Focal molography for assessing protein-ligand interactions

The list of technologies used to find and validate fragments is long, with more than a dozen in our 2024 poll. But it’s always fun to learn about new approaches. At the Novalix conference earlier this year I learned of “focal molography,” and this is the topic of a recent paper in J. Med. Chem. by Nicholas Favalli, Andreas Frutiger, Sebastian Oehler, and colleagues at Philochem and lino Biotech.

 

The approach is described in detail in this Wikipedia article. Briefly, it is a biophysical technique based on changes in diffraction. A sensor chip contains a matrix of “molograms,” each of which is a lens constructed of micropatterned ridges and grooves. The ridges of each mologram are functionalized with unique single-stranded oligonucleotides. These capture complementary strands, each attached to a molecule to be screened. The grooves are coated with oligonucleotides without small molecules to act as a control in the subsequent readout. Proteins are then flowed over the chip. Protein binding to the small molecules of a specific mologram changes the topography of the ridge, and so the diffraction. This change can be measured in units of “coherent mass density” (pg/mm²). Because only specific binding to the ridges is detected (the grooves provide background controls for each mologram), the technique is suitable for even crude samples such as cell lysates.

 

An obvious application for focal molography is to confirm the binding of hits identified from DNA-encoded libraries (DEL), since the small molecules already have an oligonucleotide tag. This is the focus of the new paper.

 

The researchers started by assessing three known binders to the model protein carbonic anhydrase IX (CAIX). Surface plasmon resonance (SPR), the most frequently-used chip-based biophysical method, was used as a benchmark in two formats, one in which the small molecule was bound to the SPR chip, which is most comparable to focal molography, and one in which the protein was bound to the SPR chip.

 

SPR and focal molography agreed in rank order for the three compounds, but focal molography sometimes suggested tighter binding. For the highest-affinity compound, SPR gave a K_d of 28 nM for compound bound to the chip and 450-750 nM for protein bound to the chip, while focal molography gave a K_d of 0.82 nM. Agreement was better for the weaker binders, one of which was mid-nanomolar and the other low micromolar. The kinetic constants k_on and k_off also differed between focal molography and SPR by as much as two orders of magnitude.

 

Next, the researchers examined hits from a DEL screen against CAIX, some of which were selective against the related protein CAII. A total of two dozen molecules were tested by both focal molography and fluorescence polarization (FP) as an orthogonal technique. Again, the rank orders of affinities for the compounds to CAIX and CAII agreed while the absolute values varied, with focal molography usually suggesting ten-fold tighter binding. (Though the FP assay often bottomed out above the K_d values measured by focal molography.)

 

Finally, the researchers examined the binding of a known high-affinity binder to the oncology target fibroblast activation protein (FAP). In this case the measured affinities were close to the reported value.

 

This is an interesting approach, and according to the researchers “focal molography can support up to ~500 duplicate kinetic measurements per day on a single regenerable chip.” The observation that affinity measurements seem to be tighter than other methods does raise concerns. I wonder if the density of the molecules on the molograms leads to rebinding, as is sometimes seen when SPR chips are too heavily functionalized. Alternatively, since CAIX is a homodimer, perhaps avidity effects played a role. Also, the researchers suggest that the technique is best used for compounds with affinities better than 10 µM, which reduces utility for many fragment programs.

 

If you’ve used focal molography, how has it worked for you?

Expanding the Scope of chemical space at Novartis

Without a good library, it is difficult to find a good hit, so library design is one of the most import aspects of a screening campaign. The size of a library also impacts how it can be screened. A virtual or DNA-encoded library might be billions (or even trillions) of compounds, but for most physical screens, such huge numbers would be unfeasible. Generally, fragment screens sample more chemical space but require more resources, while screens of larger molecules can be higher throughput. In a new (open-access) J. Chem. Inf. Model. paper, Johanna Jansen, Charles Wartchow, and colleagues at Novartis describe a middle ground, the “Scope Concept.”

 

The researchers, many of whom have fragment and biophysics experience, were interested in molecules that might be larger than the rule-of-three guidelines for fragments, but still small enough to sample reasonable swaths of chemical space. To this end they developed the Scope library. To be included, compounds need to have molecular weights between 200-400, measured or calculated solubilities of at least 100 µM, at least two moieties capable of forming hydrogen bonds, and a “Scope ring system,” meaning two rings connected by a 0-3 atom linker. Additionally, undesirable substructures were removed, and in-house compounds had to pass quality control. Originally compounds were required to have log P < 5, but the solubility limit weeded these out anyway. Some warhead-containing molecules were included, though the fraction is not disclosed.

 

The Novartis compound collection was queried using these criteria to choose a 10,000-compound core Scope set as well as a 40,000-compound extension set designed for higher throughput screens. While these numbers are not large in the context of high-throughput screening libraries, they are larger than most fragment libraries according to our polls.

 

The Scope libraries proved to be popular at Novartis: 18 screens were performed in the first year across three sites. Half of these were biochemical screens. Of the rest, six used SPR, two used DSF, and one used native mass spectrometry (nMS). Most of the biochemical screens used the full 50,000 library, while the biophysical screens used the 10,000 core set and sometimes expanded to the full set. For four of five targets screened using a biochemical assay, primary hit rates were similar or slightly higher for the Scope library than a diversity library, though the Scope library was screened at a 50-100 µM concentration as opposed to 10-50 µM.

 

Three targets are discussed in some detail. The first, trypanosomal CLK1 kinase, had a freakishly high primary hit rate of 21% when screened at 100 µM, compared to 2.5% for a diversity set screened at 12.5 µM. Another kinase had an 11% hit rate, while a third had a more reasonable 1.2% hit rate when the ATP-binding site was blocked, suggesting binding to this site. The researchers now screen kinases against lower concentrations of the Scope compounds due to the high ligandability of kinases in general.

 

The chemical structures of half a dozen hits are shown, with IC₅₀ values ranging from 30 nM to 1.1 µM. Interestingly two of the molecules are covalent modifiers, and both are somewhat large for fragments, with 19 or 20 non-hydrogen atoms.

 

Another target screened was the molecular hub protein 14-3-3, which we wrote about most recently just a few months ago. A screen of the 10,000-compound Scope core set looking for stabilizers of 14-3-3σ and a peptide from the estrogen receptor yielded 86 hits, of which three were fully validated in orthogonal assays. One of these yielded a crystal structure and turned out to be a covalent modifier at a cysteine residue previously shown to be reactive. As with CLK1, the hit was on the larger side, with 22 non-hydrogen atoms. A separate publication by Colin Skepper and colleagues in ACS Med. Chem. Lett. describes this and three other covalent hits derived from diversity sets. Here too, the hits ranged from 20 to 24 non-hydrogen atoms.

 

The native mass spectrometry screen mentioned above was run against the main protease (MPro) of SARS-CoV-2. The 10,000 compound core set was screened in pools of four, with each compound at 25 µM. Of 61 primary hits, five validated with IC₅₀ values < 25 µM. In contrast to many inhibitors of this protein, these were mostly non-covalent.

 

The Scope Concept is a nice addition to the field of library design. As we noted last year, covalent fragments may need to be larger than non-covalent fragments, and it is interesting that two of the three case studies identified covalent modifiers. I hope Novartis publishes a follow-up in a few years with lessons from additional screens.

Site-specific HDX-MS for increased resolution

Most methods to characterize protein-ligand binding interactions have drawbacks. Crystallography, obviously, requires your protein to crystallize, while NMR and cryo-EM both have size limitations and are resource-intensive. Hydrogen-deuterium exchange mass spectrometry (HDX-MS), which we wrote about earlier this year, is theoretically faster and can apply to more proteins, but the technique provides limited resolution. Now a new open-access paper in J. Am. Chem. Soc. by Derek Wilson and collaborators at York University, the Structural Genomics Consortium, and SCIEX have improved the resolution down to single amino acids.

 

As we wrote in March, HDX-MS relies on the exchange between deuterium and protons on proteins; slower exchange is associated with more stable secondary structures. The exchange is detected by digesting the protein with proteases and determining the mass of the resulting peptide fragments using MS; incorporation of deuterons increases the mass of the peptides. If, for example, a peptide has three deuterons incorporated, the mass would increase by 3. However, in conventional HDX-MS, one can’t tell exactly where the deuterons have exchanged.

 

Last year the researchers described a method in J. Am. Soc. Mass Spectrom. to do just this using some clever mass spectrometry experiments. I won’t go into details as the paper is open access, but suffice it to say that it involves electron-activated dissociation (EAD) to fragment the peptides while preventing the scrambling of the protons and deuterons that normally limits resolution.

 

In the new paper, the approach was applied to the oncology target WDR5, which we previously discussed here. The researchers applied site-specific HDX-MS to three small molecule and two peptide ligands. All five of these ligands had previously been characterized by conventional HDX-MS as well as surface plasmon resonance (SPR), and four had also been studied crystallographically.

 

Reassuringly, the results from site-specific HDX-MS were mostly consistent with conventional HDX-MS, but there were some surprises. For example, the site-specific approach revealed protection from exchange for one amino acid (which makes a hydrogen bond to the ligand) and enhanced exchange for the adjacent amino acid on the same peptide. In conventional HDX-MS, the “peptide contains offsetting uptake increases and decreases, resulting in a ‘net-zero’ signal.”

 

The researchers also found that, for another residue, the change in HDX-MS signal correlates with the affinity of the ligand, as assessed by SPR. The mechanism is unclear since the concentrations of ligands were far higher than their affinities, but the results are intriguing.

 

The new paper describes just a single, well-behaved target, but if site-specific HDX-MS applies more broadly, it would offer a significant advance in obtaining structural information. The researchers note that the data analysis is currently “manual and prohibitively cumbersome,” a problem that should be solvable with automation. I look forward to seeing it applied prospectively to more targets, particularly if it works for weak binders such as fragments.

Differential scanning fluorimetry (DSF) for covalent ligands

Differential scanning fluorimetry (DSF), also known as a thermal shift assay, is one of the most common techniques for fragment screening according to the most recent methods poll on Practical Fragments. This popularity is in part due to the simplicity of the assay: just mix your protein with a dye such as SYPRO Orange, which binds to the hydrophobic core of unfolded proteins, heat the solution in a PCR thermocycler, and measure the change in fluorescence. Ligands that bind specifically to proteins often stabilize them, increasing the melting temperature. As we noted in 2017, some companies even use DSF to assess the ligandability of new targets.

 

Most of the focus on DSF has involved non-covalent ligands. But the approach also works for covalent ligands, according to a new open-access paper in the British Journal of Pharmacology by Nir London and colleagues at the Weizmann Institute of Science.

 

The researchers acknowledge that they are not the first to explore DSF on covalent ligands; last year we discussed a screen of 47 covalent fragments against 47 kinases, and just last month we highlighted a DSF screen that identified an unexpectedly covalent fragment hit.

 

The new paper starts by performing DSF on five drug targets (BTK, the G12C mutant of KRAS, SARS-CoV-2 MPro, Pin1, and Keap1), each with well-characterized covalent ligands (for example, ibrutinib, acalabrutinib, and evobrutinib for BTK, sotorasib and adagrasib for KRAS^G12C, etc.) For four of the proteins they also tested non-covalent or covalent reversible ligands. Almost all of the ligands increased thermal stability of the bound protein, and covalent ligands tended to have a greater effect.

 

In addition to testing specific ligands, the researchers also performed DSF experiments on the five proteins with three reactive, non-specific covalent ligands: iodoacetamide, ethyl 2-(bromomethyl)acrylate, and a chloroacetamide called RA13. Intact protein mass spectrometry confirmed that these molecules gave essentially complete modification of the five proteins, in some cases at multiple sites.

 

In contrast to the specific ligands, the reactive alkylators tended either to have marginal effects on the melting temperatures of the proteins or to actually destabilize the proteins, sometimes dramatically. That said, there were cases of stabilization. The researchers suggest that “reactive, non-specific, irreversible binders may act as destabilizers, since they form an irreversible covalent bond regardless of molecular recognition, which may result in deformation of the protein if the rest of the binder cannot be accommodated near the modified amino acid.”

 

To assess how well DSF works for covalent fragments more generally, the researchers acquired 2612 acrylamides from Enamine and screened them (each at 8 µM in pools of 5) against Keap1 for 24 hours at 4 ºC. Mass spectrometry showed that just over 100 gave at least 50% modification, which a back of the envelope calculation suggests a covalent efficiency roughly 1 M^-1s^-1. Next, 84 compounds with differing degrees of modification were tested by DSF, and, in contrast to the kinase paper we discussed last year, there was a correlation between extent of modification and either stabilization or destabilization of the protein. But consistent with the specific ligands discussed above, the more reactive fragments (as assessed by glutathione reactivity) were the only ones that caused destabilization.

 

The authors conclude by proposing “DSF as a fast and complementary follow-up approach for electrophilic fragment screening, to prioritize productive and selective covalent binders over promiscuous reactive fragments.” This seems reasonable – what do you think?

Best practices for applying HDX-MS to FBLD

Among the many biophysical techniques presented at the recent Novalix meeting, hydrogen/deuterium exchange mass spectrometry (HDX-MS) was mentioned only a few times. Practical Fragments last covered it nearly four years ago in the context of a paper that described theoretical challenges and improvements to the method for assessing fragment binding modes. A new open-access Comm. Chem. paper from Tiago Bandeiras, Alessio Bortoluzzi, and collaborators at iBET-Instituto de Biologia Experimental e Tecnológica and Merck KGaA implements some of these suggestions.

 

The researchers find only two examples where HDX-MS had been applied to fragments, one of which we covered here. The new paper focuses mostly on Cyclophilin D (CypD), a mitochondrial protein implicated in several diseases. A screen we wrote about in 2020 described several fragment hits, some of which were crystallographically found to bind in three overlapping sites designated the proline pocket, the aniline pocket, and the pyrazolo pocket.  The researchers chose a binder from each pocket to study as well as two more fragments whose binding sites were not known. All five fragments are extremely weak hits, with at best 7 mM (yes, millimolar) affinity as assessed by SPR, making this a particularly challenging test case.

 

As a reminder, HDX-MS examines the exchange of deuterium from D₂O to protein backbone amides. Nearby ligands can slow this exchange, and mapping the locations and magnitude of these changes reveals where the ligand binds. Optimization experiments were initially run on a compound with a K_D of 44 mM for the aniline pocket. Three protein concentrations were tested. Since the highest (10 µM) yielded the highest number of detected peptides, it was used for subsequent experiments.

 

As suggested in the 2022 paper, compound was added both to the initial protein solution as well as to the deuterium exchange buffer. The fragment was tested at 2.5, 5, and 10 mM, and changes in deuterium uptake were found in all cases, which is remarkable given that the theoretical occupancies range from 5 to 18%. An experiment using substoichiometric concentrations of a high affinity ligand confirmed that 18% protein occupancy is sufficient to generate a reliable signal.

 

Still, given the low occupancy, the researchers used statistical methods to ensure that changes in signals were significant. Mapping those that were onto the structure of the protein confirmed that the fragment bound to the aniline pocket.

 

A second fragment was tested by HDX-MS, and the results confirmed that it binds in the pyrazolo pocket, as previously shown by crystallography. However, for a third fragment that had been shown to bind in the proline pocket, the results suggested instead that it binds in the aniline pocket. The proline pocket exhibited very low levels of deuterium exchange, but when the researchers increased the pH from 7.4 to 9 they did find evidence that the fragment binds here as well.

 

Next, the researchers turned to the two fragments with unknown binding sites. HDX-MS revealed that these bind to the aniline binding site, though with subtly different protection patterns suggesting that they bind in slightly different regions of the pocket.

 

Finally, the researchers used their optimized HDX-MS conditions on a previously identified fragment that binds the kinase FAK with low millimolar affinity. This showed that it binds in the so-called hinge region, in agreement with crystallography. This fragment was also used as a negative control for CypD, showing that it does not bind.

 

This paper is a nice resource for those hoping to apply HDX-MS to fragments. The fact that the binding sites of such weak binders can be determined is quite remarkable. That said, the resolution is not as good as crystallography or protein-detected NMR; for FAK in particular, the ligand reduces deuterium update across a large fraction of the protein surface. And the fact that a proline-pocket binder was initially mapped to the aniline pocket also gives one pause. Perhaps the binding mode in solution really is different from that found crystallographically. It would be interesting to see whether NMR can resolve the conundrum.

Twelfth Novalix Biophysics in Drug Discovery Conference

Last week the Twelfth Novalix Biophysics in Drug Discovery Conference was held for the first time in La Jolla, California. It’s been several years since I wrote about one of these, and I was happy to see that they’ve maintained their reputation for excellent science and convivial conversation. There’s no way to cover the two-dozen talks, but here are a few highlights.

 

One of the things I most enjoy about these meetings is learning about new and emerging methods, and these were well represented. Chris Brosey (AbbVie) discussed time-resolved high-throughput small-angle X-ray scattering (TR-HT-SAXS). As I discussed a couple years ago, the approach can be used to measure the kinetics of protein dimerization in response to fragment-sized ligands.

 

SAXS-based approaches typically require access to a synchrotron, but Takashi Sato (Rigaku) described a related approach, electron density tomography (EDT), using an in-house instrument. Using machine learning, EDT can provide more detailed structural information than standard SAXS, and Takashi provided examples for samples ranging in size from viruses to single-chain variable fragments (scFvs) smaller than 30 kD.

 

Another approach to examine protein complexes is microfluidic diffusional sizing (MDS), described by James Wilkinson of Fluidic Sciences. By assessing the amount of diffusion in disposable chip-based chambers, MDS can determine how the hydrodynamic radius changes in response to ligands. Each chip holds 24 samples, and data can be collected in less than an hour. The minimum observable size change is 5-10% so measuring small molecules directly is unlikely. Still, the technique is useful for observing induced proximity events such as those caused by molecular glues, and it is sufficiently robust that it can be run in pure serum.

 

Among solution-based methods, none have achieved such recent prominence as cryo-EM. Weiru Wang, my colleague at Frontier Medicines, described how this technique was used iteratively to design and characterize bivalent degrader molecules that covalently exploit the E3 ligase DCAF2. (We recently published this work in Structure.)

 

Cryo-EM has revolutionized the types of biological molecules that can be structurally characterized. According to Denis Zeyer (Novalix), the technique accounted for 40% of PDB entries last year. However, despite the “resolution revolution,” most structures are not as detailed as those from X-ray crystallography; Denis noted that only 20% of the new structures were solved to a resolution better than 3 Å, which may have negative implications for machine-learning methods trained on these lower resolution structures.

 

If cryo-EM is the new kid in town, NMR is the grizzled veteran. But proving that it is possible to find new applications for old methods, Matthew Eddy (University of Florida) described a clever ¹⁹F-labeling approach for GPCRs in nanodiscs to quantify the distribution of various states in response to anionic lipids and ligands. This has allowed him to distinguish between antagonists and inverse agonists, which can be difficult using cell-based assays.

 

Turning from solution-based to surface-based methods, SPR has moved into the number two slot for fragment-finding, as we noted in our recent poll. Just as there are new tricks for NMR, the same applies to SPR. Matthew Peterfreund (Bruker Biosensors) described switchSENSE, a fluorescence proximity assay built on an SPR chip that is useful for measuring the binding and kinetics of bifunctional ligands such as PROTACs to two or more proteins. He also introduced the Triceratops SPR#64 instrument, which as its name implies supports 64 sensor spots.

 

Kris Borzilleri (Pfizer) discussed SPR-microscopy (SPRm), which combines an optical microscope with an SPR instrument. This can be used to measure the affinities of ligands binding to receptors in cells grown on SPR chips, and Kris described applications to membrane proteins such as GPCRs and solute carriers. The technique is still quite slow though, at only 10-15 compounds in duplicate per week.

 

Another surface-based approach to screening cells was described by Volker Gatterdam of Lino Biotech. Focal molography relies on changes in diffraction from nanoengineered diffraction gratings, called molograms. Targets, which can include living cells, are immobilized to the molograms, and analyte is flowed over. The instrument contains 64 spots, and assays can be run in complex samples such as tissue lysates.

 

Covalent drug discovery also made an appearance, with talks by Landon Whitby (Lundbeck) and Ben Cravatt (Scripps). Landon provided an overview of chemoproteomics techniques to screen ligands in cells, such as those we wrote about in 2016. Ben continued the theme, including several success stories, and also discussed challenges for finding cryptic ligandable pockets. Despite impressive progress with machine learning, Ben noted that these methods often find only common solutions, while empirical chemoproteomics methods can find rare types of pockets.

 

Of course, as we’ve repeatedly emphasized, biophysics methods are best used in combination, as noted by Daniel Harki (University of Minnesota) and Ann Boriack-Sjodin (Takeda). Daniel presented a screen of 1056 fragments against the cancer target APOBEC3 using NMR and SPR. This yielded just a single validated hit, which interestingly turned out to be the same fragment found against KRAS in a paper we discussed in 2022. And Ann described how biophysics led to multiple clinical compounds against a variety of targets at Epizyme and Accent Therapeutics.

 

I’ll stop here, but please feel free to add your thoughts. And while the date for the next Novalix conference has not yet been scheduled, the location has, with a return to beautiful Strasbourg. Vive la biophysique!

Review of 2025 reviews

Turning and turning in the widening gyre

The falcon cannot hear the falconer…

 

In our small, annual counterweight to Yeats’ “mere anarchy," Practical Fragments looks back on 2025.

 

This year marked the thousandth post on Practical Fragments, a milestone neither Teddy nor I imagined when the blog launched back in 2008. In terms of conferences, I wrote about CHI’s Drug Discovery Chemistry in San Diego here and Discovery on Target in Boston here.

 

For the past decade I’ve participated in annual J. Med. Chem. perspectives covering fragment-to-lead success stories, two of which published this year. The first, spearhead by Rhian Holvey at Astex, covers the year 2023, while Astex’s David Twigg took the lead on covering the year 2024. In addition to the tabular summaries for which these reviews are best known, both also include tables of “near misses,” none of which made the main tables because the starting points were (sometimes just slightly) too large. Four out of six of these heavyweights are covalent fragments, suggesting that the rule of three may need to be relaxed for these. The most recent paper also includes a table showcasing the eight approved FBLD-derived drugs.

 

Two more general publications are also of interest. In a brief (open-access) editorial in J. Med. Chem. Weijun Xu and Congbao Kang at A*STAR summarize fragment-finding methods and approved drugs and discuss future applications of FBLD in PROTACs and targeting RNA. And in Curr. Res. Pharm. Drug Discov., Geoffrey Wells, Exequiel Porta, and colleagues at University College London present a “graphical review” which covers library design, screening strategies, hit validation, fragment optimization, and a few case studies of approved drugs, along with current challenges.

 

In Drug Des. Devel. Ther., Bangjiang Fang and colleagues at Shanghai University of Traditional Chinese Medicine present an open-access bibliometrics analysis of 1301 fragment-based drug design papers published between 2015 and the end of 2024, which includes top ten lists of institutions, authors, and papers as well as keyword trends and analyses. Annual growth has averaged 1.4%, and the field is both global and collaborative, with 35% of publications involving more than one country.

 

Targets

Two reviews focus on oncology. The first, in Bioorg. Chem. by Milind Sindkhedkar and collaborators at Manipal College of Pharmaceutical Sciences and Lupin Ltd., briefly covers the history and practice of FBDD before providing short summaries of seven of the eight approved drugs to come from it. The second, published open-access in Chem. Rev. by Vanderbilt’s Steve Fesik, is a concise and highly readable introduction and account of the author’s groundbreaking work on BCL-2 family proteins, KRAS, and WDR5.

 

A much longer open-access review in Chem. Rev. by Paramjit Arora and colleagues at New York University covers protein-protein interactions (PPIs). Much of the focus is on larger molecules such as cyclic peptides, peptide mimetics, and other macrocycles, but there are summaries of fragment-based approaches against KRAS and 14-3-3 proteins.

 

The topic of 14-3-3 proteins is treated more fully in an open-access Acc. Chem. Res. paper by Michelle Arkin and colleagues at UCSF. While the focus of most efforts against PPIs is to find inhibitors, for 14-3-3 the goal is to find stabilizers, or molecular glues. The Arkin lab and others have been succeeding using various approaches, particularly disulfide tethering. We wrote about these efforts most recently in 2023, and the new review provides a nice update.

 

Fragment finding methods and libraries

Sahra St. John-Campbell and Gurdip Bhalay, both at The Institute of Cancer Research, published a massive open-access perspective on “target engagement assays in early drug discovery” in J. Med. Chem., covering a host of biochemical, biophysical, and cell-based assays. A table lists more than 50 different techniques, almost half of which are applicable to FBLD. Each row shows what characteristic(s) are measured as well as critical requirements for  protein, sample, and equipment. The paper is also beautifully illustrated with dozens of figures: one shows which techniques are most useful for different types of targets, and each method gets its own diagram.

 

A more focused open-access review is provided by Stefanie Freitag-Pohl and colleagues at Durham University in Biophys. Rev. After surveying various biophysical techniques, the researchers focus on spectral shift analysis, and in particular the Dianthus instrument from NanoTemper Instruments. This plate-based, high-throughput microfluidics-free instrument can detect changes in fluorescence caused by environment or temperature. Examples demonstrate affinity measurements across several orders of magnitude, up to double-digit millimolar, and a nice scheme shows use of the Dianthus in a fragment-screening workflow.

 

Moving to specific techniques, Jia Gao, Ke Ruan, and colleagues at University of Science and Technology of China Hefei provide an open-access survey of “the rise of NMR-integrated fragment-based drug discovery in China” in Mag. Res. Lett. After a brief overview of NMR approaches, they cover case studies from China, most of which are focused on fragment screening rather than optimization.

 

A less common biophysical method is native mass spectrometry (nMS), the subject of an open-access opinion in RSC Med. Chem. by Louise Sternicki and Sally-Ann Poulsen at Griffith University. This is a good survey of the approach; we highlighted a more fragment-focused review by the same authors last year.

 

The most common fragment-finding approach, X-ray crystallography, is covered in two open-access reviews. The first, in Acta Cryst. F by Sarah Bowman and collaborators at University of Buffalo and Brookhaven National Laboratory, focuses on critical early stages, from protein characterization to sample preparation and various crystallization approaches. The second, in Curr. Opin. Strut. Biol. by Martin Noble and colleagues at Newcastle University, starts by briefly reviewing crystallographic fragment screening before turning to fragment libraries. The paper includes a nice table summarizing publicly available libraries at major synchrotrons, with the text describing these in more detail.

 

The provider of one of these libraries, EU-OPENSCREEN, is the subject of an open-access review in SLAS Discov. by Robert Harmel and collaborators at EU-OPENSCREEN ERIC and Fraunhover ITMP. As we wrote last year, EU-OPENSCREEN is a broad consortium whose mission is to advance early drug discovery by providing access to technology and expertise. The new paper summarizes the four compound collections, including the European Fragment Screening Library (EFSL), and surveys progress to date. It also lays out ambitious plans, including expanding to >30 sites in nine countries.

 

Computational approaches and cryptic sites

Despite the hype about artificial intelligence in the broader world, AI in fragment-based drug discovery has been less common. In Curr. Opin. Struct. Biol., Woong-Hee Shin and colleagues at Korea University College of Medicine summarize applications to fragment growing, merging, and linking. The open-access paper includes a handy table of 13 programs, and includes GitHub links where available.

 

Cryptic binding sites, defined by Ehmke Pohl and collaborators at Durham University and Cambridge Crystallographic Data Centre “as binding pockets that exist in the ligand-bound state of a protein but not in its apo form,” are the focus of an open-access review in Bioinform. Adv. The researchers cover earlier computational approaches for finding these, especially molecular dynamics (MD) and machine learning (ML). They note that a key challenge for ML is the limited quantity and quality of experimental data: undiscovered cryptic sites would be misclassified as non-binding sites.

 

Yowen Dong, Ge-Fei Hao, and colleagues at Guizhou University review “computational methods for identifying cryptic pockets” in Drug Discov. Today. As with the previous review, these are divided between molecular dynamics and AI-based techniques, which are discussed individually and then compared. The researchers apply six approaches to the model bacterial protein TEM-1 β-lactamase and find that, for this highly studied single protein, the AI-based methods are much faster (seconds instead of days) and just as accurate, though MD-based methods provide more insight into formation mechanisms of cryptic pockets.

 

Covalent ligands

Allosteric sites are an important sub-class of cryptic pockets, and in J. Med. Chem. Jianing Li and colleagues at Purdue University discuss covalent allosteric inhibitors. After briefly discussing advantages of covalent molecules, they review examples targeting protein phosphatases, kinases, and GTPases, such as KRAS.

 

Of course, covalent molecules are not limited to allosteric sites. An open-access review in Bioorg. Med. Chem. Lett. by Walaa Bedewy, John Mulawka, and Marc Adler at Toronto Metropolitan University summarizes published covalent protein ligands, grouping them by target site:  active sites, residues adjacent to an active site, protein-protein interfaces, cofactor binding sites, and allosteric sites.

 

Chem. Rev. published two massive reviews on covalent ligands, each with more than 300 references. The first, by Tomonori Tamura, Masaharu Kawano, and Itaru Hamachi at Kyoto University, covers a wide range of topics, from covalent drugs, to peptide- and protein-based covalent inhibitors, to chemical biology labeling and target engagement strategies, to covalent bifunctional molecules such as PROTACs and radionucleotide-based molecules, and even covalent modification of DNA and RNA. The paper includes 68 figures, many reproduced from the original publications.

 

The second (open-access) Chem. Rev. paper, by Ku-Lung Hsu and colleagues at University of Texas at Austin, focuses on covalent ligands targeting protein residues other than cysteine, particularly lysine and tyrosine; we highlighted some of Hsu’s work recently. The paper also discusses naturally occurring molecules that bind to lysine, such as pyridoxal phosphate and aldose sugars.

 

Methods for finding covalent ligands are the focus on an open-access review in JACS Au by Mengke You, Hong Liu, and Chunpu Li at Shanghai Institute of Materia Medica. Specifically, they review disulfide tethering, activity-based protein profiling (ABPP), covalent DEL, phage and mRNA display, and sulfur(IV) fluoride exchange (SuFEx), with examples for each.

 

The last paper on this topic, in J. Med. Chem., offers a brief but important overview of all covalent FDA-approved small molecule drugs through 2023. Samuel Dalton and collaborators at Isomorphic Laboratories and Merck counted 128 covalent drugs, about 7% of all small molecule drugs. More than half are antibiotics, and more than 85% target serine or cysteine. Only 10% are reversible, but this number is rapidly increasing, with 11 of the 13 reversible covalent drugs approved since 2010. Importantly, the names, chemical structures, indication, target and target residue, warhead, and key references for all the drugs are provided in the supporting information.

 

Miscellaneous

Deconstruction of ligands to smaller fragments that are then “reconstructed” into new leads is a venerable approach in FBLD and the subject of an open-access perspective in J. Med. Chem. by J. Henry Blackwell, Iacovos Michaelidies, and Floriane Gibault at AstraZeneca. Multiple examples dating as far back as the late 1990s are provided, along with appropriate caveats about potential changes in fragment binding modes and protein conformations.

 

Finally, an open-access perspective in J. Med. Chem. by Dean Brown (Jnana Therapeutics) examines the 104 oral drugs approved from 2020 through 2024, including structures, dosing, pharmacokinetics, and safety. Roughly a third of these drugs are dosed more than once per day, and almost a quarter have a black box warning, while 42% have at least one contraindication. Dean warns that “overly prescriptive [development candidate] criteria may inadvertently stifle the development of innovative drugs,” and that it is difficult but important “to be the champion for a compound that others perceive as ‘un-drug like.’” The growing success of covalent drugs illustrates that some organizations are taking this to heart.

 

And that’s it for 2025. Thanks for reading and special thanks for commenting. And in 2026, may the best of us be filled with passionate intensity.

Protein-detected NMR without isotopic labeling

Protein-detected NMR was the first practical approach for finding fragments, and as we noted last week some still consider it the gold standard. As commonly practiced, it requires isotopically labeled protein: at a minimum ¹⁵N and sometimes ¹³C and even deuterium. Making large amounts of labeled protein can be both expensive and difficult. A new ACS Med. Chem. Lett. paper by Andrew Petros and collaborators at AbbVie describes a new approach that avoids this requirement. The method, called 1D-ECHOS, combines two previously described techniques.

 

The first technique addresses the fact that fragment screens typically use much higher ligand concentrations than protein concentrations, and thus the proton signals coming from the ligand can overwhelm those coming from the protein. “1D-diffusion filtered NMR” essentially removes signals coming from small molecules to focus on the protein.

 

When a ligand binds to a protein, the chemical shifts of nearby residues on the protein change, and these peak shifts are most easily observed in two-dimensional (2D) NMR spectra, where each dimension typically corresponds to the signal from a different nucleus, such as ¹H or ¹⁵N. Without isotopic labeling, only protons can be observed, and only in one dimension, so the resulting spectra look like mountain ranges, with overlapping peaks. To facilitate comparison between the two samples (protein with or without ligand), the researchers use a second technique, called Easy Comparison of Higher Order Structure (ECHOS). This allows differences to be expressed as a single “R-score”, where larger numbers indicate more deviation between the two spectra.

 

So, how well does it work? The researchers started by examining a set of 13 hits from a DNA-encoded library against an unnamed 36 kDa protein. Four of these had previously been confirmed to bind using 2D-NMR, and all of these had positive R-scores, while the non-binders had R-scores close to zero. The approach was also faster than a standard HSQC with labeled protein, requiring just 10 minutes rather than 35 minutes.

 

As the researchers note, DEL hits are typically larger and more potent than fragment hits, so they next turned to 11 confirmed MCL-1 binders from a fragment screen we wrote about here. These were tested at 62.5 µM, and the R-scores roughly correlated with their previously measured affinities, which ranged from 20 µM to 500 µM.

 

To try to get more quantitative information, the researchers performed dose-response experiments and plotted the R-score as a function of ligand concentration. This allowed them to extract dissociation constants, which were in good agreement with the known values. For ligands containing tert-butyl groups the 1D-diffusion filter was not fully capable of masking the signal, but this peak could be manually removed from the analysis. The researchers also applied the approach to two additional targets, BRD4 BDII and TNFα, and found good agreement with known ligand affinities. Of course, unlike 2D NMR, 1D-ECHOS does not provide information on where the fragments bind.

 

1D-ECHOS appears to be a practical approach for validating and characterizing fragment binding, but I’m no NMR spectroscopist, so I’ll be interested to hear what experts think.

The thousandth Practical Fragments post!

As the title states, this is the 1000^th post at Practical Fragments. This blog was conceived in 2008 over drinks at the Third Annual CHI Fragment-based Drug Discovery Conference. (Don’t miss the twentieth in April!) Teddy Zartler said he was planning on starting a blog and asked if I wanted to join. In July of 2008 Teddy wrote the first post, and every month since then has seen at least a couple new ones. I thought it would be fun to look back briefly on the past 16+ years.

 

Methods

The very first Practical Fragments post asked what screening methods people use, and this eventually led to five polls on the topic, the latest of which published just a few months ago. In our first formal poll, in 2011, the average respondent used 2.4 techniques. Today that number has grown to 5 due to the increased recognition that different methods have different strengths and weaknesses.

 

By far the biggest winner among methods has been X-ray crystallography; it jumped from sixth place in 2011 to first place in both 2019 and 2024. Crystal structures have long been prized in drug discovery, but the dramatic increases in throughput and automation over the last decade mean more structures are more available to more users.

 

Computational methods too have improved spectacularly. In 2009 we highlighted an in silico screen of around 67,000 fragments which yielded ten micromolar inhibitors. Today, screening multibillion compound libraries is becoming routine, and artificial intelligence is likely to enable even more opportunities.

 

Pitfalls

One of the reasons that it took so long for FBLD to develop was the myriad artifacts that can haunt screens run at high concentrations. For example, compound aggregation was not widely recognized until the first decade of this century, and even today too many papers are published without checking for this pathological phenomenon.

 

Similarly, pan-assay interference compounds, or PAINS, were not defined until 2010. Scientists at large companies have long known to steer clear of certain chemotypes. Now academics and folks in startups are more aware of problematic substructures, even if Dr. Saysno objects.

 

Long-time readers may recall a series of posts on “PAINS-shaming,” where we highlighted (lowlighted?) papers that lacked appropriate selectivity or mechanistic studies. Occasionally this led to productive discussions, as in this example where an author and journal editor contributed to the comments. But with the increasing use of metrics measuring social media engagement to rank articles I’ve decided that blogging about them may inadvertently reward shoddy science. If you’re looking for most of the things that can go wrong in a screen, check out this open-access review by Ben Davis and me.

 

Covalent craze

One prominent mechanism of PAINS is indiscriminate covalent modification of proteins. For many years drug hunters actively avoided covalent modifiers for fear of off-target modifications and their potentially toxic effects. Indeed, the first several mentions of covalent compounds at Practical Fragments were in the “things to avoid” category. We discussed reversible covalent modifiers in 2012 and 2013, but it wasn’t until 2014 that we wrote about intentionally irreversible fragments.

 

How times have changed! The success and safety of targeted covalent kinase inhibitors has fueled enthusiasm for covalent drugs in general, creating opportunities for fragment-based approaches. Indeed, as we discussed here, both reversible and irreversible fragment-based screens were used in the discovery of the first approved drug targeting the previously intractable target KRAS, and these learnings have been applied at multiple companies to produce an impressive armamentarium against what Darryl McConnell has called “the beating heart of cancer.”

 

To find KRAS inhibitors, researchers screened pure proteins against libraries of covalent fragments. One of the most exciting recent developments in chemoproteomics has been screening covalent fragment libraries in intact cells or cell lysates to find hits against thousands of proteins in their native environment. We first wrote about this approach in 2016, and last year we highlighted the first drug to enter the clinic from covalent screening in cells.

 

And all this is just the beginning: each of our past four annual “review of reviews” posts has featured between three and six papers focused on covalent fragment-based drug discovery.

 

Clinical compounds

My first blog post in 2008 was a brief mention of a C&EN story on FBLD, in which I noted that “an FBLD drug that reaches the market by 2011 would be a ‘psychological’ victory for the whole FBLD community.” Although I claim no prescience, I was happy to see vemurafenib approved in August of 2011.

 

Indeed, I would argue that FBLD-derived drugs are the most meaningful output and validation of the field. Our first systematic tabulation in 2009 counted just 17 that had entered clinical trials, and today there are more than 60. Like investigational drugs in general, the majority of these have stumbled, but at least eight have been approved by the US FDA, and more are working their way through clinical trials. While eight might seem like a modest number, the number of patients they’ve helped is orders of magnitude greater.

 

Closing thoughts

There are far more themes in a thousand posts than I could summarize in a single one: metrics, induced proximity, and newer methods such as cryo-EM all come to mind. But as this post has already surpassed 1000 words, I’ll wrap it up.

 

One minor frustration has been the sparsity of comments; it sometimes feels as if I’m blogging into the void. That said, I’m pleased that some posts may have led to new research, such as this. And blogging can be its own reward: I sometimes find myself using the “Search This Blog” function on the top right-side of the page when I’m trying to remember a paper from years ago.

 

Since Teddy left the FBLD field several years ago I’ve been writing most of the content, with occasional guest posts (such as this from Glyn Williams). At the current rate it might take a couple decades for Practical Fragments to reach 2000 posts, if we even get there. But for now, I’d like to thank each of you for reading. I hope you enjoy it and that is has, at least occasionally, made your scientific pursuits more practical.

Review of 2024 reviews

Long winter is here in the global north, with its dim days and gaping nights. As is tradition, Practical Fragments looks back on the year almost done. 2024 was the best year for conferences since the arrival of COVID. I wrote about CHI’s Drug Discovery Chemistry in San Diego, FBDD-DU in Brisbane, FBLD 2024, and CHI’s Discovery on Target, both in Boston. 

Another tradition is the annual J. Med. Chem. fragment-to-lead success story review; the latest covers the year 2022 and was written by Andrew Woodhead (Astex) and collaborators, including yours truly.

 

For a timely and accessible overview of “how to find a fragment,” look no further than a review of that title in ChemMedChem by Marcio Vinicius Bertacine Dias and collaborators at University of São Paulo and University of Warwick. This covers crystallography, cryo-EM, NMR, SPR, thermal shift, virtual screening, functional screening, ITC, mass spectrometry (including HDX-MS), MST, and BLI, and concludes with a nice comparison table. Some twenty other reviews were also published throughout the year, and these are discussed thematically.

 

Structure-based methods

Three reviews cover NMR. In J. Med. Chem., Janet Caceres-Cortes and colleagues at Bristol-Myers Squibb provide “perspectives on nuclear magnetic resonance spectroscopy in drug discovery.” Ligand- and protein-detected screening are covered thoroughly, with examples such as the discoveries of BI-2852 and venetoclax. Applications beyond hit finding are also discussed, such as the characterization of atropisomers in sotorasib, the identification and characterization of impurities and metabolites, in-cell NMR, and much more.

 

“Perspectives on applications of ¹⁹F-NMR in fragment-based drug discovery” is the title of an open-access review in Molecules by Qingxin Li and CongBao Kang at Guangdong Academy of Sciences and A*STAR, respectively. As we discussed in 2020, fluorine NMR is becoming increasingly common in FBLD, and this paper covers the various methods, including using ¹⁹F-NMR to measure ligand affinity. The authors also include a table summarizing 17 fragment screens that used fluorine NMR.

 

The rise of powerful permanent magnets has enabled low-maintenance benchtop NMR instruments that can be yours for as little as $50,000, compared to upwards of $1 million for a 600 MHz superconducting machine. Although sensitivity is at least 150-fold lower, hyperpolarization techniques such as photo-CIDNP, which we wrote about here, can close the gap. The latest developments are described (open access) in Chemistry–Methods by Felix Torres and collaborators at NexMR and the ETHZ.

 

X-ray crystallography has retained the top position among fragment-finding methods according to our most recent poll. In an open-access Applied Research paper, Daren Fearon, Frank von Delft, and collaborators describe high-throughput crystallographic fragment screening at the Diamond Light Source. As of August 2024 they have collected more than 240,000 academic data sets on hundreds of targets, and the paper distills some of the key lessons, some of which were applied to the COVID Moonshot, which we last wrote about here. The paper also describes future developments and needs, such as how and where to house such massive quantities of data.

 

Another center for high-throughput crystallographic screening is the Helmhotz-Zentrum Berlin (HZB) F2X-Facility at the BESSY II synchrotron, and in an open-access Applied Research paper Manfred Weiss and collaborators provide an overview of workflows and capabilities. One unique offering is the F2X-GO kit, in which F2X fragment libraries (which we wrote about here) as well other supplies are shipped to users to do soaking experiments in their own laboratories prior to shipment to the synchrotron.

 

“Structure-based virtual screening of vast chemical space” is the topic of an open-access review in Curr. Opin. Struct. Biol. by Jens Carlsson (Uppsala University) and Andreas Luttens (MIT). The Enamine REAL collection currently contains 40 billion compounds, and the researchers predict that “make-on-demand chemical libraries will likely reach more than one trillion compounds in the next few years,” which presents both opportunities and challenges, particularly given the existence of the “virtual cheaters” we recently discussed. Machine learning and fragment-based methods such as V-SYNTHES could help.

 

Continuing the virtual theme, Li Wang and collaborators at Nantong University discuss “molecular fragmentation as a crucial step in the AI-based drug development pathway” in an open-access Commun. Chem. paper. This summarizes 15 different computational methods for dissecting larger molecules into fragments, and also includes a list of 11 library vendors.

 

Other methods

Among experimental methods, few can match the throughput of fluorescence techniques, the subject of an open-access Heliyon review by Neelagandan Kamariah and colleagues at inSTEM & NCBS in Bangalore. It has short sections on “fluorescence polarization (FP) and anisotropy (FA), Förster resonance energy transfer (FRET), time-resolved Förster resonance energy transfer (TR-FRET), fluorescence lifetime (FLT), protein-induced fluorescence enhancement (PIFE), fluorescence thermal shift assay (FTSA) and microscale thermophoresis.” It also describes applications to GPCRs, protein-protein interactions, and other biological systems.

 

Native mass spectrometry (nMS), which we wrote about most recently in 2022, is the subject of an RSC Med. Chem. review by Louise Sternicki and Sally-Ann Poulsen at Griffith University. Sally-Ann is a leading expert in nMS, and the paper describes the technique and how it compares to other fragment-finding methods. It also includes a nice table summarizing 17 studies published between 2013-2023 that used nMS for FBLD; a 2013 review of nMS covered earlier examples.

 

Covalent Fragments

Mass spectrometry plays a prominent role in finding covalent fragments, as discussed in an open-access SLAS Discovery review by Simon Lucas and colleagues at AstraZeneca. “Covalent hits and where to find them” also describes other biophysical, biochemical, cellular approaches, and even DEL screening. It also discusses covalent libraries (which we wrote about earlier this month) and successful examples such as the discovery of sotorasib. In my opinion the researchers succeed in their “hope that this review will help serve as a useful roadmap to those seeking to drug the undruggable.”

 

A concise open-access review in Curr. Opin. Struct. Biol. by Katrin Rittinger and collaborators at The Francis Crick Institute and GSK focuses on using covalent fragments to assess target tractability, specifically ligandability and functionality. Target-based, proteome-wide and function-first approaches are summarized, and the researchers also discuss the importance of negative control compounds such as inactive enantiomers.

 

Continuing the theme of “assayability,” Micah Niphakis (Lundbeck) and Ben Cravatt (Scripps) review “ligand discovery by activity-based protein profiling” (ABPP) in a Cell Chem. Biol. paper. Because ABPP is usually conducted in cells or cell lysates, full-length proteins are assayed in their native environment, facilitating the discovery of allosteric ligands as in the case of WRN, which we wrote about earlier this year. The paper summarizes multiple examples of finding covalent ligands for challenging targets, and also highlights future challenges such as increasing throughput and targeting residues beyond cysteine.

 

Reversible covalent inhibitors are the topic of an open-access review by Dustin Duncan and colleagues at Brock University in ACS Chem. Biol. The researchers argue that reversible covalent inhibitors may cause less accumulation of the off-target adducts that could form with irreversible inhibitors. The paper includes a figure showing reversible covalent warheads, details on how to characterize them, a nice summary of general considerations, and success stories for JAK3, BTK, and proteases.

 

Targets

Covalent ligands have been particularly important for cancer targets, as reviewed by Xiaoyu Zhang (Northwestern University) and Ben Cravatt (Scripps) in an open-access Annual Review of Cancer Biology paper. The focus is on use of chemical proteomics “to expand the druggability of cancer proteomes.” The paper presents examples of finding and characterizing covalent ligands for a variety of oncology targets including KRAS^G12C.

 

E3 ligases are briefly mentioned, and this target class is the focus of an Expert Opin. Drug Discov. review by Jongmin Park and colleagues at Kangwon National University. As we’ve discussed recently, the 600 or so human E3 ligases are potentially valuable for targeted protein degradation applications such as PROTACs. The review focuses on “fragment-based approaches to discover ligands for tumor-specific E3 ligases.” In addition to summarizing successes against targets such as BCL6 and XIAP, it includes a list of 113 tumor-specific E3 ligases and another list of 52 E3 ligases that are overexpressed in certain tumors.

 

The “impact of fragment-based drug design on PROTAC degrader discovery” is also the subject of a review in Trends in Analytical Chemistry by Xiaoguang Lei and colleagues at Shenzen Bay Laboratory. Here, the focus is more on using FBLD to discover ligands for target proteins rather than for E3s. For example, the researchers describe how the fragment-derived drug navitoclax was used as a starting point for developing DT2216, a clinical-stage BCL-x_L degrader.

 

As Vicki Nienaber noted more than a decade ago, fragment-based drug discovery is ideally suited for targeting the central nervous system, particularly when combined with a ruthless focus on molecular properties. This is the topic of an open-access review in Front. Chem. by Michael Kassiou and collaborators at University of Sydney, CSIRO, and Vast Bioscience. After a brief summary of FBLD the researchers present case studies published since 2015, the last year this topic was reviewed. We’ve covered quite a few on Practical Fragments, including apoE4, Notum, and PDE10A.

 

Other

We mentioned allostery above, and in an open-access FEBS Open Bio. article Andrea Bellelli and collaborators at Sapienza University of Rome and elsewhere ask “is allostery a fuzzy concept?” Digging into half-century old publications from Jacques Monod, the researchers conclude that the concept was “born with an original sin: two definitions.” Indeed, the first mathematical model did not even apply to monomeric proteins. Most readers of this blog will probably be satisfied with the notion that an allosteric ligand is one that binds outside of an active site, but it is worth remembering that “allostery is an umbrella that covers more than a single reaction mechanism and cannot be defined by a single mathematical expression.”

 

Structure comes up frequently on Practical Fragments, but James Fraser (UCSF) and Mark Murcko (Disruptive Biomedical) remind us in Cell that “structure is beauty, but not always truth.” We’ve written multiple posts about getting misled by crystal structures, and in this brief commentary the authors provide “four harsh truths: a structure is a model, not experimental reality; representing wiggling and jiggling is hard; in vitro can be deceiving; drugs mingle with many different receptors.” They conclude that “truth is a molecule that transforms the practice of medicine.”

 

Stumbling towards truth is a little easier with the help of a good chemical probe, and in Nucleic Acids Res. Paul Workman (Institute of Cancer Research) and collaborators provide an updated description of The Chemical Probes Portal. This free community resource now contains 803 probes against 570 targets, including 28 covalent ligands and 51 degraders. Moreover, 332 of the probes have structurally related negative controls. Importantly, the Portal also includes 258 “Unsuitable” compounds that are insufficiently potent or selective to serve as chemical probes. Checking this list can save you valuable time when reading papers about unfamiliar targets.

 

Finally, a brief open-access interview with Nobel Laureate Katalin Karikó in Issues in Science and Technology is an inspiring reminder that “you learn more from failure,” and that the pleasure of doing science can be its own reward.

 

Thanks for reading. Good luck in 2025, and remember that the sun is always out there, even when you can neither feel nor see it.

Poll results: fragment finding methods and structural information needed for fragment-to-lead efforts

Our most recent poll asked about fragment finding methods. The poll ran from September 21 through November 8 and received 135 responses from 20 countries. Two thirds of these were from the US, about 12% were from the UK, 4% from Germany, 3% from the Netherlands, and 2% from Australia.

 

The first question asked how much structural information you need to begin optimizing a fragment. In contrast to 2017, when we first asked this question, crystallography has significantly increased at the expense of the other choices. 

 

 

I confess to being surprised, as I expected that by now people would be more comfortable beginning optimization in the absence of structural information, an approach that has been quite successful as discussed in a 2019 open-access Cell Chemical Biology review by Ben Davis, Wolfgang Jahnke, and me. Perhaps the increasing speed and accessibility of new methods has so lowered the bar to getting crystal structures that people have the luxury of waiting. Of course, with an online poll there is always the risk that many respondents from the same organization may skew the results.

 

The second question asked which methods you use to find and validate fragments. This is the fifth time we’ve run this poll, starting in 2011. As with our first question, X-ray crystallography came out on top, with nearly 80% of respondents choosing it. This was followed by SPR, at 67%, and thermal shift and ligand-detected NMR, each around 55%. 

 

 

Functional screening was used by nearly half of respondents, with computational methods, protein-detected NMR, and literature starting points used by around a third. Mass spectrometry and ITC were each used by slightly more than a quarter of respondents.

 

For the first time we asked about cryo-EM, and nearly 20% of respondents reported using this technique.

 

MST and affinity-based methods each came in at 13%, with just 4% of respondents using BLI, and 5 individual respondents using other methods. I’d be curious to know what these are.

 

The average respondent reported using just over 5 different techniques, which is down slightly from 6 in 2019 but up from 4 in 2016. Using multiple orthogonal methods is clearly well established as best practice, even if the precise number varies.

 

How do these results compare with your own practices?