Seventeenth Annual Fragment-Based Drug Discovery Meeting

Last week the CHI Drug Discovery Chemistry (DDC) meeting returned triumphantly to San Diego. This was the best conference I’ve attended in years, which reflects not just the quality of the meeting itself but the fact that three-dimensional events are vastly superior to their 2D counterparts.

 

About 75% of the more than 700 attendees were physically present, though having a virtual option turned out to be wise; at least three of the speakers had COVID but were still able to present remotely. Although the FBDD track lasted just a day and a half, fragments were well-represented across the four days and ten tracks. I won’t attempt to summarize the more than 40 talks I attended but will just cover some broad themes.

 

Computational Methods

Seva Katritch (USC) described the V-SYNTHES approach we highlighted in January. This modular method enables computational fragment growing, in effect facilitating a search of 11 billion molecules from just 600,000 scaffolds. The method as described makes heavy use of Enamine’s make-on-demand molecules, and I think everyone in the audience was excited to hear that the company has started making and shipping compounds from Kyiv again.

 

In the comments to the blog post on V-SYNTHESES someone mentioned BioSolveIT, and Paul Beroza (Genentech) described using their software for a similar approach. One of the targets they investigated, ROCK1, was also investigated with V-SYNTHES, and both techniques yielded unique nanomolar inhibitors.

 

Jan Wollenhaupt (Helmholtz Zentrum Berlin) also mentioned BioSolveIT in the context of fragment growing by catalog. Fragments identified crystallographically from their F2X libraries (see here) were grown to low micromolar endothiapepsin binders. Interestingly an unbiased docking screen did not find these molecules, illustrating the utility of stepwise computational approaches.

 

DOTS is another approach to computational growing and docking enabled by rapid synthesis we’ve previously written about, and Xavier Morelli (CNRS) gave an update, including the fact that they plan to launch a webserver soon.

 

Physical Methods

Tim Kaminski (InSingulo) described an intriguing method for screening liposome-bound proteins such as GPCRs. Dyes incorporated into the liposome are visualized using single molecule microscopy, and the liposomes can be observed in real time binding to immobilized targets in 384-well plates. Tim mentioned that the instrument should be available for purchase next year.

 

A new take on an old method was described by Félix Torres (ETH), who discussed using photochemically induced dynamic nuclear polarization (photo-CIDNP) to increase the sensitivity of NMR, thereby reducing experimental times by a factor of 100. The method requires specialized fragments and a customized NMR, but they can currently screen 1500 fragments per day, and the approach could be particularly valuable for screening hard-to-express proteins.

 

Sticking with the theme of photochemistry, Rod Hubbard (Vernalis by way of Hitgen) discussed a DNA-encoded library of more than 130,000 fragment-linker combinations each containing a photoaffinity tag. Screening this against PAK4 yielded 425 hits, and of the 30 chosen for validation more than 90% confirmed by NMR or crystallography. As we noted in 2020, combining DEL and FBLD provides new opportunities for exploring chemical space.

 

It’s been a few years since we discussed weak affinity chromatography, and Kirill Popov (WAC) provided an update. They’ve applied the approach to more than 50 targets and have obtained hit rates up to 20%. An example against SMARCA4 yielded hits that were subsequently found to bind at two sites, one of which had not previously been described.

 

Covalent fragments continue to increase in popularity. FragNet alum Lena Muenzker (BI) described an intact-protein mass spectrometry screen of the E3 ligase SIAH1 against 1260 acrylamides, resulting in 214 hits. Crystallography has been successful, and they are planning to use these to generate covalent PROTACs.

 

We’ve previously written about screening covalent fragments in cells, and Benjamin Horning (Vividion) and Madeline Kavanagh (Scripps) described a nice chemoproteomics case study in which an alkynamide-containing fragment was identified that binds to cysteine 817 in the kinase JAK1. Optimization led to a low nanomolar binder that inhibits JAK1 signaling.

 

Cysteine is not the only amino acid amenable to covalent modification. Plenary keynote speaker Laura Kiessling (MIT) described squarate derivatives as tunable “Goldilocks” warheads for lysine, with the right balance of reactivity and stability.

 

Success Stories

Cases studies were abundant, including some new disclosures that I’ll hold off describing until they publish. Of course, drugs are the ultimate success stories, and several of these were presented. Svitlana Kulyk recounted the discovery of MRTX1719, Mirati’s MTA-cooperative PRMT5 inhibitor, including some interesting tangents not discussed in the publication.

 

Steve Fesik (Vanderbilt) gave two presentations on near-clinical compounds, one targeting MCL1 and the other WDR5. In both cases weak fragments were advanced to picomolar binders within one to two years, but it has taken much longer to optimize other properties of the molecules.

 

Indeed, this turned out to be something of a theme. Valerio Berdini (Astex) discussed the discovery of erdafitinib, the third approved FBLD-derived drug. The program started in 2006, and it took just nine months to go from the fragment hit to late lead optimization. But the compound didn’t enter the clinic until 2012, and it took until 2019 to be approved.

 

Similarly, Wolfgang Jahnke (Novartis) described the story of the sixth approved fragment-based drug. The fragment screen against ABL was conducted in 2006, but the project went through two near-death experiences. Asciminib finally entered the clinic in 2014, and it was approved last year.

 

But timelines are not destined to be long. We’ve previously written about vemurafenib, the first FBLD-derived drug, which took just six years from project initiation to approval. Ryan Wurz (Amgen) gave a retrospective on sotorasib, the fifth approved FBLD-derived drug. Amgen started the program in August 2012, sotorasib was first synthesized in early 2017, first dosed in humans in 2018, and approved in May of last year. Fast doesn’t mean easy: it took 110 co-crystal structures, and I counted more than 100 names on the acknowledgement slide. But success against KRAS is a welcome reminder that sometimes we really can accomplish the impossible when we work together.

 

This is a good point on which to close. Assuming SARS-CoV-2 doesn’t intervene, DDC is scheduled to return to San Diego April 10-13 next year. I hope to see you there!

Fragments win in a virtual screen against Notum

Wnt proteins are implicated in a variety of diseases, from Alzheimer’s to colorectal cancer. The enzyme Notum shuts down signaling by removing a palmitoyl group from Wnt. Last year Practical Fragments highlighted several series of Notum inhibitors identified from biochemical and crystallographic fragment screens. The researchers behind those efforts, including Paul Fish and Fredrik Svensson (University College London), have now published a successful virtual screen against the enzyme in J. Med. Chem.

 

Starting with 1.5 million compounds available from ChemDiv, the researchers chose 534,804 based on a variety of computational filters including molecular weight (200-500 Da), number of hydrogen bond donors (<=2) and ClogD (-4 to 5). A virtual screen of these (using Glide) produced 1330 high-scoring hits, of which 1088 were chosen for purchase. Of these, 952 were available, a much higher percentage than the ZINC15-reliant paper we wrote about earlier this year.

 

All 952 compounds were tested in a biochemical assay, and the 44 that gave >50% inhibition at 1 µM were then tested in dose-response format. This yielded 31 compounds with IC₅₀ values < 500 nM. These could be subdivided into four structurally related clusters and eight singletons. Further triaging removed compounds likely to cause assay interference as well as those similar to known Notum inhibitors. This left two clusters and two singletons.

 

Compound 1f was the most potent member of a series of 9 related (and possibly covalent) inhibitors. Although these strongly inhibited the enzyme in the biochemical assay, they were essentially inactive in a cell-based assay. They were also highly insoluble and showed low cell permeability, and were thus dropped.

 

Compound 2a was one of two related molecules that were also quite potent when initially tested. Unfortunately, when the molecules were resynthesized they turned out to be significantly weaker and were also not very soluble, so this series was also halted.

 

The singleton compound 3 turned out to be a covalent inhibitor; the catalytic serine formed an ester with the molecule. The mechanism is more fully described in this open-access J. Med. Chem. paper.

 

That leaves the second singleton. Compound 4d was not just active in the biochemical assay, it also showed sub-micromolar cell activity. SAR, guided by crystallography, ultimately led to low nanomolar inhibitors. The pK_a of compound 4d was measured to be 7.9, which is less acidic than many previously reported Notum inhibitors and thus more likely to be cell permeable. This turned out to be the case experimentally, and the compound was also stable in mouse liver microsomes. Pharmacokinetics in mice were promising for several compounds, but unfortunately brain penetration – which the researchers were hoping for – was negligible. (This could be an advantage for peripheral diseases.)

 

This is a nice example of lead discovery in academia. Like last week’s post, it also illustrates that fragments themselves can be quite potent. Indeed, although the researchers were looking for molecules up to 500 Da in their virtual screen, all of the best hits were fragment-sized. Another illustration that small is beautiful.

Nucleophilic fragments vs SARM1: in situ inhibitor assembly

Recently Practical Fragments wrote about nucleophilic fragments that could react with proteins or cofactors. Previously we’ve also written about in situ chemistry, in which a protein catalyzes the formation of an inhibitor. An interesting marriage of these concepts has just been published (open access) in Mol. Cell by Robert Hughes (Disarm Therapeutics), Thomas Ve (Griffith University) and a group of international collaborators.

 

The researchers were interested in the protein SARM1, which is implicated in the axon degeneration associated with several neurodegenerative disorders. Last year the researchers published a Cell Rep. paper (also open access) in which a biochemical screen of roughly 200,000 molecules led to the discovery of isoquinoline as a 10 µM inhibitor of SARM1. Optimization led to 5-iodoisoqinoline, dubbed DSRM-3716, a 75 nM fragment-sized inhibitor. The paper goes on to demonstrate that the molecule not only prevents axonal degeneration but can even promote recovery of injured axons. The new paper explores the mechanism of action.

 

SARM1 is an NADase: it cleaves the critical cofactor nicotinamide adenine dinucleotide (NAD⁺). While using NMR to study the mechanism of inhibition, the researchers found that DSRM-3716 reacts with NAD⁺ to form the new compound shown. In this sense, DSRM-3716 acts as a prodrug, somewhat analogous to sulfanilamide antibiotics which act as PABA mimics to block folate biosynthesis.

 

What’s behind the inhibition of SARM1? A series of crystallographic and cryo-EM studies of SARM1 reveal that the protein can self-associate into multimers which are either inactive or active depending on the relative orientations of the individual proteins. NAD⁺ normally binds at the interface between two SARM1 proteins. The compound made from NAD⁺ and DSRM-3716 binds here as well, blocking further activity. The crystal structures also revealed a clear halogen bond (see here) with the iodine in DSRM-3716, explaining the increased activity over isoquinoline itself.

 

Unlike the nucleophilic fragments we wrote about last month, isoquinoline probably won’t raise too many eyebrows among medicinal chemists, as the moiety is found in a handful of approved drugs. The researchers also demonstrated that DSRM-3716 itself is selective for SARM1 in a panel of other enzymes that use NAD⁺.

 

This is a lovely case of high-throughput screening in which the hit turns out to be a fragment. Indeed, the highly charged compound that actually inhibits SARM1 would not be cell-permeable, but that's just fine since it is formed inside cells. It is worth noting that nearly 1000 approved drugs could be classified as fragments in terms of molecular weight. In the case of CNS drugs, small is beautiful, and it will be fun to watch how far DSRM-3716 derivatives will be able to advance.

Fragments in space!

Practical Fragments has discussed fragments on Mars and Venus, but those planets are just two small specks in a vast universe. Always thinking big, the luminaries at DREADCO (who previously brought us fragment screening in cells using cryo-EM) have set their sights on deep space. Their theoretical proposal has just been published in the Journal of Extraterrestrial and Space Technologies.

 

One of the big unknowns in molecular recognition is precisely how small molecule ligands approach proteins. To find out, the researchers propose creating a library of fragments, each of which is attached to a very tiny mirror. Proteins of interest would also have tiny mirrors affixed to them. Laser interferometry would be used to study the interactions of proteins and ligands in extremely dilute solutions.

 

One potential problem with this approach is gravity, which is hard to escape on Earth, so the researchers propose running their experiment at a Lagrange point. They had hoped to catch a ride on the James Webb Space Telescope, but the mirror fabrication has taken longer than expected.

 

Even for a secretive multinational megacorporation like DREADCO this will be an expensive endeavor, so they’ll probably have to wait until they’ve eradicated human disease before launching this project. In the meantime, they’re taking suggestions for protein targets – feel free to leave yours in the comments!

Why HDX-MS is rare in FBLD – and practical tips to change this

Hydrogen/deuterium exchange mass spectrometry (HDX-MS) can help identify the binding site of a ligand, sometimes. Briefly, a protein-ligand complex is diluted into a solution of D₂O; exchangeable hydrogens on the protein will be replaced by deuterium, and those that interact with the ligand will be protected. A comparison with the protein alone will thus reveal which region interacts with the ligand. Practical Fragments discussed the technique back in 2012 and 2014, but since then it has been mentioned only a handful of times. In a new paper in J. Am. Soc. Mass Spectrom. Yoshitomo Hamuro and Stephen Coales (ExSAR) provide insights into why it is rarely used in FBLD, and offer solutions.

 

The researchers argue that the main problem with using HDX-MS in FBLD is that fragments often have low affinities and low solubilities. A theoretical analysis reveals that “the concentration of a ligand, not the molar excess of a ligand over a protein, is the key to drive the equilibrium to complex formation.” A series of calculations with hypothetical ligands having dissociation constants of either 100 µM or 1000 µM reveals that changing the concentration of protein is unlikely to have much effect on the outcome of the experiment, whereas increasing the concentration of ligand will give cleaner data. The problem is that many fragments may not be soluble at sufficiently high concentrations.

 

To solve this challenge, the researchers provide two solutions. First, they suggest spiking ligand into the D₂O exchange buffer; this will keep the ligand from being diluted.

 

A second fix is similar: rather than diluting a protein-ligand complex 1:9 into D₂O, the researchers suggest a 1:1 dilution, so the ligand concentration drops only by half rather than by 10-fold.

 

High concentrations of ligand can potentially interfere with the mass spectrometry measurements, so the researchers also suggest using smaller volumes with higher concentrations of protein.

 

These all seem like simple, practical measures to make HDX-MS more applicable to FBLD, but unfortunately the paper does not actually provide any experimental proof of concept data, so I’ll put the question to you, dear readers: have you found HDX-MS useful in FBLD? If so, under what conditions?

Nucleophilic fragments: the other kind of covalent inhibitors

Covalent fragment-based lead discovery is becoming increasingly popular, spurred on by the rapid discovery and approval of sotorasib. In general, covalent inhibitors contain cysteine-reactive electrophiles, though efforts are also targeting other amino acid residues such as serine and lysine. In all these cases though, the fragment contains an electrophile, while the protein contains the nucleophile. A new paper in J. Am. Chem. Soc. by Megan Matthews and collaborators at University of Pennsylvania and Oberlin College turns things around.

 

None of the twenty standard amino acids are electrophilic, but some proteins do use electrophilic cofactors, such as pyridoxal phosphate. Moreover, some proteins undergo post-translational modifications which introduce a pyruvoyl (Pyvl) or glyoxylyl (Glox) group onto the N-terminus; these contain, respectively, an electrophilic ketone or aldehyde. As we wrote about here, aldehydes and ketones can react covalently with hydrazines, and the new paper shows that the kinetics of this reaction vary – as expected – with the nucleophilicity of the hydrazine.

 

Next, the researchers assembled a library of 17 fragment probes containing both a nucleophile as well as an alkyne that could be used for click chemistry. These probes were screened against cells for 30 minutes at 37 °C, the cells were lysed, labeled proteins conjugated to a dye, and the whole gemish run on a denaturing gel; the results showed a wide range of reactivities for the different probes.

 

To assess which proteins were reacting with which probes, the researchers turned to isoTOP-ABPP, a chemoproteomic method we previously wrote about here in the context of electrophilic fragments. (Chemical biologists are fond of abbreviations, and they call this new approach with nucleophilic fragments “reverse-polarity activity-based protein profiling”, or RP-ABPP.) Three probes, P11, P12, and P13, were found to modify 98, 60, and 16 proteins, respectively. Remarkably, despite their small size and common hydrazine nucleophile, only a single protein was labeled by all three probes.

 

Two of the proteins labeled by P11 include secernin-2 and -3 (SCRN2 and SCRN3). The functions of these proteins are unknown, though genome-wide studies have associated SCRN3 with several diseases.

 

The requirement for the probes to contain both an alkyne handle and a nucleophile increases complexity, and the researchers recognized that they could use the probes in competition mode against fragments lacking the alkyne. They assembled a set of 45 nucleophile-containing fragments and treated cell lysates with these, followed by treatment with probe P11, click chemistry to introduce a fluorescent dye, and gel electrophoresis. Hydrazine-containing fragments that inhibited the binding of P11 were found for SCRN2, SCRN3, and the protein AMD1. Some of these fragments showed EC₅₀ values less than 1 µM and were up to 25-fold selective for SCRN3 over SCRN2 despite the 54% sequence identity shared between the two proteins.

 

An orthodox medicinal chemist might sniff at the hydrazine moiety in these molecules, but it is worth noting that P12, P13, and P17 are all derived from approved drugs (carbidopa, hydralazine, and phenelzine; substructures colored blue).

 

The functional roles of Pyvl and Glox modifications in proteins are poorly understood, and whether modulating them will prove useful in treating diseases remains uncertain. But the best way to answer this question will be by inventing suitable chemical probes. This paper suggests that nucleophilic fragments may prove useful.

Higher hit rates with heavier halogens

Halogen bonding is an esoteric type of molecular interaction. Any first-year chemistry student can tell you that halogens are electronegative. More advanced students learn that the electron density on a halogen attached to a carbon is not evenly distributed. Rather, an electron deficient region appears directly opposite the carbon bond on chlorine, bromine, and iodine atoms. This “σ-hole” can form attractive interactions with electron-rich moieties, such as backbone carbonyl atoms. These highly directional interactions can be useful alternatives to hydrogen bonds, especially since they allow a reduction in the number of hydrogen bond donors. But how to find them? This is the topic of a recent open-access paper in Frontiers in Chemistry by Frank Boeckler and collaborators at Eberhard Karls Universität Tübingen.

 

The researchers constructed a library of 191 commercially available halogen-enriched fragments (called HEFLibs), which we wrote about in 2019. Most fragments have a single halogen atom, though 15 have two of the same type (two chlorine atoms, for example). The initial publication had no screening data, but the new paper describes screening the library against four diverse proteins: the methyltransferase DOT1L, the oxygenase IDO1, and the kinases AAK1 and CAMK1G.

 

Ligand-detected STD NMR was used as the primary screen, with proteins present at 20 µM and fragments at 1 mM each in mixtures of two. Between 9 and 57 hits were found for each target, with unique hits for all the targets except DOT1L. Some fragments hit all four targets, including one similar to the "universal fragment" we highlighted here.

 

Interestingly, iodine-containing fragments gave higher hit rates than bromine-containing fragments, which in turn gave higher hit rates than chlorine-containing fragments. Specifically, 9 of 14 (64%) iodine-containing fragments hit at least one target, vs 51% and 35% for bromine- and chlorine-containing fragments.

 

To assess whether halogen bonding played a role, the researchers calculated maximum electrostatic potential (V_max) for each fragment; this is a measure of the size of the σ-hole. Fragment hits tended to have higher V_max values than non-hits.

 

One possible confounding influence is that aryl halides can react with cysteine residues in proteins, and indeed the researchers did find that some of their fragments are unstable in the presence of the cellular reducing agent glutathione.

 

To confirm the STD-NMR results with an orthogonal method, the researchers turned to isothermal titration calorimetry (ITC). Of 57 fragment-protein pairs tested, only ten gave K_D values less than 1 mM, and nine were against the kinases; there were even a couple single-digit micromolar binders for AAK1. ITC is less sensitive than NMR, so some of the other fragments may bind too weakly to fully characterize.

 

Unfortunately, crystallography has been unsuccessful so far, so it remains unclear whether any of the hits are actually making halogen bonding interactions with the proteins. Halogens are good at filling lipophilic pockets, so it is perhaps likely that less specific van der Waals interactions are the key affinity drivers. But the Boeckler group has been pursuing halogen bonding for more than a decade, so I look forward to seeing more on this topic.

 

And in the meantime, happy Pi Day!

Virtual screening succeeds against the SARS-CoV-2 main protease

Today marks exactly two years since Practical Fragments first mentioned SARS-CoV-2. Since then, COVID-19 has killed more than 6 million people worldwide. Multiple effective vaccines have been developed and approved, along with a couple small-molecule drugs, but the virus is here to stay, and more drugs will be needed. This brings us to an open-access paper published in J. Am. Chem. Soc. by Jens Carlsson (Uppsala University) and a large group of international collaborators.

 

The so-called main protease (M^pro, or 3CLp) has been an antiviral target since the earliest days of the pandemic; the work we highlighted two years ago focused on a crystallographic screen against this enzyme. The new paper describes two virtual screening approaches.

 

The first started with a library of 235 million virtual compounds, mostly from Enamine’s “readily available for synthesis” (REAL) collection. Each compound was docked in thousands of different orientations against the active site of M^pro using DOCK3.7. Despite the staggering numbers (more than 223 trillion complexes!), the screen took just a day on 3500 CPU cores. The top 300,000 compounds were clustered based on similarity, and 100 molecules were synthesized. Nineteen of these showed binding by SPR, and three also inhibited the enzyme. Crystal structures were obtained for two of these, and both bound similarly to the predicted binding modes.

 

Compounds 1 and 3 each contain a hydantoin moiety that makes multiple hydrogen bonds to the protein, and merging elements led to low micromolar compounds such as compound 15. Further optimization ultimately delivered compound 19.

 

Compound 19 was potent in SPR and biochemical assays. Though it binds noncovalently, it had comparable cellular activity to nirmatrelvir, the recently approved covalent inhibitor of M^pro. Compound 19 showed nanomolar cell potency against SARS-CoV-1 and MERS-CoV and good selectivity against ten human proteases. The in vitro stability and permeability of compound 19 are also promising.

 

In addition to this de novo virtual screen, the researchers performed a second screen starting from one of the fragments identified crystallographically at Diamond Light Source. Of 93 molecules purchased and experimentally tested, 21 showed binding by SPR and 5 of these also inhibited the enzyme, with the most potent compound showing low micromolar activity.

 

There are several lessons from this paper. First, despite searching hundreds of millions of compounds, the best hits had only modest activity. This is perhaps surprising given the high fragment hit rates observed against M^pro in crystallographic and NMR screens, though it is worth noting that those fragments were even weaker binders.

 

Second, the hit rate from the naïve virtual screen was similar to that from the experimentally derived fragment screen. The researchers suggest that perhaps docking “may be more proficient in ranking diverse chemotypes rather than differentiating between closely related elaborations of the same scaffold.” In other words, virtual screens seem better at evaluating diverse starting points rather many similar molecules.

 

Third, despite the fact that the de novo virtual screen was not explicitly fragment-based, compound 1 does actually adhere to the rule of three. From there, addition of just six atoms improved affinity by >600-fold while also improving ligand efficiency.

 

Finally, this work is a testament to the utility of combining massive virtual screening with readily synthesizable compounds: the researchers note that it took less than four months to progress from compound 1 to nanomolar inhibitors.

 

This work relied heavily on rapid chemical synthesis done in Ukraine. Indeed, the two most popular fragment suppliers are both largely based in that country. Over the years many of us have come to know Ukrainian scientists not just as trusted colleagues but also as friends. I wish them and their families safety, and strength.

Photoaffinity fragment PhABits, faster

Practical Fragments has written previously about PhotoAffinity Bits, or PhABits, which are fragments designed to reveal binding (as opposed to inhibition). These fragments contain a photoreactive moiety such as a diazirine. When incubated with a protein target and irradiated by ultraviolet light, the diazirine transforms into reactive species that can react irreversibly with anything nearby. Intact protein mass spectrometry can identify whether a reaction has occurred, and further proteomics experiments can identify more precisely where the PhABits reacted.

 

One challenge with this approach is obtaining a library of PhABits; few are commercially available (though AstraZeneca is sharing a set). In a recent open-access Chem. Sci. paper, Jacob Bush and collaborators at GlaxoSmithKline and University of Strathclyde describe speeding up the process.

 

The approach is called direct-to-biology high-throughput chemistry (D2B-HTC). Recognizing that purification is often the rate-limiting step in library synthesis, the researchers synthesized PhABits in 384-well plates and used the crude reaction mixtures directly. In short, a diazirine moiety linked to an activated ester was reacted for 24 hours with 1073 diverse alkylamines chosen from the GlaxoSmithKline internal collection. Interestingly, 54 of the amines themselves were not pure as judged by LC-MS – a useful reminder of the importance of quality control. Ultimately, 853 of the reactions were deemed successful, with >80% purity. Residual activated ester was quenched with hydroxylamine, and the reactions were performed in biologically compatible DMSO so that they could be used directly.

 

Next, each member of the library was screened at 100 µM against human carbonic anhydrase I (CAI, at 1 µM), a well-characterized model protein. After UV light illumination (302 nm for 10 minutes) the reactions were analyzed by mass spectrometry, resulting in seven hits, defined as > 1.5% covalent adduct. Five of these contained a primary sulfonamide, a privileged pharmacophore for carbonic anhydrases. Dose response experiments gave similar results on both the crude mixtures as well as resynthesized, pure compounds, with the best molecule showing high nanomolar activity. All seven PhABits could be competed with the known ligand ethoxzolamide, suggesting that they bind in the active site of the enzyme.

 

The seven hits gave even higher levels of modification with carbonic anhydrase II (CAII), and four of the sulfonamide-containing hits were further characterized by proteolyzing the modified enzyme and using LC-MS/MS to determine the sites of modification. This revealed that the PhABits were reacting with either a glutamic acid or histidine residue at the entrance of the active site. As we discussed last year, the precise nature of the diazirine probe can affect which amino acid residues are likely to react.

 

Based on the SAR from the primary screen, a second 100-member library was constructed and screened without purification. This provided a much higher hit rate, with all 52 hits containing a primary sulfonamide.

 

I do wish the researchers had used an orthogonal method to assess the affinities of their molecules. One drawback of the approach, which they note, is that “the absolute value of the crosslinking yield is not indicative of binding affinity,” but it would be interesting to know whether there is any correlation at all. It would also be nice to get a sense of how often false negatives occur.

 

Still, D2B-HTC adds to the growing list of methods that screen crude reaction mixtures, alongside related approaches such as off-rate screening, Chemotype Evolution, and REFiL_x. The future may be a bit dirty, but perhaps we can get to our destination faster.

Ensembles of fragment structures guide selectivity

Scientists generally want structural information when a project begins, and ideally that structural information comes from crystallography. Most of us who have been doing drug discovery for a while can remember seeing the first structure of a favorite molecule bound to a target protein and being inspired, reassured, or sometimes confused. But as crystallography becomes increasingly high throughput, it is now not uncommon to obtain dozens or even hundreds of structures. What to do with all this bounty? In a recent open-access J. Chem. Inf. Model. paper, Mihaela Smilova, Brian Marsden, and collaborators at University of Oxford, the Cambridge Crystallographic Data Centre, and Exscientia describe one application.

 

Back in 2016 we wrote about a computational approach called hotspot mapping, which uses three small fragment probes (aniline, cyclohexa-2,5-dien-1-one, and toluene) to virtually explore potential binding sites and map hydrogen bond acceptors, donors, and apolar interactions. The idea was to predict binding sites and the key interactions likely to drive affinity. The new paper focuses not just on affinity, but on selectivity.

 

The approach starts by taking multiple structures of the same protein bound to various ligands, especially fragments. Ligands and water molecules are then removed, and hotspot mapping is conducted for each structure. Then, all the hotspot maps are combined to generate an “ensemble” hotspot map, which in theory should give a more complete picture of potential attractive and repulsive interactions than a single structure.

 

To assess selectivity, the ensemble hotspot map of one protein is “subtracted” from that of another. If the proteins are very closely related, this “selectivity map” might be empty: all the interactions for one protein would be present in the other. But if there are differences, they become very apparent.

 

Several retrospective case studies are provided. In the first, ensemble hotspot maps were generated from the closely related bromodomains BRD1 and BRPF1, using 23 and 26 fragment-bound structures, respectively. The selectivity map clearly shows the potential for a hydrogen bond donor on a ligand to bind to the backbone amide of a serine in BRD1; the corresponding residue in BRPF1 is a proline, incapable of making this interaction. And indeed, an examination of the literature revealed that this interaction had previously been used to generate inhibitors of BRD1 that were 15-fold selective over BRPF1.

 

The kinases p38α and ERK2 are also closely related, but selectivity maps generated from five p38α structures and 17 ERK2 structures revealed a hydrophobic pocket in the former but not in the latter. This pocket had previously been used to generate selective inhibitors of p38α. Similarly, 28 structures of CK2α and 32 structures of PIM1 were used to generate a selectivity map that also revealed a hydrophobic pocket that can form in the former protein and had been used to generate selective inhibitors.

 

Generally, the more structures available, the more informative the selectivity maps are. The researchers note that though they only used five p38α structures, the fragments were chosen to be diverse (and interestingly all of them made interactions in the hydrophobic pocket). Also, while some protein flexibility can improve the maps, too much is a problem. (For the kinases, only DFG-in structures were used, for example.)

 

This method is a nice synthesis of experimental and computational techniques. A skeptic might argue that it doesn’t provide fundamentally new information: in the examples provided, the selectivity features had already been found and exploited by medicinal chemists. But the automated process and the clear output may speed things up, especially for newer targets, and indeed the researchers note that it is being applied in-house at Exscientia.

 

Perhaps most importantly, if you’d like to try it yourself, the code is freely available here. Happy mapping!

Fragment merging vs bacterial SAICAR synthetase

People living with cystic fibrosis are susceptible to lung infections from a rogues’ gallery of bacterial species, one of which is Mycobacterium abscessus. It is often antibiotic resistant, and even when it responds, a course of antibiotics can take two years to resolve the infection. In a recent ACS Infect. Dis. paper Tom Blundell, Anthony Coyne, and collaborators at University of Cambridge and elsewhere describe progress against this organism.

 

The researchers chose to target a protein called SAICAR synthetase, or PurC, which is essential for purine biosynthesis and thus bacterial growth, as shown by genetic knockout studies. The enzyme is significantly different from the human ortholog, but similar to the Mycobacterium tuberculosis ortholog, giving the potential for a twofer.

 

Fragment screening was conducted both in-house using thermal shift assays as well as at XChem using crystallography; we discussed the differing outputs of these screens in this 2019 post. Compound 1, from the in-house screen, was found crystallographically to bind in the ATP-binding site, and ITC studies revealed it to have high micromolar affinity for the protein. Meanwhile, compound 2 was identified from the crystallographic screen, and while the affinity wasn’t measured, the pyridyl ring is located a short distance from where compound 1 binds.

 

Initial SAR around fragment 1 revealed that growing toward the binding site of compound 2 would be possible, as illustrated by compound 9. Appending a pyridyl ring onto this molecule led to compound 16, with low micromolar affinity. The pyridyl moiety stacks onto an arginine side chain, and improving this interaction by replacing the pyridyl with a phenyl appended with electron-withdrawing fluorine atoms led to compound 27, with submicromolar activity. Overlaying the crystal structures of compounds 1 (cyan), 2 (magenta), and 27 (gray) reveals that the merged molecule does indeed bind in a similar manner to the component fragments.

Unfortunately, despite good biochemical activity against PurC, none of the compounds were particularly effective at inhibiting growth of either M. abscessus or M. tuberculosis. Such disconnects between biochemical and cell potency are unfortunately all too common, particularly for antimicrobial targets, as we wrote about here. The researchers suggest possible reasons including efflux and physicochemical properties. The paper ends by noting that work is continuing, and we look forward to hearing more.

Automated scaffold hopping for fragments

A post last month covered high-throughput virtual screening, but most practitioners of FBLD still start with some sort of (bio)physical screen. These initial hits can’t be expected to be optimal, since the average fragment library contains a few thousand compounds at most. Indeed, as Xavier Barril and collaborators at Universitat de Barcelona and Oxford University write, “fragment hits should be seen as beacons indicating privileged areas of chemical space to be further explored.” They describe one way to expedite exploration in a recent J. Med. Chem. paper.

 

As we noted here, most good fragments make at least one essential interaction (such as a hydrogen bond) to the protein. The approach starts with a structure of a fragment bound to the target of interest, with that essential interaction identified.

 

Next, a virtual library is searched for similar molecules, with the definition of “similar” being rather loose (>50% Tanimoto similarity). Ideally the library is large enough to produce lots of hits; the researchers used ZINC15, which contains >15 million ostensibly commercial compounds. Also, only molecules within two non-hydrogen atoms of the starting fragment are considered. In other words, a fragment with ten “heavy” atoms would yield molecules with 8-12 non-hydrogen atoms. This search is similar though perhaps more permissive than Astex’s Fragment Network (which we wrote about here).

 

All the molecules are then superposed on the initial fragment structure and only those that maintain the key interaction and binding mode are kept. Aboout 500 molecules are then selected to represent the best and most-diverse hits. These are subjected to dynamic undocking (DUck), which weeds out fragments that have weaker interactions. If desired, each of the remaining hits can be subjected to further cycles.

 

To demonstrate the approach, the researchers turned to bromodomains, a popular target class for FBLD. They started with 1XA, a fragment Teddy highlighted back in 2013 that led to a clinical compound against BRD4. The isoxazole moiety makes a hydrogen bond with the side chain nitrogen of an asparagine that normally binds to acetylated lysine residues. After one cycle, 58 molecules were selected, but unfortunately only five were actually available commercially. Compound 3 had similar affinity and ligand efficiency as 1XA, and this scaffold had not been reported as a bromodomain ligand. A crystal structure of compound 3 bound to the first bromodomain of BRD4 confirmed the predicted binding mode.

Three additional successive iterations were conducted to look for more ligands, but experimental confirmation was challenging as overall only 17 of more than 100 ligands selected for purchase were commercially available. (Compound 23 was chosen for custom synthesis as it was related to a family of high-scoring molecules.) Encouragingly, eight molecules were active in a differential scanning fluorimetry (DSF) assay, a technique that works well for BRD4. Crystal structures of two of these were obtained: compound 9 contains an isoxazole moiety like 1XA (and indeed resembles this fragment) but compound 23 is quite distinct.

Overall this looks like a valuable method for scaffold hopping. Not only might the described approach lead to novel molecules, it could provide new growth vectors that may not be accessible from the original fragment. Before jumping immediately into chemistry with your fragment hits, it may be worth trying something like this.

A framework for evaluating commercial fragment libraries

The easiest way to build a fragment library is to purchase one. Quite a few vendors sell fragments, and as our poll from a few years ago demonstrated, most buyers are quite happy with them. But what exactly do they offer? This is the subject of a new paper by Gilles Marcou, Esther Kellenberger, and colleagues at CNRS Université de Strasbourg in RSC Med. Chem.

 

The researchers analyzed 86 different libraries from 14 vendors that were available in February of 2021. These were classified into ten categories, such as “general,” “3D-shaped,” “metal chelating,” “diverse,” “covalent,” etc. Individual library sizes ranged considerably: 41 had ≤ 2000 compounds, 31 had 2000-10,000, and 14 libraries had > 10,000 molecules. The total number of fragments came to 754,646, of which 512,284 were unique, indicating some redundancy between libraries. Laudably, the structures and several analyses are all provided as downloadable files here.

 

Most of the fragments are 200-300 Da, with only 13% less than 200 Da. This skew towards larger molecules is common but may not be desirable, as researchers at Astex demonstrated back in 2014. On the other hand, people do seem to be paying attention to lipophilicity: nearly half the fragments have AlogP < 1. Interestingly, less than a quarter of fragments strictly fulfill the rule of three, though the majority of violations are for more than 3 hydrogen bond acceptors, which is probably not as important as the other criteria, according to analyses of approved drugs.

 

Two different methods were used to assess diversity. These were applied to 433,433 compounds from fifty libraries; specialized libraries such as fluorine-rich and covalent libraries were excluded. The first analysis deconstructed fragments into 59,270 component scaffolds. Not surprisingly, benzene was the most common, present in nearly 5% of all fragments. Quinoline, indole, pyridine, and benzimidazole all were present in at least 1% of compounds. At the other end of the spectrum, 36,555 scaffolds occurred only once. Not surprisingly, these tended to be more complex.

 

In addition to assessing scaffolds, the researchers developed a “Generative Topographical Map (GTM) model to represent the chemical space in a landscape.” The resulting figures do indeed look like topographical maps, with darker regions corresponding to more populated areas. For example, since substituted benzimidazoles are common and similar to one another, they form a dark cluster. Not unexpectedly, the landscape for the set of 433,433 compounds is heterogenous, with denser regions separated by sparsely-populated regions.

 

A nice feature of the GTM model is that it allows easy, intuitive comparisons. For example, some of the “diverse” libraries are more diverse than others, or emphasize different regions of chemical space, and potential customers may want to take these into account.

 

Fragment shapeliness was assessed using plane of best fit (PBF), where lower values correspond to “flatter” molecules, such as benzene, with PBF = 0. The libraries varied considerably in their average PBF, though reassuringly the “3D-shaped” libraries did have higher values. Interestingly, GTM models showed both flat (PBF < 0.1) and non-planar (PBF ≥ 0.1) fragments had similar distributions across fragment space.

 

Overall this is a valuable snapshot of the current state of commercial libraries, and makes a useful complement to the ongoing analysis Chris Swain does at Cambridge MedChem Consulting. Of course, the devil is in the details; PAINS still sometimes show up in commercial libraries, and quality control can vary. In the end you’ll want to do your own vetting, but this is a good place to start.

Fragments (almost) in the clinic: MRTX1719

Synthetic lethality is a relatively new approach to cancer therapy. The idea is to inhibit a protein that is necessary for cancer cells but dispensable for normal cells, thereby minimizing toxicity. Last year we described one example, and in a just-published open access J. Med. Chem. paper Chris Smith and colleagues at Mirati describe another.

 

The biology gets a bit complicated, so please bear with me. Protein arginine methyl transferase 5 (PRMT5) is an epigenetic writer that adds two methyl groups to arginine residues in a wide variety of proteins. It is essential for cell survival. PRMT5 uses a cofactor, S-adenosyl-L-methionine (SAM), that is converted to methylthioadenosine (MTA) during the reaction. In certain cancers a gene called methylthioadenosine phosphorylase (MTAP) is deleted, causing an accumulation of MTA and – through product inhibition – a decrease in PRMT5 activity. The idea is to develop a drug that binds to and further stabilizes the (inactive) PRMT5•MTA complex, which is abundant in cancer cells, while not interfering with the active form of the protein, which predominates in normal cells. Told you it was complicated! [Note added: as befits the complicated biology I got a couple things wrong, corrected in the comment on 26 Jan.]

 

The researchers started with an SPR screen of 1000 commercially available fragments, each at 100 µM. PRMT5 was immobilized on the chip, with MTA added to the buffer to form the PRMT5•MTA complex. This screen yielded 17 hits, and based on this encouraging result a further set of nearly 1900 fragments was screened at 500 µM. The higher concentration yielded significantly more hits, and when these were tested in dose response experiments 100 were found with dissociation constants better than 1 mM. The best 24 of these were then screened against PRMT5 loaded with either MTA or the cofactor SAM. Compound F1 proved to be 5-fold selective for the MTA-bound protein over the SAM-bound protein.

 

Crystallography revealed that this molecule binds in the substrate-binding site in the vicinity of MTA and suggested that it would clash with SAM binding, thus providing an explanation for its selectivity. The crystal structure also revealed a nearby pocket that could be targeted through fragment growing, and this was accomplished with compound 2, which also showed activity in a biochemical assay. Further structure-based design led eventually to compound 14, which was 26-fold selective for the MTA-bound protein.

 

Crystallography revealed another lipophilic pocket, and adding a phenyl group provided a nice increase in potency in the form of compound 15. This molecule also showed low micromolar cell activity. Further structure-based drug design ultimately led to MRTX1719; the medicinal chemistry is elegant but beyond the scope of this post. Chemists will recognize that the final molecule is an atropisomer. This type of stereoisomer is uncommon in drugs in part because they can be difficult to separate; the researchers note assessing 70 different conditions before abandoning one series in favor of a more tractable one.

 

The dissociation constant of MRTX1719 was measured by SPR as 0.14 pM and 9.4 pM for the PRMT5•MTA and PRMT5•SAM complexes, respectively. We don’t encounter femtomolar binders very often; the dissociation half-life for the MTA-bound protein is 14 days! The 67-fold difference in binding was in good agreement with 70-80-fold differences in cells without or with MTAP.

 

MRTX1719 was quite selective in a panel of 42 methyltransferases. Pharmacokinetics and oral bioavailability were good in mice, dogs, and cynomolgus monkeys. The molecule was well tolerated in a mouse tumor model and caused tumor growth inhibition. Based on these results, an IND for the molecule has been submitted to the FDA.

 

This is a lovely fragment-to-candidate story, and Practical Fragments wishes everyone involved good fortune in the clinic!

An epidemic of aggregators, and suggestions for cures

COVID-19 has been with us for over two years now. While the human effects have been unquestionably negative, for science it has been the best of times and the worst of times. The development of remarkably effective vaccines in less than a year stands as a triumph of twenty-first century medicine, as does the discovery of nirmatrelvir, a covalent inhibitor of the SARS-CoV-2 main protease M^pro (also called 3CL-Pro). But there is a lot of junk-science out there too, as illuminated in a recent J. Med. Chem. paper by Brian Shoichet and colleagues at University of California San Francisco.

 

Before vaccines and custom-built drugs were developed, labs everywhere started screening all the compounds they could get against targets relevant for COVID-19. The most popular molecules to test were approved drugs, the idea being that if any of these turned out to be effective they could immediately be put to use.

 

One of the most common artifacts in screening is caused by aggregation: small molecules can form colloids that non-specifically inhibit a variety of different assays. This phenomenon has been understood for more than two decades; Practical Fragments wrote about it back in 2009. Unfortunately, many labs ignore it.

 

The UCSF lab investigated 56 drugs that had been reported in 12 papers as inhibitors against two targets relevant for SARS-CoV-2, including 3CL-Pro. The molecules were characterized in multiple assays: particle formation and clean autocorrelation curves in dynamic light scattering (DLS), inhibition of an aggregation-sensitive enzyme in the absence of detergent but no inhibition in the presence of detergent, and a high Hill slope in the dose-response curve. Nineteen molecules, four of them fragment-sized, were positive in most of these assays, clearly indicating aggregation. (Interestingly, several of these gave reasonable Hill slopes (<1.4), and the researchers suggest this be a “soft criterion.”) Another 14 molecules gave more ambiguous results, such as forming particles by DLS but not inhibiting the sentinel enzyme.

 

OK, so maybe the molecules are aggregators, but perhaps they also act legitimately? Unfortunately, of the 12 drugs reported in the literature to inhibit 3CL-Pro, only two inhibited the enzyme in the presence of detergent, and one of these was five-fold less potent than reported. And as the researchers point out, detergent is not a magic elixir, and sometimes only right-shifts the onset of aggregation. Moreover, of the 19 molecules conclusively found to be aggregators, detergent was not included for 15 of them in the original publications. Brian may be too polite to write this, but channeling my inner Teddy, I would argue that the authors are negligent for failing to test for aggregation, as are the editors and reviewers who allowed these papers to be published.

 

And the problem is not confined to the COVID-19 literature. The researchers examined a commercial library of 2336 FDA-approved drugs, 73 of which are known aggregators. Another 356 were flagged in the very useful Aggregation Advisor tool (see here), and 6 of 15 experimentally evaluated tested positive in all the aggregation assays.

 

How do you avoid being misled by these artifacts? An extensive suite of tools for assessing aggregation is provided in a recent Nat. Protoc. paper by Steven LaPlante and colleagues at Université du Québec and NMX. The procedures are described in sufficient detail that they “can be easily performed by graduate students and even undergraduate students.”

 

Most of the focus is on various NMR techniques, such as one we wrote about here. The easiest is an NMR dilution assay, in which a 20 mM solution of a compound in DMSO is serially diluted into aqueous buffer at concentrations from 200 to 12 µM. If the number, shape, shift, or intensities of the NMR resonances changes, aggregation is likely.

 

Another assay involves testing compounds in the absence and presence of various detergents, including NP40, Triton, SDS, CHAPS, Tween 20, and Tween 80. Again, changes in the NMR spectra suggest aggregation.

 

The researchers note that “no one technique can detect all the types of aggregates that exist; thus, a combination of strategies is necessary.” Indeed, the various techniques can distinguish different types of aggregates which can vary in size and polydispersity. On a lemons-to-lemonade note, these “nano-entities” might even be useful for “drug delivery, anti-aggregates, cell penetrators and bioavailability enhancers.”

 

We live in the age of wisdom and the age of foolishness. As scientists – and as people – it is our responsibility to aspire to the former by being aware of “unknown knowns,” such as aggregation. And perhaps, by even taking advantage of the weird phenomena that can occur with small molecules in water.

Virtually screening 11 billion compounds – no problem!

Three years ago we highlighted virtual screens of roughly 100 million molecules which led to numerous high-affinity ligands against two targets. Those efforts made use of the Enamine “readily available for synthesis” (REAL) library, a virtual catalog of molecules that can be rapidly made and delivered. Enamine is continuing to grow this resource, which as of last year stood at 11 billion compounds. This is an impressive number, but how do you make use of it? In a just-published paper in Nature, Vsevolod Katritch (University of Southern California, Los Angeles) and a large group of collaborators provide a promising fragment-based solution.

 

Molecules in the Enamine REAL collection can be made using one-pot parallel synthesis from two or three reagents; for example, an amide could be made from an amine and a carboxylic acid. Enamine built a set of 75,000 reagents and 121 different reactions which collectively could produce 11 billion molecules (it’s even larger now). However, docking all of these could take thousands of years on a single CPU or cost hundreds of thousands of dollars on a computing cloud.

 

Rather than docking all the Enamine REAL compounds, the researchers developed an approach called virtual synthon hierarchical enumeration screening, or V-SYNTHES. The first step is to create a library of scaffolds with molecular weights in the 250-350 Da range. Taking the amide example above, imagine linking a set of 1000 amines to benzoic acid and a set of 1000 carboxylic acids to methylamine. This 2000 compound minimal enumeration library, or MEL, could be considered a subset of the full 1000 x 1000 = 1,000,000 virtual amide library. The numbers are even more dramatic for a three-component reaction: a MEL of just 1500 compounds could represent 125,000,000 fully elaborated molecules.

 

The MEL is docked against a protein of interest, and a diverse set of the top-scoring compounds chosen for fragment growing. In our example, the benzoic acid “cap” on the best compounds would be replaced by the full set of 1000 carboxylic acids. These would then be virtually screened, and the top compounds synthesized and tested.

 

The researchers applied V-SYNTHES to two targets. The first was a cannabinoid receptor bound to an antagonist. A total of 1.5 million molecules were docked against CB₂, representing 11 billion fully enumerated compounds. After filtering the best hits to remove PAINS and molecules similar to known CB₂ ligands, 80 diverse compounds were chosen for actual synthesis and testing, of which Enamine was able to deliver 60 in less than 5 weeks. One-third of these turned out to be antagonists with K_i values < 10 µM in biological assays.

 

How does this compare to a brute-force approach? Screening all 11 billion molecules wasn’t feasible, so the researchers screened a representative subset of the Enamine REAL library consisting of 115 million molecules – two orders of magnitude larger than the libraries screened in V-SYNTHES. Of 97 compounds synthesized and tested, only 5 turned out to be antagonists of CB₂ with K_i values < 10 µM.

 

A nice feature of V-SYNTHES is that it is well-suited to SAR-by-catalog. This was demonstrated by looking for analogs of the three best hits within Enamine REAL space. Of 104 compounds synthesized and tested, more than half had K_i values < 10 µM, and 23 were submicromolar antagonists. In fact, several turned out to be low nanomolar and selective not just against the related CB₁ receptor but against a panel of 300 other GPCRs.

 

V-SYNTHES was also applied to the kinase ROCK1 and achieved similarly impressive results: six of 21 compounds synthesized and tested had K_d < 10 µM in a binding assay, and one was a low nanomolar inhibitor.

 

This is a lovely and practical application of fragment concepts. Importantly, because the computational cost only increases linearly with the number of synthetic components while the library size increases with the square (for two-component molecules), it is very scalable; the researchers suggest that “terascale and petascale libraries” should be “easily” accommodated. These are numbers beyond even what DNA-encoded libraries can promise.

 

Currently V-SYNTHES relies on a good structural model for docking, but as computational predictions of protein structures become ever more accurate, perhaps even this will cease to be a limitation. Our SkyFragNet post from 2019 is looking ever more prophetic, in a good way.

Fragment events in 2022

Will 2022 mark the full return of in-person conferences? That's the plan - here's hoping SARS-CoV-2 doesn't interfere.

February 5-9: The  SLAS2022 International Conference and Exhibition will be held in Boston, so if you're looking for new instrumentation this is the place to be.

March 20-24: The American Chemical Society will hold its Spring National Meeting both in-person and virtually in San Diego. There are bound to be fragment talks, including a session on Modern Screening Methods on March 24.

March 27-29: The Royal Society of Chemistry's Fragments 2022 will be held in the original Cambridge, and also virtually. This is the eighth in an esteemed conference series that historically has alternated years with the FBLD meetings. You can read my impressions of Fragments 2013 and Fragments 2009.

 

April 19-20: CHI’s Seventeenth Annual Fragment-Based Drug Discovery, the longest-running fragment event, returns in-person to sunny San Diego (and will also be online). This is part of the larger Drug Discovery Chemistry meeting. You can read impressions of the 2021 virtual meeting here, the 2020 virtual meeting here, the 2019 meeting here, the 2018 meeting here, the 2017 meeting here, the 2016 meeting here; the 2015 meeting here, here, and here; the 2014 meeting here and here; the 2013 meeting here and here; the 2012 meeting here; the 2011 meeting here; and 2010 here. 

May 9-11:  While not exclusively fragment-focused, the Eighth NovAliX Conference on Biophysics in Drug Discovery will have several relevant talks, and for the first time will use a hybrid model, both online and in Munich, Germany. You can read my impressions of the 2018 Boston event here, the 2017 Strasbourg event here, and Teddy's impressions of the 2013 event here, here, and here.

 

October 17-20: CHI’s Twentieth Annual Discovery on Target will be held both virtually and in Boston, as it was last year. As the name implies this event is more target-focused than chemistry-focused, but there are always plenty of FBDD-related talks. You can read my impressions of the 2020 virtual event here, the 2019 event here, and the 2018 event here.

 

Know of anything else? Please leave a comment or drop me a note!