Finding weak fragments for membrane proteins with WAC

Last week we wrote about NMR, one of the most popular fragment-finding methods. This week we turn to a less common technique: weak affinity chromatography, or WAC. As we’ve written previously, WAC involves immobilizing a protein of interest in a chromatography column and flowing a ligand-containing solution through the column. If the ligand interacts with the protein, its elution time will be delayed in proportion to its affinity. In a new (open-access) Molecules paper, Claire Demesmay and collaborators at Universite Claude Bernard Lyon and Ecole Supérieure de Biotechnologie de Strasbourg extend the technique to membrane proteins.

 

Membrane proteins are themselves tricky to study, since removing them from their membranes often denatures them. One trick is to use nanodiscs, which are tiny lipid bilayer islands surrounded by proteins that keep them soluble in water. These scaffolding proteins can also be biotinylated so that the nanondiscs can be attached to streptavidin, which itself can be linked to a surface or matrix. Each nanodisc holds one or at most a few membrane proteins.

 

When we first wrote about WAC in 2011 the technique used standard HPLC columns, which required non-negligible amounts of protein. Here, the technique has been miniaturized to use glass capillaries with volumes of less than 1 microliter, requiring only a few tens of picomoles of protein. The researchers fill the capillaries with a bio-compatible polymer, functionalize it with streptavidin, and then capture biotinylated nanodiscs containing the membrane protein of interest.

 

A long-recognized challenge with WAC is nonspecific binding of the fragments to the column or matrix. Here, the researchers chose a filling (or monolith) that is more hydrophilic (for aficionados, they picked poly(DHPMA-co-MBA)) and found it superior to the previous polymer both with regards to capacity and non-specific binding.

 

Another challenge with WAC is detecting low-affinity binders: because interactions with the protein are weak, the shift in retention time is harder to detect. One solution is to pack more protein in the column, and the researchers develop a clever way of doing this with a “multilayer grafting” approach in which successive injections of streptavidin and nanodiscs more effectively fill the capillary. The combination of a more hydrophilic filling and multilayer grafting increased the column capacity for nanodiscs by three-fold.

 

The researchers tested their approach on the adenosine-A2A receptor (AA_2AR), which has frequently been used as a model GPCR. Two previously reported weak ligands, both with affinities around 0.2 mM, could be detected, and competition with an orthosteric binder revealed that they were binding specifically.

 

This is a nice, how-to guide for performing WAC on membrane proteins, and the paper includes detailed equations for calculating affinities from differences in retention times. I look forward to seeing the technique used in de novo screens.

Fragments win in a virtual screen against the 5-HT2A receptor

Virtual screening is continuing to make impressive strides. The latest example, in Nature, comes from William Wetsel (Duke), John Irwin (UCSF), Georgios Skiniotis (Stanford), Brian Shoichet (UCSF), Bryan Roth (UNC Chapel Hill), Jonathan Ellman (Yale), and a large group of collaborators. The paper has received considerable attention (for example In the Pipeline), but in my opinion the connection to FBLD has been understated.

 

The researchers were interested in finding new agonists for the 5-HT_2A receptor (5-HT_2AR). This GPCR is the target for LSD and psilocybin, both of which have been shown to reduce depression and anxiety. Is it possible to find molecules with similar therapeutic activity but without the accompanying psychedelic properties?

 

LSD contains a tetrahydropyridine (THP) moiety, which is relatively rare in screening libraries. The researchers developed convergent routes to THPs in which they could independently and efficiently vary multiple substituents. Using this chemistry, they constructed a virtual library of 4.3 billion compounds, all with molecular weights ≤ 400 Da and cLogP ≤ 3.5.

 

At the time the research began, there were no structures of 5-HT_2AR, so the researchers built a homology model based on the closely related 5-HT_2BR, which differs by only four amino acid residues in the orthosteric pocket where LSD binds. This model was then screened against a subset of the THP library, those ≤ 350 Da. Despite screening some 7.45 trillion complexes (sampling an average of 92 conformations and 23,000 orientations per molecule), the process took only nine hours on a 1000-core CPU cluster. The result was 300,000 hits in nearly 15,000 families. To ensure novelty, only compounds quite different from known ligands were further considered, and 17 “richly functionalized” THPs were synthesized and tested in radioligand assays. Four were active, including racemic compound 28. Searching the 4.3 billion compound library for analogs ultimately led to compound 70 and a related, slightly more potent molecule lacking the methyl substituent on the amine. A cryo-EM structure subsequently validated the predicted binding mode.

 

The paper spends considerable time characterizing these two compounds. Both are agonists and somewhat selective for 5-HT_2AR over 5-HT_2BR and 5-HT_2CR. They are highly selective over 318 other GPCRs and 45 off-targets. GPCRs can signal through arrestin and/or G-protein, and while LSD works (mainly) through the arrestin pathway, the new molecules work (mainly) through the G-protein route. Importantly, the compounds showed anti-depressive and anti-anxiety effects in mouse models. Although you can’t ask mice if they are tripping, the molecules did not cause “head-twitch responses” and other behavioral effects seen with LSD, suggesting that they may not have hallucinogenic properties.

 

This is a lovely piece of work, and a few observations relevant to FBLD stand out. First, the best molecules are actually rule-of-three compliant, despite the fact that larger molecules were included in the virtual screen. Indeed, the top two molecules are actually smaller than the initial hits. This suggests that choosing more richly functionalized molecules may not have been the most efficient approach. We’ve written previously about V-SYNTHES, which entails stepwise selection and growing of fragments; it would be interesting to retroactively test whether this type of approach would have more quickly gotten to compound 70.

 

Finally, this approach can easily be extended to other scaffolds for which syntheses are readily available. Six years ago we wrote about the synthetic accessibility of dihydroisoquinolines, and last year Practical Fragments published our fifth “fragment library roundup.” The marriage of clever chemistry with virtual screening seems to have a bright future.

Fragments vs human Adensoine 2a Receptor using SPR

Last week we highlighted the use of surface plasmon resonance (SPR) to find ligands against RNA. Although RNA is not a typical protein target, it is at least normally free in solution. Targets such as GPCRs are more technically challenging because they are bound within membranes. Challenging, but not impossible, as illustrated by this post from 2012. A new ACS Med. Chem. Lett. paper by Reid Olsen, Iva Navratilova, and colleagues at Exscientia, University of Dundee, and AstraZeneca provides the latest example.

 

Navratilova and colleagues previously described using SPR to screen the β2 adrenergic receptor. In the new paper, the researchers studied the human adenosine 2a receptor (hA_2AR), a “rheostat for energy homeostasis” that also plays a role in cancer immunotherapy. hA_2AR is one member of a small family of adenosine receptors, and the researchers expressed all four of them, each with a polyhistidine tag that could be captured in the SPR instrument using a nickel-NTA sensor chip. Other labs (such as Heptares) have used mutant, stabilized forms of GPCRs, but here the researchers used native proteins and stabilized them by crosslinking them to the surface of the chip. They confirmed that these GPCRs bound known ligands with similar affinities to those reported in the literature.

 

Next the researchers screened a library of 656 fragments, each at 50 µM, against hA_2AR. This led to 72 potential hits taken into dose-response experiments, of which 17 confirmed with affinities ranging from 1.1 to 410 µM. All the sensorgrams are shown, as are the structures of the fragment hits. These confirmed hits were also screened against A₁, A_2B, and A₃; most of the fragments bound to all the receptors, though two were selective for hA_2AR.

 

To assess where the fragments bind, the researchers added a known high-affinity ligand; ten of the fragments could be competed, while seven showed less or no competition, suggesting that they may bind to an allosteric site.

 

GPCRs biology is complicated, and just because a ligand binds does not mean it will have any effect on signaling. In cell experiments, none of the fragments behaved as agonists, but five fragments could act as antagonists of a known agonist. Another fragment seemed to increase the signal, suggesting it is an allosteric modulator. As the researchers conclude, “while SPR can screen fragment-like molecules that allow for extrapolation of extremely large and diverse chemical spaces, it cannot predict the biological activity of these binders."

 

Nonetheless, this paper provides a nice guide on how to use SPR, with its low protein requirements, to screen GPCRs. And the fragments disclosed could be interesting starting points for medicinal chemistry.

Fragments in the clinic: HTL9936

Of the 50+ fragment-derived drugs that have entered the clinic, only two (both from Sosei Heptares) target transmembrane proteins, reflecting the difficulty of structure-based design for this hard-to-crystallize class of proteins. The story behind one of them was published late last year in Cell by Malcom Weir, Andrew Tobin, and a large group of collaborators.

 

The researchers were interested in the M1 muscarinic acetylcholine receptor, which is involved in memory and learning. By activating the receptor the hope is to be able to treat symptoms associated with Alzheimer’s disease. The M1 receptor has been a long-standing target for this disease, but previous drugs have caused side effects ranging from salivation and sweating to gastrointestinal distress and seizures. The M1 receptor is one of five closely related subtypes, and some of the side effects have been attributed to hitting the M2 and M3 receptors. However, the M1 receptor itself may also not be entirely innocent, so the goal was to develop a partial agonist, the idea being that this may be more effective in the brain, where the M1 receptor is highly expressed, while sparing other tissues where the M1 receptor is rarer.

 

The campaign began with a virtual screen of 1.6 million molecules (with molecular weights up to 400 Da) against a homology model of the human M1 receptor bound to a known agonist. This led to the purchase of 322 compounds, of which 16 were active in a cell-based functional assay, including compound 4. Fragment growing led to compound 6 and ultimately to HTL9936, which is selective for M1 over M2, M3, and M4 receptors. It also showed no significant agonism against a panel of 62 GPCRs even at 10 µM concentration.

 

Sosei Heptares pioneered the use of mutagenesis to stabilize specific conformational states of GPCRs, and this process was used to produce co-crystals with HTL9936 to understand its binding mode. Like other reported agonists, which were also characterized crystallographically, HTL9936 binds in the orthosteric site of the M1 receptor, but the increased size of the homopiperidine ring relative to other ligands provides selectivity over other receptors such as M2.

 

HTL9936 was tested in mice, rats, dogs, and cynomolgus monkeys, and in general showed good safety and brain penetration. The molecule even showed cognitive benefits in a mouse model of neurodegeneration and in aged beagles. It did cause an increase in heart rate and blood pressure in dogs, and there was a single convulsive episode, but only at a very high dose.

 

The paper also summarizes the results of human clinical trials which demonstrated that HTL9936 is well tolerated up to 100 mg doses, though at higher doses sweating, salivation, and changes in heart rate and blood pressure were observed. A small trial in healthy elderly people did not show any improvement in memory tasks, though functional magnetic resonance imaging studies did show that the molecule activated regions of the brain associated with cognition.

 

And that’s where the story ends. The Sosei Heptares website does not list HTL9936, though a different M1 receptor agonist (HTL0018318) is described. This paper also illustrates the long gap that can occur between research and publication: ClinicalTrials.gov lists three Phase 1 studies for HTL0009936, one of which began in 2013, and all of which ended by early 2017. Like most approaches to Alzheimer’s disease that have been tested, perhaps targeting the M1 receptor is a dead end. But reaching that conclusion requires highly selective chemical probes. Kudos to the team at Sosei Hetpares for their efforts.

Selective fragments vs GPCRs, guided by modeling

Earlier this year we highlighted a fragment optimization success story against a G protein-coupled receptor (GPCR) which made no use of structural information. Due to the difficulty of crystallizing these membrane-bound proteins, structures have been rare for this large class of drug targets. Advances in crystallography are starting to change that. In a recent open-access Chem. Commun. paper, Jens Carlsson and collaborators at Uppsala University and the US National Institutes of Health make use of the increasing availability of such structures to develop potent, selective inhibitors.

 

The researchers were interested in A₁ and A_2A adenosine receptors (A₁AR and A_2AAR), targets for a variety of ailments from cancer to cardiovascular diseases. (A_2AAR was the subject of this blog post a few months ago.) In the current study, the researchers wanted to know whether structures and molecular dynamics (MD) simulations could guide production of selective inhibitors.

 

Previous computational and experimental work from the authors had yielded compound 1, with low micromolar activity against A₁AR and 7-fold selectivity over A_2AAR. Crystal structures of both these proteins are available, though not bound to the small molecule. Docking studies suggested that the ligand would make similar interactions to both proteins, but that there might be an opportunity for increased selectivity towards A₁AR due to the presence of a smaller threonine residue compared with a methionine in A_2AAR. Nine analogs were designed to grow into this lipophilic pocket, and free energy perturbation and MD simulations suggested that they would have improved affinity for A₁AR. This turned out to be the case when the molecules were made and tested in radioligand binding assays.

 

Although compounds 5 and 9 were more potent, selectivity was not improved. MD simulations suggested this might be due to the small size of the fragments, which could be accommodated in A_2AAR by slight shifts in the binding modes. To try to anchor compounds within the pocket, the researchers grew off the phenyl ring, leading to molecules such as compound 15. Borrowing from this molecule and compound 9 led to compound 22, the most potent and selective molecule in the series. (A separate effort led to a somewhat weaker but A_2AAR-selective ligand.) Both molecules were found to be antagonists when tested in cells, which was expected given that the crystal structures used for modeling were in the inactive conformation.

 

The correlation between predicted and measured binding energies was respectable, with a mean unsigned error (MUE) of 1.08 kcal/mol and Spearman’s rank correlation coefficient (ρ) of 0.8 for 24 compounds. Selectivity predictions were also impressive at MUE = 0.48 kcal/mol and ρ = 0.85.

 

This is a nice illustration of using computational methods to improve the affinity of a fragment by more than three orders of magnitude while also increasing selectivity. This particular system is probably on the easier side; we blogged about previous research from this group on A_2AAR back in 2013. The researchers note that proteins with larger binding sites and weaker ligands are likely to be more challenging. It will be fun to see efforts towards Class B GPCRs, for example.

A minimal fragment library for maximal coverage of pharmacophore space

Last week we described a fragment library built with the aid of machine learning and designed to contain privileged fragments that should produce high hit rates. Unfortunately, only about a tenth of the library members are commercially available, so it will be some time before we know whether the design was successful. We continue the theme of fragment libraries with a just published Nat. Commun. paper by György Keserű (Hungarian Research Centre for Natural Sciences) and a large group of multinational collaborators (see also here for a nice summary by György).

 

The researchers started by analyzing more than 3300 crystal structures of protein-fragment complexes in the protein data bank. Fragments were defined as having 10-16 non-hydrogen atoms, and the computational approach FTMap was used to ensure that fragments were binding at hotspots as opposed to spurious, less ligandable sites. This exercise yielded 3584 fragments, but many of them were identical or very similar to one another. The researchers used a series of computational tools to cluster similar fragments (or pharmacophores) and choose a set that would maximize diversity. This ultimately led them to assemble a library of just 96 fragments, purchased from five vendors.

 

This SpotXplorer0 library mostly follows the rule of three, with 7 to 17 non-hydrogen atoms, MW 100-250 (or 280 for bromine-containing molecules), ≤ 3 hydrogen bond donors, ≤ 8 hydrogen bond acceptors, and ≤ 3 rotatable bonds. In addition, all members have 1-3 rings, no more than a single halogen or sulfur atom, and no PAINS. Despite the small size, this library covers most of the pharmacophores identified in the larger set, and considerably more than the F2X-Entry fragment library we highlighted last year or the top five commercial library vendors we noted here.

 

The researchers then screened this library against eight targets. Three GPCRs (the serotonin receptors 5-HT_1A, 5-HT₆, and 5-HT₇) were assessed in a cell-based radioligand displacement assay with fragments at just 10 µM. Despite the low concentration, 4-11 hits were found. Biochemical screens conducted at 800 µM against the proteases thrombin and Factor Xa yielded 7 and 8 hits respectively. Further analysis revealed that the SpotXplorer0 ligands sampled a majority of the pharmacophores found in published fragment hits against theses five targets.

 

Next the researchers screened their library against the histone methyltransferase SETD2, an oncology target with few known attractive ligands. An enzymatic assay yielded two hits, with IC₅₀ values between 300 and 500 µM.

 

Finally, the SpotXplorer0 library was part of the XChem crystallographic screens against the SARS-CoV-2 main protease (M^pro) and Nsp3 macrodomain, which we discussed here and here. For M^pro, just a single hit was found. This is only half the overall hit rate for noncovalent fragments in the crystallographic screen against this target, but the hit is functionally active and has a high ligand efficiency.

 

The screen against NSP3 yielded five hits binding at two different sites, for a hit rate of 5.2%. The overall hit rate against this target was 8%, but that encompasses screens against two crystal forms of the protein. The crystal form used for SpotXplorer0 had a hit rate of 21%.

 

In summary, SpotXplorer0 is new fragment library that gives high coverage of experimental pharmacophore space. Laudably, structures of all 96 fragments are provided in the Supplementary Information. But the jury remains out on how hit-rich the library will be. Interestingly, the F2X-Entry library we highlighted last year gave considerably higher hit rates of 21% and 30%, albeit against two different targets. SpotXplorer0 is being screened crystallographically against multiple targets at XChem, and it will be interesting to see how it performs in the long run.

Advancing fragments without structures: NPBWR1

Last week’s post highlighted how biophysical methods, and in particular structural insights, can be critical for advancing fragments to leads. But while everyone likes a structure, one quarter of respondents to our 2017 poll said they were comfortable optimizing fragments on the basis of SAR alone. (See also a recent review.) A new example of structure-free optimization has been published in Bioorg. Med. Chem. Lett. by Remond Moningka and colleagues at Merck.

 

The researchers were interested in the GPCR neuropeptide B/W receptor subtype 1 (NPBWR1, also known as GPR7), a potential target for obesity. Although impressive advances have been made towards obtaining structural information on membrane-bound proteins such as GPCRs, especially using cryo-EM, routine structure-based design is generally not an option.

 

The researchers started with a 30,000 member library of fragments between 200-350 Da. Both the size of the library and the size of the fragments are on the large side compared to what is typically used. A cell-based screen (cAMP assay) at 100 µM yielded 500 hits that inhibited at least 30%. Counter-screening against an unrelated GPCR whittled down the number to 20, of which just 3 provided dose-responses. The low confirmed hit rate illustrates both the utility of a larger library as well as the number of false positives likely to arise in a cell assay.

 

SAR by catalog on compound 1 led to compound 2, and further SAR led to compound 3c, with low micromolar activity and good ligand efficiency. Replacing the nitro group with a more pharmaceutically acceptable trifluoromethyl group produced compound 10. It is worth noting that compound 10 is still fragment-sized yet is >300-fold more active than the initial hit. This is a useful reminder that one can often make significant improvements even before fragment growing. Finally, extensive SAR studies around the phenyl ring ultimately led to compound 21a, with low nanomolar activity.

 

The pharmacology around GPCRs can be complicated, and compound 21a turned out not to be a simple competitive (orthosteric) antagonist of NPBWR1. Rather, it seems to act as a negative allosteric modulator: it reduces the affinity of the natural ligand.

This is a concise success story of advancing a fragment in the absence of structural information. Does this mean we should not strive for structures? Heck no! Not only would structures likely facilitate faster and further improvements, they might explain the mechanism of action of the compounds. I, for one, would love to know where and how they bind.

 

But this paper is another reminder that you do not always need crystallography - or even a model -  to take a fragment to a lead.

Fifth NovAliX Biophysics in Drug Discovery Conference

Last week NovAliX held its biophysics meeting outside of Strasbourg for the first time. Naturally they chose Boston, one of the most European of US cities and a major hub of drug discovery. The event brought together 118 participants from 15 countries, roughly 80% from industry. Although the food and drink could not compare to France, the science and discussion were every bit as satisfying. With 30 talks and 22 posters I won’t attempt to be comprehensive, but as with last year just try to capture a few themes. 

One particularly noteworthy session was devoted to single particle cryo-electron microscopy (cryo-EM), which was recently reviewed in Nat. Rev. Drug Discov. by conference chairman Jean-Paul Renaud and a multinational team of experts. The approach involves flash-freezing a thin film of sample and using transmission electron microscopy to capture two-dimensional “projection” images of your target. If the protein is randomly oriented you can computationally combine thousands of individual images into a three dimensional structure. Although the technique has been around for decades, until recently the resolution was too low to be useful for structure-based drug design. Recent advances in hardware and computation have led to what’s come to be known as the “resolution revolution,” explained Gabe Lander (Scripps).

One advance is the 300 keV Titan Krios – a massive (and massively expensive) instrument that is so widely coveted that Gabe showed pictures of happy scientists hugging newly delivered crates. Indeed, of the ~1000 structures solved to < 4 Å resolution, the vast majority of them were solved on one of more than 130 Krios instruments throughout the world. But Gabe showed that high resolution structures can be obtained with more common 200 keV instruments, including a 2.6 Å resolution structure of aldolase (150 kD), a 2.9 Å structure of hemoglobin (64 kD), and a 2.9 Å resolution structure of alcohol dehydrogenase (81 kD) with bound NAD⁺ cofactor. Although only a handful of sub-2 Å structures have been reported, he thought these would become routine in the next few years.

Bridget Carragher (New York Structural Biology Center) described challenges and how to overcome them. Currently it takes at best eight hours to go from data to structure, but she thought getting this to under one hour would be achievable. Moreover, cryo-EM can be used to characterize different conformational or oligomeric states present in a single sample, as Giovanna Scapin (Merck) demonstrated with insulin binding to its receptor. Indeed, even simple visualization – without fancy computational processing – can provide useful information about protein aggregation, as demonstrated by Wen-ti Liu (NovAliX).

Although primary fragment screening still looks a long way off for cryo-EM, it should start to provide useful structural information for fragments bound to targets less amenable to conventional biophysical techniques, such as membrane proteins – the topic of another session.

Miles Congreve (Heptares) discussed how their stabilized “StaR” GPCRs can provide high-resolution crystal structures suitable for FBDD (see for example here). This has allowed them to discover less lipophilic, more ligand-efficient drug candidates against a variety of targets.

According to Anass Jawhari, it isn’t even necessary to make mutant GPCRs: Calixar has developed proprietary detergents that can stabilize full length adenosine A_2A receptor for a week – more than enough time to perform STD NMR screens of 100 fragments and identify 19 hits, some of which turned out to be functional antagonists. Matthew Eddy (University of Southern California) used two-dimensional NMR on this same protein to reveal dramatic differences in conformational dynamics when bound to agonists vs antagonists.

Indeed, conformational changes and dynamics were a running theme throughout the conference. Keynote speaker and Nobel-laureate Martin Karplus (Harvard) quoted fellow Nobelist Richard Feynman: “everything that living things do can be understood in terms of the jiggling and wiggling of atoms.” (As an aside, Martin’s MCSS method pioneered computational FBDD approaches, predating SAR by NMR.) Göran Dahl (AstraZeneca) described how large scale conformation changes well outside of the active site of PI3Kgamma were responsible for freakishly high selectivity of a class of inhibitors.

But how do you detect conformational changes? We’ve previously mentioned Biodesy’s SHG approach, and Parag Sahasrabudhe (Pfizer) described how this proved useful for classifying ligands for IL-17A. Gerrit Sitters (Lumicks) described a completely different “dynamic single-molecule” (DSM) approach, which involves trapping a single fluorescently labeled protein between DNA strands tethered to two microspheres. Changes in protein conformation caused by ligand binding change the distance between microspheres, and these can be detected to within 1 Å.

Kinetics is intimately linked to dynamics, but the factors responsible for slow binding and dissociation are still poorly understood. Chaohong Sun (AbbVie) examined an archive of 8000 data points and found that on-rates and off-rates each varied by more than five orders of magnitude. There was no correlation with ClogP of the ligands, though larger ligands were more likely to have slower kinetics. There were also significant target effects; on-rates were consistently slow for one target.

As we’ve previously discussed, off-rate screening (ORS) can be used to identify hits in crude reaction mixtures, and Menachem Gunzburg (Monash University) described how this technique is being used in hit-to-lead efforts. Lowering the temperature to 4 °C and adding 5% glycerol further slows dissociation, allowing weaker hits to be discovered.

At the extreme, irreversible inhibitors have an off-rate of 0, and Gregory Craven (Imperial College London) described quantitative irreversible tethering of electrophilic fragments to cysteine residues in proteins using a fluorimetric plate-based assay. As we’ve noted, one challenge with irreversible tethering is deconvoluting intrinsic reactivity from proximity-directed reactivity, which Gregory addresses using a reference thiol such as glutathione.

There is much more to say but in the interest of time I’ll stop here. If you missed the conference you have two chances next year: June 4-7 when it returns to Strasbourg, and November 20-22 when it will be held in Kyoto. And there are still excellent events coming up this year – hope to see you at one!

Acceptable tradeoffs: From fragment hit to fragment lead against mGluR2, without structures

Membrane-bound proteins such as GPCRs are often ignored by practitioners of FBLD in part because – Heptares notwithstanding – they are usually difficult to characterize structurally. This seems like a missed opportunity. A large fraction of drugs target GPCRs, and the vast majority of these were developed without crystallographic information, so why is the fragment community so fixated on structure? A paper just published in J. Med. Chem. by György Szabó, György Keserű and colleagues at Gedeon Richter, the Hungarian Academy of Sciences, and Mitsubishisi Tanabe shows how much can be done without strcutures.

The researchers were interested in metabotropic glutamate receptor 2 (mGluR2), a popular target for schizophrenia. In particular, they sought positive allosteric modulators (PAMs), which act outside the main ligand binding site to enhance signaling. A functional screen yielded compound 4 as a fairly potent fragment-sized hit. Comparison with other larger reported inhibitors suggested growing could be productive, leading to molecules such as compound 5, with sub-micromolar activity. Further optimization for potency and ADME properties led to compound 29, with low nanomolar potency.

Unfortunately, this molecule is very lipophilic (cLogP > 5), resulting in poor solubility, high plasma protein binding, and thus limited efficacy in a mouse pharmacodynamic model. All attempts to reduce lipophilicity came at the cost of potency.

To determine which elements of compound 29 were most important for binding, the researchers turned to group efficiency analyses; that is, they systematically removed different chemical groups and weighed the loss in binding energy versus the reduction in size. Even though they could not visualize precisely how each group interacted with mGluR2, the researchers could measure it. This effort revealed that the biaryl moiety was not particularly efficient, and although trimming it came at a cost in potency, this was compensated for by improved ligand efficiency. Substitution at another position off the initial fragment led to a satisfying boost in activity (compound 30). Further optimization for pharmacokinetic properties led to the fragment-sized compound 60, which is considerably less potent in vitro than compound 29 but which has better brain penetration and also better efficacy in two mouse models.

Several lessons can be drawn from this story. First, as Mike Hann warned seven years ago, molecular properties should not be ignored in the push for potency. Indeed, despite the 25-fold decrease in potency for compound 60 compared with compound 29, the smaller molecule is more effective in vivo. This is reminiscent of the Merck verubecestat story, which also involved optimization of a fragment hit to a potent but lipophilic lead that was ultimately abandoned in favor of an initially less active but more ligand-efficient series. The second lesson is that in vitro models can only take you so far. And finally, creative chemists are able to advance fragments even in the absence of structural information. Hopefully more of them will give it a try.

Fragments vs GPCRs – virtually vs experimentally

G protein-coupled receptors (GPCRs) are common drug targets that present challenges for fragment-based approaches. Biophysical studies of these membrane proteins are often difficult. Moreover, while many fragment-finding methods reveal binders, GPCR ligands can be agonists, inverse agonists, neutral antagonists, and more – and directing a search toward desired functionality can be tough (though see here). In a paper published earlier this year in Bioorg. Med. Chem. György Keserü and colleagues at Gedeon Richter and the Hungarian Academy of Sciences describe how they have tackled this problem.

The researchers were interested in the adrenergic α_2C receptor; agonists could be useful for a variety of indications, though selectivity is challenging. No crystal structure has been reported in the literature, so the researchers investigated a radioligand displacement assay as well as a cell-based functional assay (calcium mobilization) for agonists. A test set of 160 fragments from Maybridge was screened in both assays at 250 µM, giving 3 hits in the functional assay but a whopping 48 hits in the displacement assay. A 30% hit rate in an unbiased screen generally means something’s wrong, so the researchers chose to focus on the functional assay.

For the full screen, 3071 fragments having 9-22 non-heavy atoms were tested at 250 µM in the cell-based functional assay, resulting in 318 hits – a much higher rate than the initial set. However, when these were retested, only 86 reproduced, which the researchers attribute to variability in the cell-based assay. Many of the hits were also active against an unrelated GPCR; ultimately 16 were specific for the α_2C receptor and were also active in the radioligand displacement assay (as was one of the three original Maybridge hits). The chemical structures and activities of these molecules are shown in the paper; they are all quite potent with inhibition constants from 2-220 nM in the displacement assay, with correspondingly high ligand efficiency scores.

Despite the lack of a crystal structure, the researchers also performed a virtual screen of the same set of 3071 fragments using a homology model of the α_2C receptor. Two of the top 30 hits were fragments that had been discovered in the functional assay. Although this is not as impressive as another docking study on a different GPCR, it is certainly better than chance, and not too shabby considering the lack of an actual structure for the protein.

Next, the researchers attempted to find more potent analogs by testing compounds chemically related to their best hits. Some of these did show good potency in the radioligand displacement assay, but interestingly all of these were antagonists as opposed to the desired agonists. This is further evidence that gaining affinity may be easier than maintaining functionality.

As the authors concede (and we’ve noted elsewhere), the α_2C receptor has evolved to bind fragment-sized ligands. Still, the computational discovery of agonists is encouraging. It will be interesting to see whether such approaches will work against more difficult targets, such as peptidergic GPCRs.

Uninteresting GPCR Fragment Work...meant as a Compliment!!

There are certain movies that when they are on TV, I can't not watch.  I call these Broken Leg Movies (as in if I were laid up with a broken leg what would I watch).  As I have said, Road House is one, Apollo 13 another.  Its about America's blase attitude towards the amazing feat of putting men on the moon.  It takes a potential horrific tragedy (For those off you who haven't seen it, let me say (**Spoiler Alert**) don't worry it has a happy ending.) in order for America to care about men in space.  Which of course is in direct contrast to Pigs in Space (with Swedish Subtitles)! 

One of the field changing technologies is Heptares' STAR technology (for creating stabilized, soluble GPCRs).   We have discussed it often on this blog.  Well, they are back with another paper, this time working the voodoo they do so well on a Class C GPCR.  Negative allosteric modulation of the mGluR has the potential for significant medical impact in a variety of diseases.  In a relatively well trod drug space (there have been several molecules in late stage trials), an issue appears to be the acetylenic moiety in these drugs (which appears to be manageable).  So, non-acetylenic molecules would be desireable.  

To attempt to ligand this molecule, they screened 3600 non-acetylenic fragments using a radio-labeled assay.  This is in contrast to previous work where they used SPR. From this screen, 178 fragments were tested in concentration-response curves leading to "a number of promising" hits, including the compound shown below. 

Cpd 5.  pKi=5.6, LE=0.36

This compound was advanced using the tools you would expect (especially from Heptares): modeling, X-ray crystallography, medchem, and so on.  The final molecule is an advanced lead with excellent mGluR selectivity and in vivo activity, clean tox, and so on. 

This is excellent work, but "yawn".  I think it might be interesting to hear why they went with the radioligand approach, as opposed to SPR.  You could quibble that 5 is too big to be a fragment, but really?  Papers like this are uninteresting, we know its going to work.  The science is excellent, but I want to see the triumph out of tragedy.  Not here.  I want to congratulate Heptares for making an achievement like this paper perfectly uninteresting.  And I mean uninteresting as the very best of compliments. 

Fragment-Based Drug Discovery

This is the straight-to-the-point title of a new book published by the Royal Society of Chemistry, edited by Steven Howard (Astex) and Chris Abell (University of Cambridge). It is the second book on the topic published so far this year, and it is a testimony to the fecundity of the field that the two volumes have very little overlap.

After a brief forward by Harren Jhoti (Astex) and a preface by the editors, the book opens with two personal essays. The first, by me, is something of an apologia for Practical Fragments and the growing role of social media in science (and vice versa). If you’ve ever wondered how this blog got started or why it keeps going, this is where to find out. The second essay is by Martin Drysdale (Beatson Institute). Martin is a long-time practitioner of FBDD, dating back to his early days at Vernalis (when it was RiboTargets) and he tells a fun tale of “adventures and experiences.”

Chapter 1, by Chris Abell and Claudio Dagostin, is entitled “Different Flavours of Fragments.” With a broad overview of the field it makes a good introduction to the book. There are sections on fragment identification, including the idea of a screening cascade, as well as several case studies, some of which we’ve covered on Practical Fragments, including pantothenate synthetase, CYPs, RAD51, and riboswitches.

The next two chapters deal with two of the key fragment-finding methods. Chapter 2, by Tony Giannetti and collaborators at Genentech, GlaxoSmithKline, and SensiQ, covers surface plasmon resonance (SPR). This includes an extensive discussion of data processing and analysis, which is critical for improving the efficiency of the technique. Competition studies are also described, as are advances in hardware, notably those from SensiQ. This is a good complement to Tony's 2011 chapter.

Chapter 3, by Isabelle Krimm (Université de Lyon), provides a thorough description of NMR methods, both ligand-based (STD, WaterLOGSY, ILOE, etc) and protein-based (mostly HSQC). The chapter does a nice job of describing techniques in terms a non-specialist can understand while also providing practical tips on matters such as optimal protein size and concentration.

Chapter 4, by Ian Wall and colleagues at GlaxoSmithKline, provides an overview of FBLD from the viewpoint of computational chemists. The chapter includes some interesting tidbits, such as the observation that fragment hits that yield crystal structures tend to be less lipophilic but also contain a smaller fraction of sp³ atoms and more aromatic rings. The researchers note that the current fashion for “3D” fragments is yet to be experimentally validated. They also include accessible sections on modeling, druggability, and integrating fragment information into a broader medicinal chemistry program.

The remaining chapters focus on specific types of targets. Chapter 5, by Miles Congreve and Robert Cooke (both at Heptares) is devoted to G protein-coupled receptors (GPCRs). This includes descriptions of how to screen fragments against these membrane proteins using SPR, TINS, CE, thermal melts, and competition binding. It also includes a detailed case study of their β1 adrenergic receptor work (summarized here). Congreve and Cooke assert that, although many of the GPCR targets screened to date have been highly ligandable, technical challenges only now being addressed have caused this area of research to lag about a decade behind other targets. They predict a bright future.

Rod Hubbard (Vernalis and University of York) turns to protein-protein interactions in Chapter 6. After describing why these tend to be more challenging than most enzymes and covering some of the methods for finding and advancing fragments, he then presents several case studies, including FKBP (one of the first targets screened using SAR by NMR), Bcl-2 family members (including Bcl-x_L and Mcl-1), Ras, and BRCA2/RAD51. He concludes with a nice section on “general lessons,” which boils down to “patience, pragmatism, and integration.” As Teddy recently noted, this can lead to substantial rewards.

Allosteric ligands have potential advantages in terms of selectivity and addressing otherwise challenging targets, and in Chapter 7 Steven Howard (Astex) describes how fragments can play a role here. This includes how to establish functionality of putative allosteric binders, as well as case studies such as HIV-1 RT, FPPS, and HCV NS3. Astex researchers have recently stated that they find on average more than two ligand binding sites per protein, and this chapter includes a table listing these (including 5 binding sites each on bPKA-PKB and PKM2).

The longest chapter, by Christina Spry (Australian National University) and Anthony Coyne (University of Cambridge) describes fragment-based discovery of antibacterial compounds. After discussing some of the challenges, the authors report several in depth case studies including DNA gyrase, DNA ligase, CTX-M, AmpC, CYP121, and pantothenate synthetase, among others. At least one fragment-derived antibacterial agent entered the clinic; hopefully more will follow.

Chapter 9, by Iwan de Esch and colleagues at VU University Amsterdam, focuses on acetylcholine-binding proteins (AChBPs), both as surrogates for membrane-bound acetylcholine receptors and as well-behaved model proteins on which to hone techniques (see for example here, here, and here). Since AChBPs have evolved to bind fragment-sized acetylcholine, these proteins can bind tightly to small ligands; 14-atom epibatidine binds with picomolar affinity, for example, with a ligand efficiency approaching 1 kcal mol^-1 atom^-1.

And Chapter 10, by Chun-wa Chung and Paul Bamborough at GlaxoSmithKline, concisely covers epigenetics. Bromodomains are well-represented, including a table of ten examples (see for example here, here, here, here, here, and here). Happily, although some of these projects started from similar or identical fragments, the final molecules are quite divergent. However, the authors note that much less has been published on histone-modifying enzymes, such as demethylases and deacetylases, perhaps reflecting the challenges of achieving specificity with what are often metalloenzymes.

Finally, this is the 500^th post since Teddy founded Practical Fragments way back in the summer of 2008. Thanks for reading, and special thanks for commenting!

Heptares Get Bought

Yesterday brought news that Heptares was purchased by Sosei.  The deal is for 180$MM upfront and 220$MM in royalties.  Similar to the Astex deal, Sosei is not absorbing Heptares, but is keeping them as a wholly owned subsidiary.  In terms of clinical assets, Heptares didn't show up on the 2015 version of fragments in the clinic, but they do have a p1 asset, a M1 agonist.  As if we needed further validation, this deal shows the power of SBDD/FBDD and gives a good idea off how it is valued.  Congratulations to our friends at Heptares.

Review of 2014 reviews

The year is spinning to an end, and as we did in 2013 and 2012, Practical Fragments is looking back on notable events as well as reviews we didn’t cover previously.

2014 was full of conferences, starting with the CHI meeting in San Diego (here and here), moving to the Zing conference in the Dominican Republic, on to the Fall ACS meeting in beautiful San Francisco, and ending with FBLD 2014 in Basel.

In terms of reviews relevant to the fragment community, John Christopher and colleagues at Heptares published an extensive analysis of “Structure-based and fragment-based GPCR drug discovery” in ChemMedChem early in 2014. The last few years have seen an efflorescence of new structural information on G protein-coupled receptors, and this paper provides a thorough compilation of crystal structures and small molecule ligands. The review also discusses methods that have been used to discover fragments that bind to GPCRs, including TINS, SPR, CEfrag, radioligand binding, and fluorescence assays, and ends with case studies on A_2A antagonists and β₁AR ligands.

In contrast to GPCRs, kinases represent a well-established target class for fragment-based drug discovery, as exemplified by the first approved drug, vemurafenib. Structural biology has played a major role in this success; more than 200 of the 518 human kinases have had their X-ray crystal structures determined, and more than 3000 protein kinase structures have been deposited in the protein data bank. Astex has put several kinase inhibitors into the clinic, and in Methods in Enzymology Paul Mortenson and colleagues from the company discuss the state of the art. This is a clear and concise review of fragment-based drug discovery in general and as specifically applied to kinases. It serves as an excellent introduction to the topic.

Any chemist who has worked on kinases will be familiar with azaindoles, and in Molecules, Sylvain Routier and colleagues at Université d’Orléans discuss “the azaindole framework in the design of kinase inhibitors.” This provides a thorough compilation of azaindole inhibitors against ALK, Aurora, Cdc7, CHK1, C-Met, DYRK1A, FAK, IKK2, JAK2, KIT/FMS, PAK1, p38α, PIM1, B-Raf, ROCK, m-TOR, and TrkA, replete with synthetic methods. The paper also includes a nice analysis of binding modes. Of the 58 crystal structures of azaindoles bound to kinases in the protein data bank, the majority (48) are with 7-azaindole rather than the three other positional isomers. This isomer (found in vemurafenib) is also over-represented in the patent literature and among commercial compounds.

Another target that has yielded to FBLD is BACE1, a hot but still controversial target for Alzheimer’s disease, and in Bioorg. Med. Chem. Lett. Daniel Oehlrich and colleagues at Janssen review “the evolution of amidine-based brain penetrant BACE1 inhibitors”. This is very much a medicinal chemist’s review, with over 100 chemical structures, including a nice summary of the various chemotypes used by different companies. The authors do an excellent job synthesizing a tremendous amount of data, much of it reported only in the patent literature, and engage in some intriguing chemical sleuthing to guess at the identity of clinical candidates whose structures have not been publicly disclosed, such as MK-8931.

Jia Zhou and collaborators at the University of Texas Galveston and Fuzhou University discuss “Evolutions in fragment-based drug design: the deconstruction-reconstruction approach” in Drug Discovery Today. After briefly describing fragment-finding methods and library design, the review focuses on deconstruction of known ligands to generate “privileged” fragments that are then reassembled into new molecules. Although this approach can be productive, if one doesn’t exclude PAINS the result can be garbage-in, garbage-out.

Finally, in Methods in Enzymology, Katherine Warner (National Heart, Lung and Blood Institute) and Adrian Ferré-D’Amaré (University of Cambridge) review the crystallographic analysis of fragments binding to the TPP riboswitch. This is a concise how-to guide, and the methodology could be applicable to other RNA targets.

And with that, Practical Fragments says farewell to 2014. Thanks for reading, and may the New Year bring wonderful new discoveries!

Progress in Biophysics and Molecular Biology special issue

The latest issue of Prog. Biophys. Mol. Biol. includes five articles on fragment-related topics. We already discussed one from Astex; brief summaries of the rest follow.

Eddy Arnold (who has an editorial introducing the articles) and colleagues from Rutgers University discuss the advantages of screening fragments crystallographically. Regular readers of this blog will likely be familiar with some of the material, but there is lots of practical advice on fragment cocktail design (that is, choosing which fragments to mix together), optimization of soaking, high-throughput crystallography, and related topics. There is also a nice example of an “unknown known,” where the apparent activity of a compound turned out to be due to contaminating metal.

David Dias (University of Cambridge) and Alessio Ciulli (University of Dundee) have a piece on using NMR in structure-based lead discovery, with a heavy focus on large multi-protein complexes. They succinctly review both ligand-based and protein-based NMR methods and then discuss how these techniques can help determine ligand conformations and binding sites. Next, they discuss how to tackle high molecular weight protein assemblies or protein-protein complexes, often by using clever isotopic labeling strategies. The figures throughout are particularly effective at showing what kinds of information can be obtained from the various techniques.

Andrew Hopkins (University of Dundee) and colleagues are up next with “Fragment screening by SPR and advanced application to GPCRs”. Surface plasmon resonance, of course, is a mainstay of fragment screening, and this is a timely how-to guide by some of the experts in the field. As the title suggests, a major focus is on GPCRs, a class of membrane proteins only recently targeted by fragments. There are some good practical tips on protein immobilization, screening, and weeding out false positives. My sense is that screening GPCRs by SPR remains challenging; most of the fragment libraries screened tend to be small (no more than a few hundred compounds), and sensitivity seems to be an issue, with most of the hits being quite potent by the standards of FBLD (low micromolar or better).

Finally, Theresa Tiefenbrunn and C. David Stout (Scripps) lead us “Towards novel therapeutics for HIV through fragment-based screening and drug design.” Practical Fragments has highlighted fragment efforts against several targets for this virus, including HIV protease, HIV reverse transcriptase, HIV integrase, and TAR RNA; this paper discusses these and more. This is a thorough compilation of copious data and focuses heavily on fragment screening. Crystallography plays a starring role, but SPR and NMR are also prominent. In short, it shows practical applications of the prior papers, and so makes a nice conclusion to this series.

Ninth Annual Fragment-based Drug Discovery Meeting, Part 2

The first major fragment event of 2014 drew around 500 people to San Diego last week. This is part of CHI’s three-day Drug Discovery Chemistry conference, and although the official FBDD track was only one of six, it is a testimony to the vitality of the field that fragments made appearances in most of the other sessions. With 17 talks in the FBDD track alone this post will not attempt to be comprehensive; Teddy has already shared some impressions here.

Jim Wells (UCSF) gave a magisterial keynote address that emphasized how useful fragments can be for tackling difficult targets such as protein-protein interactions (PPIs). In fact, many of the talks in the protein-protein interaction track relied on fragments. That’s not to say it’s easy. Rod Hubbard (University of York and Vernalis) emphasized that advancing fragments to leads against such targets can take a long time and often requires patience that strains the management of many organizations. Fragment hits against PPIs usually have lower ligand efficiencies (0.23-0.25 kcal/mol/HA if you’re lucky), and improving potency can be a bear. Rhian Holvey (University of Cambridge) presented a nice example of how she was able to find millimolar fragments that bind to the anti-mitotic target TPX2, potentially blocking its interaction with importin-alpha, but even structural information was not enough to get to potent inhibitors.

G-protein coupled receptors (GPCRs) were thought to be unsuitable for fragments until recently, but both Iwan de Esch (whose work has been profiled several times, including here and here) and Jan Steyaert (Vrije University) presented success stories. In fact, Jan has only been working with the Maybridge fragment library for a few months, but has found agonists, antagonists, and inverse agonists for several GPCRs.

Another example of a difficult target is lactate dehydrogenase A (LDHA). We’ve previously highlighted cases where fragment linking was used to get to nanomolar binders (here and here); Mark Elban (GlaxoSmithKline) presented an example of fragment growing and using information from a high-throughput screen (HTS) to get to nanomolar binders. Mark also discussed a particularly disturbing false positive: HTS had generated dozens of confirmed hits spanning 7 chemotypes, but upon closer inspection it turned out that all of them came from a single vendor, and that – unreported by the vendor – they were all oxalate salts. Oxalate is a low micromolar inhibitor of LDHA, and is invisible in proton NMR, so I’m sure this was not fun to track down.

Ben Davis (Vernalis) also presented great examples of false positives and false negatives, and how to avoid them. In particular, the WaterLOGSY NMR technique is great for weeding out aggregators when run in the absence of protein.

A common theme throughout the conference was the integration of fragments with other methods, such as HTS. Nick Skelton (Genentech) actually titled his presentation “Fragment vs. HTS hits: does it have to be a competition?” Kate Ashton (Amgen) discussed how using information from a fragment screen helped solve pharmacokinetic issues with an HTS-derived hit. And Steven Taylor (Boehringer Ingelheim) presented a similar example (also covered here) of using fragments to fix a more advanced lead. Steven noted that fragment-based methods are now fully integrated into the organization, which marks a significant change from Sandy Farmer’s presentation at this meeting four years ago.

The roundtables are great opportunities to swap ideas and get feedback; Teddy already mentioned the excellent roundtable he chaired, but I wanted to also give a shout-out to one organized by Derek Cole (Takeda) focused on "practical aspects of fragment screening." We recently discussed discussed fragments that destabilize proteins in thermal shift assays, and it turns out that folks from both the Broad Institute and Takeda have also crystallographically characterized such fragments. There was the sense that either stabilizers or destabilizers should be considered hits, though the latter were less likely to lead to crystal structures than the former.

Finally, on the subject of library design, Damian Young (Baylor College of Medicine) described using diversity-oriented synthesis (DOS) to generate more “three-dimensional” fragments. He is planning to build a library of roughly 3000 fragments which he hopes to make widely available to the community; these should help answer the question of whether the third dimension is really an advantage.

The importance of library design was also emphasized by Valerio Berdini (Astex); they are currently on their seventh generation library, about 40% of which is non-commercial, and half of whose members have been solved in one or more of 6000+ crystal structures. Relevant to the rule of three, Astex is moving to ever smaller fragments, with an average of 12.6 non-hydrogen atoms, ClogP = 0.6, and MW = 179. Indeed, despite assertions that PPIs may require larger fragments, Rod noted that at Vernalis the average fragments hits against PPIs are only slightly larger (MW = 202 vs 189 against all targets) and more lipophilic (ClogP 1.2 vs 0.8).

CHI has already announced that next year’s meeting will be held in San Diego from April 21-23. As it will be the ten year anniversary, they’re planning something big, so put it on your calendar now!

Docking vs TINS on a GPCR

Practical Fragments has featured a number of posts comparing various fragment-finding methods. In some cases there is good agreement, while in others – not so much. Computational methods can in theory sample the greatest swath of diversity space: a virtual library can be orders of magnitude larger than any physical library. In a recent paper in J. Chem. Inf. Model. Gregg Siegal at ZoBio and Leiden University and Jens Carlsson at Stockhom University and their colleagues compare the performance of virtual screening with a biophysical method.

The target they chose, the A_2A adenosine receptor (A_2AAR) is a GPCR implicated in a variety of diseases. It also has the advantage of multiple published co-crystal structures with either agonists or antagonists bound, making it a good candidate for computational screening.

The researchers began by conducting a computational screen of 500 fragments using DOCK 3.6 against the crystal structure of an antagonist-bound A_2AAR and ranked these according to how well they scored. Next, the researchers physically screened the same library of 500 fragments against A_2AAR using an NMR-based screening method called TINS (see also here). This resulted in a whopping 94 primary hits, which were followed up in a radioligand displacement assay to yield 5 confirmed hits with K_i values ranging from 14-600 micromolar. Happily, 4 of the 5 hits from the TINS screen were within the top 5% scoring hits identified in silico.

This is satisfying at first glance, but what does it say about the other top-scoring computational hits? Computational screening virtually docks fragments in many possible positions, or poses, which are automatically evaluated. Manual inspection of the top 50 in silico hits showed that, in some cases, the best poses had desolvated polar groups, which would presumably be energetically unfavorable. Indeed, identifying the “correct” pose seems to be a general problem with docking fragments.

But some of the top-scoring fragments looked fine by visual inspection, so 5 of these were tested in a radioligand displacement assay. Surprisingly, 3 of these were active, with K_i values ranging from 18-128 micromolar. In other words, these were false negatives in the primary TINS assay.

Having found hits that had been missed using a biophysical screen, the researchers then docked 328,000 commercially available fragments against the target – an exercise that took only seven hours on a computer cluster. Of the top hits, 22 were purchased and tested in the radioligand displacement assay, and a remarkable 14 of these were active, with K_i values ranging from 2-240 micromolar. (I do wonder how much chemical intuition played a role in choosing hits to purchase.)

Interestingly, all of the 14 hits from docking had respectable ligand efficiencies (LE > 0.3 kcal/mol/atom, with a single exception). This is consistent with previous fragment docking studies that show that the best results are obtained with the most ligand-efficient fragments. It’s also a nice feature; after all, these are exactly the kind of hits you would hope to find, though of course you want to first filter out any garbage from your virtual library.

This paper provides more evidence that computational approaches can find fragment hits for GPCRs, at least relatively “druggable” ones with good structural characterization. It is also a useful reminder of the importance of using multiple methods, to avoid both false positives and false negatives.

Finally, if you haven't already voted on your fragment-finding methods, please do so on the right side of the page!