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!

New tools for covalent fragment-based lead discovery

Covalent fragments provide an opportunity to both drug difficult targets and to more completely shut down targets. Success has spurred interest, and the literature is exploding. It has been just over a month since our last post on the topic, and already three new papers are worth highlighting.

 

The first, in Eur. J. Med. Chem. by György Keserű and collaborators at the Hungarian Research Centre for Natural Sciences and University of Szeged, describes a library of 24 covalent fragments. All of these contain the same relatively simple core but vary in their covalent warheads or how the warhead is attached.

 

The idea is to explore warhead reactivity in the context of a “vanilla” fragment that could provide modest but nonspecific hydrophobic interactions with proteins. The 14-atom 3,5-bis(trifluoromethyl)phenyl core was chosen because it is commonly used in medicinal chemistry and lacks polar atoms likely to make specific interactions to proteins. Also, the electron withdrawing trifluoromethyl groups make the warheads more reactive. The UV absorbance and lipophilicity also make derivatives synthetically easy to work with, and the fluorine atoms are useful for ¹⁹F NMR.

 

The warheads themselves span a vast range of reactivity as assessed both computationally and experimentally (by reactivity with glutathione). Some, such as maleimides and isothiocyanates, are so highly reactive that they are often used for nonspecific protein labeling, while others, such as styrene and acetylene, are quite unreactive. In the middle are moieties like acrylamides, chloroacetamides, and epoxides.

 

The researchers screened the library (at 100 µM) against four unrelated kinases: BTK, ERK2, RSK2, and MAP2K6. Unsurprisingly, four of the hottest fragments inhibited all the kinases, while the seven weakest warheads were inactive. Things got interesting in the middle though, with different inhibition profiles seen for different kinases.

 

Next, the researchers tested their fragment sets against two new kinases, JAK3 and MELK. Both kinases yielded several hits. Replacing the vanilla fragment with small hinge-binding elements for the relevant warheads rapidly yielded nanomolar inhibitors. Covalent inhibitors had already been reported for JAK3 but not for MELK. The researchers suggest using their library as a rapid tool for assessing cysteine accessibility. If you are interested in trying this at home, the authors have offered to send the library upon request.

 

The second paper, in ChemBioChem by György Keserű, Stanislav Gobec, and a large multinational group of collaborators, describes a slightly expanded covalent library consisting of 28 compounds representing 20 different warhead chemotypes, all with the same 3,5-bis(trifluoromethyl)phenyl core. Usefully, glutathione reactivity kinetics are provided for all the fragments. The fragments were screened against six different (non-kinase) targets, providing hits against all of them. ¹⁹F NMR as well as mass spectrometry was used to confirm binding.

 

It is always nice to see new types of covalent warhead chemistries, but medicinal chemistry tends to be somewhat conservative: if something works clinically and isn’t (too) toxic, we’ll stick with it. Thus the continuing interesting in acrylamides, which are found in five of the six approved covalent kinase inhibitors. Enter the third paper, in J. Med. Chem., by Adam Birkholz and colleagues at Amgen, which systematically explores the glutathione reactivity of substituted N-phenyl acrylamides.

 

The researchers first examine 11 α-substituted N-phenyl acrylamides. For the most part electron-withdrawing substituents increase the reactivity of the warhead, though fluorine has the opposite effect, attributed to its mesomeric electron-donating ability.

 

Next, the researchers turn to 21 β-substituted N-phenyl acrylamides. Again, electron withdrawing substituents increase the reactivity of the acrylamides. For aminomethyl substituents, the reactivity is lower than the parent unsubstituted acrylamide for amines with pK_a < 6, while the more basic amines show increased reactivity. All experiments were conducted at pH 7.4, and computational modeling suggests that the protonated amine inductively withdraws electron density from the acrylamide, thereby increasing its reactivity.

 

While the general trends reported in the paper are expected, the actual numbers provide a valuable resource. One of the challenges of covalent drugs is ensuring the warhead is reactive enough to bind to the target but not so reactive that it binds to other targets or is cleared too rapidly. By knowing how much a given substituent is likely to increase – or decrease – reactivity, chemists can more precisely tune their molecules.

 

Our medicinal chemistry toolkit is expanding, and covalent molecules are playing a growing role.

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?

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.

Fragments vs sepiapterin reductase, via 19F NMR

It has been two years since we’ve had a post devoted to fluorine NMR. Though I don't share Teddy’s “fetish” for ¹⁹F-based screening, I do think the technique can be quite powerful, as demonstrated in a recent J. Med. Chem. paper by Jo Alen, Markus Schade, and their colleagues at Grünenthal GmbH.

The researchers were interested in sepiapterin reductase, which is abbreviated as SPR but which I’ll spell out to avoid confusion with surface plasmon resonance. This enzyme performs the last step in the production of tetrahydrobiopterin, an essential cofactor for multiple enzymes, including some that synthesize neurotransmitters and produce nitric oxide. Sepiapterin reductase has been proposed as a target for non-opioid-based pain medications.

The primary assay involved displacement of a fluorine-containing inhibitor that binds in the substrate site of the enzyme; thus, the researchers could use ¹⁹F NMR without requiring fluorinated fragments. A total of 4750 fragments were screened at 250 µM, initially in pools of 12. The 26 hits were then tested in an enzymatic assay, and 21 showed activity better than 75 µM. The best, compound 3, was sub-micromolar.

Crystal structures were obtained for six compounds, including compound 3, and all bound in the substrate pocket as predicted from the original displacement assay. The phenolate of compound 3 makes hydrogen bonds to two critical catalytic residues. Not surprisingly, capping this moiety with a methyl group led to an inactive compound. The researchers made dozens of variants, but aside from compound 26, most of these were disappointingly less active. Compound 26 does show good solubility and permeability, though no cell data are provided, and the phenol will likely be glucuronidated in vivo.

This is a nice story that illustrates a not-infrequent frustration: after identifying the initial nanomolar hit from a small library, the researchers likely thought improving potency still further would be easy. Instead, it took more than 60 analogs just to gain another order of magnitude. That said, 57 nM is nothing to sneeze at. And this situation is certainly preferable to the more common alternative of starting with a weak fragment that remains weak no matter what you do to it!

Chiral fragments – and poll!

Chirality underpins all life. Nineteen of the twenty amino acids contain at least one stereocenter, as do all nucelosides, sugars, and most metabolites. The very first fragment I ever found was chiral, but that is not typical, at least judged by those that show up in publications. Only 5 of the 27 fragment to lead success stories published in 2015 started with a fragment containing a chiral center. This probably reflects what people choose to screen and pursue. Chiral centers can lead to challenging chemistry, and chiral centers also add to molecular complexity.

All of which brings us to the topic of our new poll: do you include chiral fragments in your primary screening collection? If so, do you include both enantiomers? Please vote in the poll to the right.

If you do include chiral fragments, do you screen racemic mixtures? Crystallography can sometimes reveal which enantiomer is active if the quality of the structure is good enough, but woe betide anyone screening racemic mixtures by ITC! In a new paper in Magn. Res. Chem., Claudio Dalvit (University of Neuchatel) and Stefan Knapp (Goethe University Frankfurt) show that fluorine NMR can also be used to screen racemic mixtures.

As Teddy wrote more than five years ago, ¹⁹F NMR is “just like ¹H NMR”. Most applications of ¹⁹F rely on detecting the line broadening that occurs when a fluorine-containing fragment binds to a protein. However, the chemical shift of the fluorine atom(s) can also change, particularly if the ligand forms hydrogen bonds to the protein. This “chemical shift perturbation” can be large enough to be detectable.

In the absence of protein, ¹⁹F NMR shows the same signal for different enantiomers, so a racemic ligand containing a single trifluoromethyl group gives a single sharp peak. However, upon addition of a protein that binds one enantiomer, the signal splits into two; one remains sharp and retains essentially the same chemical shift, while the other becomes broader and moves. The researchers show this both theoretically and experimentally with a racemic fragment that binds to the bromodomain BRD4. Adding a high-affinity ligand that binds to the same site displaces the fragment, causing the two signals to again converge.

Unfortunately there is no X-ray structure of the ligand bound to the protein, and the two pure enantiomers were not tested individually. And of course, unlike crystallography, ¹⁹F NMR does not reveal which enantiomer in a racemic mixture binds. Still, enantioselective binding can itself be indicative of specific binding, as opposed to various artifacts, and the researchers recommend that “racemates should always be included in the generation of the fluorinated fragment libraries.” What do you think?

Fragments distinguish allosteric from active site binders

As discussed last year, secondary binding sites on proteins appear to be quite common. Some of these sites have no functional relevance, but others are allosteric sites, which can modulate the activity of proteins. Allosteric ligands can be useful for several reasons. First, unlike molecules that bind at the active (that is, catalytic) site of an enzyme, which usually inhibit activity, allosteric site binders can increase activity. Second, allosteric sites are usually less conserved than active sites, allowing greater selectivity. Finally, combining an allosteric inhibitor with an active site inhibitor can lead to synergy as well as lower the incidence of resistance mutations for cancer and anti-infectives. In a recent ACS Med. Chem. Lett. paper, Lukasz Skora and Wolfgang Jahnke at Novartis describe a simple NMR approach to differentiate these two classes of ligands.

The researchers used ¹⁹F NMR to screen 540 fragments containing a CF₃ group, each at 25 µM, in pools of 30 against the kinase ABL1 (at 4 µM); the BCR-ABL1 mutant form of this protein is a key driver for chronic myelogenous leukemia. Several approved drugs target the active site of ABL1, and Novartis researchers have recently launched clinical studies of a compound called ABL001, which binds to an allosteric pocket.

Fragments that bind to ABL1 showed a decreased ¹⁹F NMR signal due to line broadening. Adding ABL001 displaced fragments that bind to the allosteric site, thereby increasing their NMR signals, while adding the active-site binding drug imatinib displaced fragments that bind to the catalytic site. Follow-up experiments with individual fragments identified a selective catalytic-site binder (CAT-1) and a selective allosteric site binder (ALLO-1). Both fragments are commercially available and quite weak (K_d = 43 µM for ALLO-1 and IC₅₀ = 380 µM for CAT-1), which in this case is a feature because they can easily be displaced.

Mixing these two fluorine-containing probes with ABL1, adding test compounds, and performing ¹⁹F NMR thus provides a simple means to determine whether a ligand binds to the allosteric site, the active site, or both sites. The researchers confirmed that the approved catalytic-site binding drugs nilotinib, dasatinib, and ponatinib displace CAT-1 but not ALLO-1, while allosteric-site binders such as ABL001 displaced ALLO-1 but not CAT-1.

Interestingly, a crystal structure of imatinib with the highly related protein ABL2 shows the compound binding to both the catalytic and allosteric sites, yet although imatinib clearly displaced CAT-1 it could not displace ALLO-1. This is a useful reminder that crystal structures say nothing about affinity.

The drug crizotinib, which binds to the active site of multiple kinases, has been reported by other researchers to bind to the allosteric pocket of BCR-ABL1, but this was not borne out in the competition assays. Similarly, the drug fingolimod has also been reported as an allosteric inhibitor of ABL1. This molecule did indeed displace ALLO-1, but only at concentrations so high as to be biologically irrelevant.

This is a nice paper, and a good reminder that fragments can make useful biophysical probes in and of themselves, even without the need for optimization.

Molecules special issue: Developments in Fragment-Based Lead Discovery

Last December the first-ever Pacifichem symposium on FBLD was held in Honolulu. Two of the organizers, Martin Scanlon and Ray Norton, invited participants to submit manuscripts to a special issue of Molecules, which has now published.

The collection starts with a very brief Foreword by me describing the Symposium itself. The first actual paper, from Qingwen Zhang and collaborators at the Shanghai Institute of Pharmaceutical Industry, WuXi AppTec, and China Pharmaceutical University, focuses on kinase inhibitors. The researchers examine fragment-sized substructures of 15 approved drugs that inhibit kinases and use these to design a high-nanomolar inhibitor of the V600E mutant form of BRAF, which modeling suggests should bind to the protein in the “DFG-out” conformation.

Next comes a fragment-finding paper from Thomas Leeper and collaborators at the University of Akron and the University of North Carolina, Chapel Hill. The researchers were interested in finding inhibitors of the glutaredoxin protein (GRX) from the pathogen Brucella melitensis, which causes brucellosis. An STD NMR screen of 463 fragments (each at 0.5 mM in pools of 5-7) resulted in 84 hits, though 75 also hit human GRX. Subsequent experiments including chemical shift perturbation and modeling identified a mM binder with modest selectivity over the human enzyme. Next, the researchers introduced several covalent warheads (including a rather exotic ruthenium analog), one of which led to improved affinity, though the stoichiometry was not determined.

The remaining papers are all reviews, starting with one on native mass spectrometry (MS) by Liliana Pedro and Ronald Quinn at Griffith University. This provides a good historical, theoretical, and practical overview of the technique generally, as well as various applications for fragment-screening. It also covers most of the published examples and discusses both the strengths (such as speed and low protein consumption) as well as the weaknesses (false positives and false negatives) of native MS.

NMR is up next, with a paper by Pacifichem organizer Ke Ruan and colleagues at the University of Science and Technology of China, Hefei. This provides a concise but detailed description of library design, ligand- and protein-detected fragment screening, structural model generation, and hit to lead optimization.

Protein-directed dynamic combinatorial chemistry (DCC) is tackled by Renjie Huang and Ivanhoe Leung, both at the University of Auckland. In addition to summarizing the theory and various literature examples, the authors do an excellent job covering the pros and cons of different types of chemistries and analytical techniques.

Next comes a review by Begoña Heras and collaborators at La Trobe University and Monash University on the subject of bacterial Dsb proteins, which are essential for disulfide bond formation in virulence factors. The review covers the biology as well as several approaches to finding inhibitors, some of which we’ve previously covered (here and here). There is much more to do: as the researchers conclude, “the development of Dsb inhibitors is still in its infancy.”

Finally, Ray Norton and colleagues at Monash University discuss applications of ¹⁹F NMR for fragment-based lead discovery. In addition to covering fluorine-containing fragments, the researchers also discuss using fluorine-containing probe molecules and – even more unusual – fluorine-labeled proteins, in this case using 5-fluorotryptophan. The paper includes previously unpublished results on how these latter two approaches can be used to understand protein-ligand interactions.

One nice feature of this journal is that it is open-access, so if you are lucky enough to be back in Hawaii this December you can pull up the papers on your smartphone while lying on the beach.

NMR poll results

The results of our latest poll are in – thanks to all who participated! Of the 119 people who responded to the first question, 87% said they use NMR for finding or validating fragments. Even if we assume that responses were biased towards NMR aficionados, big magnets are clearly popular.

The second question asked about specific NMR techniques. If everyone who said they used NMR in the first question also answered the second, this means the average user applies more than 3 different techniques; I’ll let Teddy weigh in to see whether this matches his experience.

One surprise for me was that, although many techniques are widely used, none are nearly universal; even the most popular methods seem to be used by just over half of respondents.

Among ligand-detected methods (blue in the figure), STD ranks at the top, with line-broadening, WaterLOGSY, and fluorine-based techniques all tied for second place.

Protein-detected methods (red in the figure) also appear quite healthy, with nearly as many respondents using ¹⁵N-HSQC/HMQC as STD.

Finally, 11 of you said you use "other" techniques. We didn't include TINS, even though it seems quite useful, because it is only available through the services of ZoBio. But what else is out there?

NMR poll!

Among fragment-finding techniques, nuclear magnetic resonance (NMR) ranks near the top. Protein-detected methods, like HSQC/HMQC-based SAR by NMR, helped usher in fragment-based drug discovery as a practical endeavor. More recently, ligand-detected methods such as line broadening (or CPMG), STD, and WaterLOGSY appear to have gained the edge. There are also more boutique methods, such as ILOE and spin labeling. And of course, some people proudly embrace their fluorine fetishism.

So what’s your favorite flavor? Now's your chance to weigh in on our latest poll (on the right). The first question asks whether you use NMR, and the second asks which methods you use. PLEASE ANSWER BOTH QUESTIONS - the free version of Polldaddy doesn't track individuals, so we need the answer to the first question to know the total number of respondents.

And, as always, your comments are welcome.