chemical shift range for fluorine. Although more commercial fluorine-enriched libraries are available now than when we first wrote about the approach a decade ago, the diversity of these libraries is still somewhat limited. This problem has been tackled by Mads Clausen at the Technical University of Denmark and an international team of collaborators in a new Angew. Chem. Int. Ed. paper.

The researchers wanted to create a fluorinated fragment library that would be not just diverse but also contain a high fraction of sp³-hybridized carbons (high Fsp³). Some of the early claims around “three dimensional” fragments have been questioned, and there seems to be little if any correlation between the shapeliness of fragments and that of derived leads, but if you’re going to make new fragments in academia it makes sense to explore interesting molecular architectures.

Starting from just six simple building blocks, each containing a trifluoromethyl group, the researchers generated nine different cores which were further derivatized at multiple positions to yield 115 diverse fragments. Consistent with diversity-oriented synthesis, no more than five synthetic steps were used for any molecule. All molecules were made as racemates in order to further increase the diversity of the library.

The resulting “3F Library” is mostly rule-of-three compliant, though given that the trifluoromethyl moiety alone adds 69 Da the fragments do tend to be larger, with an average molecular weight of 284 Da. They are, however, less lipophilic than two commercial fluorinated fragment libraries. And with an average Fsp³ = 0.7 and 3.3 chiral centers they are also quite shapely as assessed by principal moment of inertia.

Building a library is nice, but will it provide hits? To find out, the researchers screened the 102 fragments that passed quality control against four targets. They used a transverse (T₂) relaxation assay (specifically, CPMG) in which fragments bound to a protein tumble more slowly, causing a reduction in ¹⁹F signal intensity. Hit rates ranged from 3% to 11%, and about two thirds of these confirmed in STD or WaterLOGSY assays. As seen by the examples shown here, the fragments are quite diverse.

Whether these hits will lead to more potent molecules remains to be seen. Laudably the paper ends with the statement: “we hope that the 3F library will find use for other researchers and we encourage anyone interested in screening the fragments to contact us.” If you are looking for interesting new fragments that are tailored for follow-up chemistry, I encourage you to take the team up on their offer.