Vast fields of biologically active chemical space

Exactly 17 years ago, I highlighted a paper from Brian Shoichet’s lab in which he hypothesized that only tiny regions of chemical space are biologically relevant. If so, Practical Fragments quoted, “a major reason why the screening of synthetic compounds ever finds notable hits is that our libraries are biased toward the sort of molecules that proteins have evolved to recognize.” The best scientists continually question their assumptions, and this is exactly what Brian, Bryan Roth, and collaborators at University of California San Francisco and University of North Carolina at Chapel Hill have done in a new open-access J. Med. Chem. paper.

 

The idea that molecules more closely resembling metabolites and natural products would be more likely to be biologically active is reasonable given the promiscuity of many naturally occurring molecules. As the researchers point out, dopamine signals through 5 receptors, while serotonin binds to 14. Nature is the ultimate recycler, constantly reusing chemical motifs.

 

But since 2009 there has been a massive growth of make-on-demand libraries, and these have increasingly diverged from known molecules. Brian has been among the most prolific explorers of this new chemical space, and as he noted in his keynote at DDC 2026, these gargantuan libraries are yielding more hits against more targets.

 

Are these hits more selective? In other words, are molecules that are less “bio-like” likely to bind to fewer targets? This is the question the new paper addresses, focusing on the 5-HT_2A serotonin receptor (5-HT_2AR), the target for a variety of drugs including psychedelics. The researchers have extensively studied this GPCR; we wrote about a successful computational screen here. In the new paper, the researchers compared hits from a previous “make-on-demand” (MoD) library screen of 1.6 billion molecules with a new screen of 3.5 million “in-stock” molecules. As predicted, the in-stock compounds were much more bio-like than the MoD compounds as assessed by several metrics (Tanimoto similarity, Avalon fingerprints, and RDK7 fingerprints, for the cheminformatics aficionados among you).

 

Both libraries were computationally screened using DOCK3.8 against 5-HT_2AR. Of the top scoring hits, 85 molecules from the in-stock library and 384 molecules from the MoD library were tested in a radio-ligand displacement assay. Hit rates were nearly identical at around 24% each. Functional assays revealed the hits to be active, with some acting as agonists while others were antagonists.

 

When tested against related GPCRs, specifically 5-HT_2BR and 5-HT_2CR, the in-stock molecules were more promiscuous than the MoD molecules. But when tested against a panel of 318 GPCRs there were no differences: the in-stock molecules bound on average 1.7% of the receptors while the MoD molecules bound on average 2.1%. The similar promiscuity persisted even when focusing on the 55 aminergic GPCRs (5-HT_2AR is an aminergic GPCR). In fact, the most promiscuous compound of all came from the MoD set and is distinctly not bio-like.

 

Of course, this is just one study, but I suspect it will generalize. In 2009 I questioned whether biologically relevant chemical space is really so sparse. As I wrote then, “consider a vast field of some crop that can only be harvested by night. There are lights scattered haphazardly throughout the field. One might expect that the crops immediately under the lamp posts would be harvested more intensively than crops in darker parts of the field, even if other areas are equally productive. In this scenario, the lamp posts reveal natural products and similar molecules, but much – or even most – of (unlit) chemical space may also be biologically active, it just hasn’t been sampled yet.”

 

There is grandeur in this view of chemical space, which is supported by the new paper. Imagine yourself in the midst of the field on a moonless night. Turn on your headlamp and step forward in any direction. Drug leads glimmer as far as your light can reach.

Twenty-First Annual Fragment-Based Drug Discovery Meeting

Last week some 875 people attended the CHI Drug Discovery Chemistry (DDC) meeting in San Diego. I can’t do justice to the 40 or so presentations I attended over four days but can highlight some of the main themes.

 

Reversible fragments

Membrane targets such as G protein-coupled receptors (GPCRs) pose a challenge for biophysical methods, but three talks presented progress. Matthew Eddy (University of Florida Gainesville) described high-resolution magic angle spinning (HRMAS) NMR, which entails spinning isolated cellular membranes containing GPCRs at high speed (4 kHz!), which miraculously yields sharp NMR signals for bound ligands. Matthew demonstrated applications with the human adenosine A_2A receptor and weak (mM) ligands. He noted that the technique can work with native, poorly expressed proteins, though data collection times can be upwards of 30 minutes.

 

Kris Borzilleri described using ¹⁹F NMR to find ligands against an orphan GPCR at Pfizer. The 2287 fragments screened yielded 87 hits, of which 38 confirmed by SPR. SAR studies eventually yielded low micromolar ligands, but these were difficult to advance in the absence of structure (see here for a more successful example from Merck).

 

Vanessa Porkolab (Eurofins Cerep) described using the Nanotemper Spectral Shift technology to screen 826 fragments against the adenosine A_2A receptor at 300 µM, with a 9.2% hit rate. Many of these ligands stabilized the GPCR in a thermal shift assay and seven were even active (as antagonists) in a cellular assay.

 

Turning to soluble proteins, Paola Di Lello presented a case study from Genentech and Vernalis applying ligand-observed NMR to the protein phosphatase PTPN22. Subsequent protein-observed NMR revealed that most of the 16 validated hits bound to two pockets some distance from the active site. The fragments were optimized to mid-micromolar affinity but showed no functional activity.

 

And Charlotte Hodson presented the eIF4E story from Astex. As we discussed last year, this yielded a low nanomolar ligand that did not have the desired cellular effects. Charlotte noted that subsequent genetic experiments were consistent with the limited efficacy. Still, the target was sufficiently interesting that a chemical probe would have been pursued even knowing it would be high-risk.

 

Covalent ligands

Covalent approaches made appearances throughout the conference. Keriann Backus (UCLA) described chemoproteomic approaches to find cysteine-targeting ligands; she noted that gain of cysteine residues (such as G12C in KRAS) are the most common missense variants in cancer. Keriann also warned how covalent compounds can cause potentially misleading effects in cells, as she described in Nat. Chem. Biol. last year.

 

In 2021 we wrote about the SpotXplorer fragment library from György Keserű (Hungarian Research Centre for Natural Sciences). György has now prepared a PhotoXplorer library, which uses diazirine tags for photochemical screening, which we described here. The new library has produced high hit rates across a variety of targets. György also described a new sulfozone-based photoprobe that is easier to prepare than diazirines.

 

Kelly Craft recounted a DNA-encoded library (DEL) screen at AbbVie against the target BCL2A1, also known as BFL1. This produced an aldehyde-containing low micromolar binder that formed an imine with buried lysine 102. Uncomfortable progressing an aldehyde, the researchers sought to covalently engage cysteine 55, the same cysteine targeted by AstraZeneca, as we wrote about here. The progression included at least one dual-warhead molecule which was crystallographically confirmed to bind both the lysine and cysteine. The effort ultimately yielded cysteine-selective leads.

 

Earlier this year I described the dDRTC method we developed at Frontier Medicines for determining k_inact/K_I, and Svetlana Kholodar presented a nice overview of its scope and utility. My colleague Johannes Hermann spoke in more detail about our covalent technologies, particularly those using AI.

 

Chemical space and the exploration thereof

Brian Shoichet (UCSF) gave an entertaining and wide-ranging account of “directed and random walks in chemical space.” Brian has consistently been on the bleeding edge of high-throughput in silico screens, from 67,000 compounds in 2009 to 138 million molecules in 2019 to 4 billion molecules today. When docking artifacts are avoided (as we discussed here), bigger libraries consistently produce more potent hits for more targets – an observation strikingly consistent with Alex Shaginian’s in 2023 as HitGen expanded their DEL libraries from billions to more than a trillion molecules. Brian is developing methods to computationally screen the >4 trillion make-on-demand molecules now available from companies such as Enamine.

 

Direct-to-biology (DTB) approaches, which rely on microscale chemical reactions screened without purification, have become increasingly popular methods for exploring chemical space. Jack Sadowsky correctly stated that Carmot was the first company formed around this approach; we previously wrote about the role Chemotype Evolution played in the discovery of sotorasib. Jack described how Kimia, which spun out of Carmot, has continued to advance the technology, applying it to find inhibitors selective for single members of closely related kinase families.

 

Allan Jordan described how Sygnature Discovery is applying DTB in a variety of assays including microsome stability and crystallography. (We wrote about crude reaction screening by crystallography earlier this year.) Expanding beyond DTB, Allan called their platform direct-to-discovery, and discussed how it led to a preclinical candidate with STORM Therapeutics in just 18 months.

 

WuXi Apptec is also using DTB. Peichuan Zhang described starting with ligands derived from fragment and DEL screens against the E3 ligase GID4 to make PROTACs to degrade BRD4; DTB was used to explore a wide range of different linkers. And Daniel Blair (St. Jude) described using DTB and affinity selection-mass spectrometry (AS-MS) to find new molecular glues for the oncology target LCK.

 

Computers, DEL, and DTB are not the only way to explore chemical space. Last year we covered Tom Kodadek’s bead-based screening approach at University of Florida Scripps, and Tom presented two talks on the topic, one using macrocycles to find binders to difficult targets such as PTP1B and one using small molecules to find molecular glues.

 

Speaking of PROTACs and glues, plenary keynote speaker Alessio Ciulli (University of Dundee) discussed the “evolution and future of targeted protein degradation.” Alessio noted that there are >25 PROTAC degraders and >10 glues in the clinic, though these collectively target only a small number of E3 ligands, so there is plenty of opportunity for the area to expand.

 

For many of us in industry, drugs represent the most privileged points in chemical space, and these often look quite different than we assume, as Dean Brown (Jnana) noted in his recent analysis of 104 oral small molecule drugs approved by the FDA from 2020 to 2024 (which we mentioned here). Some drugs contain eye-raising moieties such as acetylenes, styrenes, N-O bonds, and nitro groups. Indeed, it is worth remembering that venetoclax, arguably the most successful fragment-derived drug, sports a nitro group.

 

But before getting too complacent, Jonathan Baell (Manas) warned about frequent hitters in libraries of FDA-approved drugs. He notes in Eur. J. Med. Chem. earlier this year that many commercial libraries are actually enriched for molecules that cause spurious biological activity. Jonathan calls on library vendors to remove particularly egregious compounds, though I’d settle for world peace.

 

I’ll close on that pleasant thought, but please feel free to comment. I hope to see you in San Diego next year April 19-22 for the twenty-second iteration of DDC.

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.

RSC Medicinal Chemistry special FBDD issue

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

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.

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.

Affinity mass spectrometry-based fragment screening

Among the many methods to find fragments, affinity-based methods are relatively uncommon. These include ultrafiltration, in which fragments bound to a protein are retained on one side of a molecular-weight cutoff membrane (see here and here). A related approach is to immobilize a protein onto some sort of resin, incubate with fragments, wash, and then elute any bound fragments. This affinity mass spectrometry (or affinity selection-mass spectrometry, AS-MS) is used frequently in high-throughput screening to find potent binders. In an open-access ACS Chem. Biol. paper, Wenqing Shui and collaborators at ShanghaiTech University, Fudan University, and Shanghai Institute of Materia Medica apply the approach to fragments.

 

The researchers were interested in the adenosine A_2A receptor (A_2AAR), a GPCR with roles ranging from cardiovascular disease to cancer immunotherapy. The protein has also been well-studied and used as a model system for other fragment-based methods.

 

A stabilized form of A_2AAR containing a histidine tag was immobilized on nickel agarose beads. As a control, the researchers used a different GPCR, HCAR₂. Fragments were incubated with either protein for 1 hour at 4 °C. The supernatant was then removed and the beads were rinsed to remove unbound fragments. Next, the beads were washed with methanol to elute bound fragments. These were analyzed using UPLC-MS. Those that were enriched at least two-fold by A_2AAR compared to HCAR₂ were considered hits.

 

The details are interesting. In total 1100 fragments were screened in two pools of 550, with each fragment present at a mere 200 nM. The experiment was repeated four times to generate more robust data, but even so the whole process took only 10 hours. This yielded 28 hits, 17 of which were confirmed. These 17 hits also confirmed by SPR, which further revealed that 9 were quite potent (sub-micromolar).

 

The researchers were particularly interested in allosteric modulators of A_2AAR, and an extensive series of mechanistic studies involving competition with known ligands, molecular modeling, and NMR experiments suggested that one of the newly identified ligands is a negative allosteric modulator. This molecule has an IC₅₀ = 18 µM in a cell assay.

 

Overall I’m surprised the technique worked as well as it did, particularly given the low fragment concentrations, and I’d be interested to hear from readers who have had success with it. While AS-MS is likely limited to finding fairly potent binders, the simplicity and low sample requirements might make it worth investigating, particularly in cases where protein is difficult to obtain.

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.

FBLD 2018

Ten years ago, Vicki Nienaber (Zenobia) enlisted a small group of fellow enthusiasts to help her organize an independent fragment-based lead discovery conference in San Diego. That event was so successful that it was repeated in York in 2009, Philadelphia in 2010, San Francisco in 2012, Basel in 2014, and Cambridge (USA) in 2016. Last week, to celebrate its first decade, Derek Cole (Takeda), Rod Hubbard (University of York) and Chris Smith (COI) brought FBLD 2018 back to San Diego, along with some 200 fragment fans. With around 30 talks, more than 40 posters, and nearly 20 exhibitors, I won’t attempt to present a comprehensive overview, but just focus on broad themes.

Success Stories

I estimate that, in 2008, 14 fragment-based programs had entered the clinic, none of which had advanced beyond phase 2. That list has now grown to more than 40, so naturally success stories were a focus.

Andy Bell (Exscientia) discussed NMT inhibitors for malaria and the common cold (see here); the AI-driven approach took < 500 molecules to get to molecules with animal efficacy. Steve Woodhead (Takeda) revealed potent inhibitors of TBK1, a kinase involved in the innate immune response. It took just three months to go from a fragment hit to an animal-active lead, though unfortunately that molecule also showed apparent on-target toxicity. And Rosa María Rodríguez Sarmiento (Roche) described the discovery of COMT inhibitors (see here).

Mary Harner (BMS) described the discovery of sub-micromolar KAT II inhibitors in just a few months, enabled by parallel chemistry and the synthesis of 833 compounds. Several series turned out to be aggregators, and BMS has instituted a routine β-lactamase screen (an enzyme particularly sensitive to aggregators) to catch these early.

Keith McDaniel (AbbVie) described the discovery of the BET-family bromodomain inhibitor ABBV-075. This program also made rapid progress: just six months from the initial fragment hit, although the team did spend another year trying to find better molecules. This effort eventually paid off, as the same fragment has now led to a BD2-selective molecule, ABBV-744, that has recently entered the clinic.

And Paul Sprengeler (eFFECTOR) described the discovery of eFT508. This too was a rapid success: just 1 year and 170 compounds, enabled by 30 co-crystal structures, and in the end a dozen molecules competing for candidacy.

Notice that many of these projects moved quickly. Feel free to send this summary to anyone who worries that fragment programs move too slowly to be practical.

Technologies

Technologies have always had a starring role in FBLD conferences, and this one was no exception. Ben Cravatt (Scripps) discussed his fragment-based target discovery methods (see here and here). As I speculated recently, he is now using these approaches to discover new protein degraders. And his "fully functionalized fragments" are being adopted by others, as described in a poster by Emma Grant and collaborators at GlaxoSmithKline and University of Strathclyde.

Surface plasmon resonance (SPR) was used routinely by many of the speakers, but there is plenty of room for innovation. John Quinn (Genentech) described how to extend kinetic measurements to the very fast and the very slow. John also noted that gathering kinetic data earlier to deprioritize series with slow on-rates may be wise. And for those who wonder about the limits of detection for SPR, John measured the affinity of imidazole for NTA: just 13.6 mM!

Miles Congreve (Sosei Heptares) described multiple methods applied to GPCR targets along with a number of success stories. He also noted that, in the PAR2 program we mentioned recently, fragments were able to identify a buried pocket that could not be found using DNA-encoded libraries of several billion members, presumably because the pocket would not be accessible to a DNA-bound ligand. Interestingly, this pocket could be detected computationally using FTMap, as shown in a poster presented by Amanda Wakefield (Boston University).

Pedro Serrano (Takeda) described a variety of biophysical methods applied to GPCRs, the most stunning of which is an SPR microscope capable of performing kinetic binding assays on whole cells. He has tested this Biosensing Instrument on four different GPCRs, and although there are technical challenges, the data seem usable.

But the light shone most brightly on crystallography, illuminated by Stephen Burley (Protein Data Bank) among others. In order to justify continued public funding and free access (yes, there were suggestions to put the PDB behind a paywall), the PDB was asked to demonstrate its usefulness to society. Their analysis found that of the 210 new molecular entities (NMEs) approved by the FDA from 2010 through 2016, 184 had PDB entries for the target and/or the NME – for a total of 5914 structures, 95% of which were crystallographic. Most of these structures had been deposited at least 10 years before the drug was approved, so in many cases they probably played an important role.

John Barker described how Evotec has jumped into high-throughput screening by crystallography in a collaboration with the Diamond Light Source, which is now capable of doing 700 soaks per day. They have run 10 screens over the past 18 months with a small library of 320 fragments, with hit rates typically around 8%.

We have written about how high concentrations can improve success in crystal soaking experiments, and both Chris Murray and Dominic Tisi of Astex described how they’ve taken this to an extreme: 1 M soaks, with the fragment dissolved directly in the soaking solutions. Obviously this requires highly soluble fragments, so they’ve built a library of 81 “MiniFrags” having on average just 6.4 non-hydrogen atoms. They have tested these against five targets that diffract to high resolution and have found impressively high hit rates of 20-60%, compared to the 2-20% in the original 100 mM soaks for the same targets. Some of the sites are exploited by previously reported inhibitors or substrates, while others are new. And while the “universal fragment” 4-bromopyrazole did well, 1,2,3-triazole did even better – binding to all five targets in a total of 22 sites.

Crystallographers should not become complacent. Gabe Lander (Scripps) gave an update on cryo-EM, which we’ve written about here. The number of cryo-EM structures deposited in the PDB eclipsed those from NMR in 2016, and resolution continues to improve, with the current (as of late September) record at 1.56 Å. Still, the technique is not nearly as fast as crystallography: best case is 8 hours from data collection to refinement, although Gabe did think that 10 structures per day would be possible within the next few years. And Chris Murray noted that, if present trends continue, “we’ll all be doing cryo-EM in five years’ time.” Backing this up, he showed what I suspect may be the first clear density map of a fragment bound to a test protein.

This was the last major fragment event of the year, but next year’s calendar is already shaping up nicely. And mark your calendar for September 2020, when FBLD 2020 will move to the original Cambridge (UK).

Sixteenth Annual Discovery on Target

CHI’s Discovery on Target took place in Boston last week. With >1300 attendees from over two dozen countries, this is the older, larger cousin of the San Diego DDC meeting; at some points ten tracks were running simultaneously. Although more heavily focused on biology, there were still plenty of talks of interest to fragment folks.

Michael Shultz (Novartis) provocatively asked “do we need to change the definition of drug-like properties?” Long-time readers will recall that his earlier papers on ligand efficiency led to considerable debate, which seems to have been settled to everyone’s satisfaction with the exception of Dr. Saysno.

His new study, which has just published in J. Med. Chem., analyzes the molecular properties of all 750 oral drugs approved in the US between 1900 and 2017. Contrary to what strict rule of five advocates might expect, the molecular weight has increased over the past couple decades, as has the number of hydrogen bond acceptors. In contrast, the number of hydrogen bond donors (#HBD) has remained constant, suggesting that this may be more important for oral bioavailability. (Indeed, #HBD is the only Lipinski rule not broken by venetoclax.) Although Shultz did not examine “three dimensionality,” he laudably includes all the raw data – including SMILES – in the supporting information. This will be a useful resource for data-driven debates.

Molecular properties are carefully considered by Ashley Adams, who discussed the four fragment libraries used at AbbVie. The first is a 4000-member “rule of three” compliant library. For tougher targets, a 9000-member Ro3.5 library is available, as is a specialized fluorine library for ¹⁹F NMR (2000 members) and a 1000-member “biophysics” library, in which all compounds are less than 200 Da. Fragment optimization is often challenging, and since the C-H bond is most common but perhaps least explored, the AbbVie database is annotated with references on C-H bond activation relevant to each fragment.

Anil Padyana spoke about the metabolic enzymes being targeted at Agios. As we mentioned recently, these are very difficult targets, so the researchers often use parallel (as opposed to nested) screening using different techniques to minimize false negatives. Anil also described an interesting SPR assay in which fragments were introduced to the protein after the addition of an activating substrate.

High-quality protein constructs are essential for any fragment screen, and Jan Schultz described ZoBio’s technology for generating these. The company’s “protein domain trapping” approach entails high-throughput generation and screening of tens or hundreds of thousands of truncations of a given protein and rapidly selecting stable, high-expressing, and active variants.

Trevor Perrior mentioned that Domainex has a similar technology, which has been able to produce soluble protein domains in 90% of its attempts. Trevor also described a separate project in which a 656-fragment compound library was screened using SPR against the enzyme RAS. They found fragments that bind in a previously discovered site but, unlike the earlier work, the Domainex researchers were able to optimize these to nanomolar inhibitors.

Another success story was presented by Dean Brown (AstraZeneca), who described a collaboration with Heptares to discover inhibitors of protease-activated receptor 2 (PAR2). As the name suggests, this GPCR is activated when a protease cleaves the N-terminus, allowing the remaining N-terminal residues to fold back and activate the GPCR. The researchers used a stabilized form of PAR2 in an SPR screen of 4000 fragments and obtained >100 binders in multiple series. This led to AZ8838, which blocks signaling by binding in an allosteric pocket. It also has a slow off-rate, which is often an attractive feature – particularly in the context of intramolecular activation.

A number of talks were focused on protein degraders such as PROTACs (PROteolysis-TArgeting Chimeras). These are generally two-part molecules connected by a linker: one part binds to a target of interest, while the other engages the cellular degradation machinery to destroy the target. As Shanique Alabi, a graduate student in Craig Crews's lab at Yale demonstrated, the molecules are catalytic – a single PROTAC molecule can cause the destruction of multiple copies of a target protein. This “event-driven” pharmacology is thus different from most historical drugs, which are “occupancy-driven.” Is there a role for fragments?

One of the strengths of FBLD is that if a ligandable site exists, it can be found. As Astex demonstrated, the majority of proteins seem to have secondary sites, away from the active site. Although some of these may be allosteric, others probably have no functional activity, particularly in the case of protein-protein interactions where secondary sites may be located some distance from the interface. The power of degraders is that non-functional sites can be made functional. The power of FBLD is that it can find small-molecule binding sites, which could then be used as anchoring sites for one side of a degrader. Watch this space!

Fragments in China

The 2017 International Symposium on Fragment Based Lead Discovery (pdf here) was held in Shanghai, China last week. I was fortunate to be able to attend what I believe was the first significant FBLD meeting in Asia. Antimicrobials were a major theme, particularly against drug-resistant pathogens. The two days were filled with nearly 20 talks, so I’ll just try to capture a few impressions.

Ian Gilbert discussed the fragment-based efforts underway at the University of Dundee, focusing especially on library design. Among initially purchased commercial compounds, only 56% passed quality control, with 26% insufficiently soluble (at least 2 mM in water) and most of the rest either unstable or impure, similar to what has been seen by others. Ian has also enlisted undergraduate students to make “capped” fragments ready for optimization, as well as novel heterocycles.

Biophysics was a major theme of the conference, and Ian made a strong case for biolayer interferometry (BLI), one of the lesser-used fragment finding techniques. A screen can be completed in just a few days with less than a milligram of protein. In particular, BLI may be useful for assessing ligandability: Ian tested 31 targets, 13 known to be ligandable and 5 known to be not ligandable, and found good agreement with previous research. Ligandable targets generally gave primary hit rates >4.5%.

Ismail Moarefi (Crelux, now part of WuXi AppTec) highlighted microscale thermophoresis (MST) and differential scanning fluorimetry (DSF). NMR had identified ten hits against Pim1, but only six had yielded crystal structures, despite considerable effort. Of the four that didn’t, three had no activity by MST, while the fourth was very weak. Ismail also discussed the Prometheus nanoDSF instrument, which is sufficiently sensitive that it can resolve two-stage melting curves for a two-domain protein.

Another lesser used fragment-finding technique, affinity mass spectrometry, was described by Wenqing Shui (ShanghaiTech University). This uses ultrafiltration to separate protein-bound ligands from unbound molecules and mass spectrometry to identify hits; up to 1000 molecules can be screened in a single assay! Wenqing provided several success stories, including fragment hits with very weak (millimolar) affinity. She also demonstrated that the technique works against a membrane preparation of a GPCR.

Among more common biophysical methods, NMR was represented by Ke Ruan (University of Science and Technology of China). The challenge was characterizing a low-solubility ligand which caused extensive line-broadening of the protein due to intermediate exchange rates. This was solved by examining the distance between a fluorinated ligand and a paramagnetic label on the protein and using this to model the binding mode.

But by far the star of the show was crystallography. We’ve previously mentioned the high-throughput capabilities developed at the Diamond Light Source, and part of the impetus for this conference was to bring these technologies to China. Frank von Delft (Diamond and University of Oxford) noted that since the XChem platform launched in late 2015 more than 50,000 crystals have been screened against more than 40 targets, resulting in more than 1000 fragment structures. The group is committed to removing barriers and bottlenecks and today can process 1000 crystals per week through compound soaking, harvesting, data collection, and processing (using specially developed programs such as PanDDA). More than 30 external groups have used the facility, and every target has yielded at least one hit.

Of course, to collect data on 1000 crystals requires you to reproducibly grow lots of well-diffracting crystals that can handle the rigors of soaking, and Diamond has released a handy list of tips and tricks. Getting the right crystals was also the theme of two talks, one by Sheng Ye (Chinese Academy of Sciences) and the other by Carien Dekker (Novartis). Sheng emphasized the importance of optimizing the protein construct, which could include trimming flexible termini or disordered loops, mutating flexible surface residues, or considering different species. He also noted that adding heavy metal ions can actually improve the quality of the crystals as well as making the structures easier to solve. Carien also emphasized the importance of getting the construct right and discussed how seeding (crushing a hard-won crystal and using this to seed new drops) can be very useful. As we’ve noted, screening fragments at extremely high concentrations seems to be the current state of the art, with Novartis moving to 50 mM in the final soak and Diamond going beyond 200 mM! (In contrast to other types of screens at high concentrations, crystallography should not yield false positives, though hits might bind so weakly as to be undetectable by any other method.)

Such a wealth of structures can be daunting, and Anthony Bradley (Diamond) described the construction and use of a “poised library” for follow-up studies. The 768 fragments are (mostly) soluble to 500 mM in DMSO and are designed such that simple chemistry could generate 1.4 million analogs based on reagents currently in stock at Enamine. Potential analogs can be searched using the Fragment Network approach described here, and I was happy to see that Diamond has released their own open-source version (updated link as of 3 Jan 2018).

Jianhua He (Chinese Academy of Sciences) described the facilities at the Shanghai Synchrotron Radiation Facility (SSRF). This is the first third-generation synchrotron in China and has hosted more than 200 research groups since it opened in 2009. Feng Ye, who works at SSRF, gave a talk (in Mandarin) about screening a bacterial protein at XChem; the movies showing liquid handling and robotics would be impressive in any language. Renjie Zhang (Diamond), who also spoke in Mandarin, gave a talk describing (I’m told) not just XChem but how outside users can apply for access. Although there is currently a long waiting list, this should be addressed within the next year or so when SSRF gains Diamond status.

At the 2015 Pacifichem meeting there were only a few speakers from China. Given the level of interest and expertise I saw last week, I predict that the 2020 meeting will see many more.

Poll: structural information needed for fragment optimization

As mentioned last week, advancing fragments in the absence of structure is a major challenge. But how much of a barrier is it really?

I know some researchers who would not consider moving forward with a fragment in the absence of a crystal structure. As crystallography continues to advance, more targets will be available, but many will remain out of reach for the foreseeable future.

Of course, the first SAR by NMR paper used NMR rather than crystallography, and the early work that ultimately led to venetoclax relied only on NMR-derived structures. Similarly, crystallography was initially unsuccessful against MCL-1, but NMR-based models allowed effective fragment advancement.

When crystallography and NMR both fail, there is in silico modeling, which continues to improve. Last year we highlighted how modeling succeeded in merging fragments to a nanomolar binder.

But the real challenge is advancing fragments with no structural information whatsoever. There are a few published examples (such as this and this). And it’s worth remembering that optimization in the absence of structure was how drug discovery was done decades ago, before the rise of biophysics. Indeed, until recently most GPCR-based drug discovery was done without the benefit of structural information.

So, in the poll to the right please choose the minimum level of structural information you would need to embark on a fragment to lead program. Happy voting!

Dynamic undocking for better predictions

Computational screening continues to improve, due in part to a better understanding of the energetics of protein-ligand interactions. But for low affinity fragments, differentiating binders from nonbinders is still challenging. In a recent paper in Nature Chemistry, Xavier Barril and collaborators at the Universitat de Barcelona, Discngine, Vernalis, and the University of York describe a new approach that sidesteps thermodynamics.

The researchers started with the notion that, in many cases, a single hydrogen bond is critical for the stability of a protein-ligand complex. Rather than trying to calculate the binding energy of the complex, they instead ran “dynamic undocking” (DUck) experiments. This involved “steered molecular dynamics” simulations in which the researchers calculated how much work (W_QB) is required to move the ligand from the bound state to a quasi-bound state in which the key hydrogen bond is broken. The calculations do not consider what happens under equilibrium conditions (ie, unbinding and rebinding), so W_QB should not necessarily correlate with binding affinity. Still, one might expect ligands that require a particularly high energy to dissociate (for example, W_QB > 6 kcal/mol) to have higher affinities. This turned out to be the case for ligands targeting several different proteins: the kinase CDK2, the GPCR adenosine A2A receptor, and the protease trypsin. Indeed, receiver operating characteristic curves (an analysis comparing known binders and decoys) showed a significant enrichment of true binders.

Next, the researchers compared DUck with several commonly used computational docking approaches. Again, and not surprisingly, there was essentially no correlation. However, the researchers argue that this is a feature, not a bug, since the very orthogonality of the approaches should provide better predictions: a molecule that docks favorably and has a high W_QB is more likely to be a real hit.

This is a nice idea, but does it work in practice? To find out, the researchers turned to the old work-horse protein HSP90 and performed docking experiments on 280,000 fragments. Of the top 450 hits, 139 diverse molecules were chosen for DUck. Several dozen of these were then tested for binding using three different ligand-observed NMR experiments.

Of 21 molecules with W_QB > 6 kcal/mol, 8 confirmed as binders by all three NMR methods – an impressive hit rate of 38%. SPR confirmed binding for four of these (with dissociation constants between 0.077 and 0.73 mM), while three yielded crystal structures. In contrast, only one out of 15 molecules with W_QB between 3 and 6 kcal/mol confirmed, while none of 11 molecules with W_QB < 3 kcal/mol were clear hits. In other words, not only is DUck able to improve identification of true binders, it appears to have a fairly low false negative rate.

In a sense, this approach addresses the question of kinetics. Molecules that dissociate slowly from their target are becoming increasingly fashionable; perhaps DUck can be used to identify them. Although the researchers do not make this claim, several of the authors described an experimental “off-rate screening” approach a few years ago. It will be fun to see further developments, particularly as the method is extended to incorporate information beyond a single hydrogen bond.

Fragment library vendors - 2016 version

It's been two years since we last updated our list of commercial fragment libraries, and there have been several changes. The prompt for updating the list is a new Perspective published in J. Med. Chem. by György M. Keserű & György G. Ferenczy (Hungarian Academy of Sciences), Mike Hann & Stephen Pickett (GlaxoSmithKline), Chris Murray (Astex), and me. This covers all aspects of fragment library design, so definitely check it out.

One table in the Perspective compares various libraries, both commercial and proprietary. One of the manuscript reviewers asked if we could evaluate the various vendors, particularly given some negative experiences with commercial compounds. Such direct criticism (and praise!) can be awkward in the peer-reviewed literature, but is more acceptable in an online forum - think of Yelp for library suppliers. Please comment (anonymously if desired) if you've had experiences, positive or negative, with these vendors, and please feel free to add any we omitted.

Note that this list only includes companies that sell their libraries (as opposed to just using them internally).

ACB Blocks: 1280 compounds, 19F NMR-oriented, RO3 compliant, predicted to be soluble, purity >96%

Analyticon: 213 compounds, fragments from nature, RO3 compliant, high solubility, purity >95%

Asinex: >22,000 compounds

ChemBridge: >7000 compounds, RO3 compliant with predicted solubility; minimum purity 90% by 1H NMR

ChemDiv: >4000 3D fragments

Enamine: Multiple subsets including >18,000 RO3 compliant, ~1800 "Golden", and >126,000 with < 20 heavy atoms. Also separate fluorinated, brominated, sp3-rich, and covalent subsets.

InFarmatik: 1700 member consolidated library with different subsets (3D, GPCR, kinase)

IOTA: 1500 diverse, mainly RO3 compliant fragments

Integrex: 1500 compounds with diversity in shape and chemical structure, RO3 allowing one violation

Key Organics: ~26,000 compounds total with multiple subsets including 1166 with assured solubility and RO3 compliant as well as brominated, fluorinated, and CNS-directed fragments

Life Chemicals: 31,000 fragments of which 14,000 are RO3 compliant; also fluorinated, brominated, covalent, Fsp3-enriched, and covalent subsets

Maybridge: >30,000 fragments in total. The 2500 Diversity collection is guranteed soluble at 200 mM in DMSO and 1 mM in PBS.  NMR spectra are available (in organic solvent). It is available in many formats, from powder to DMSO-d6 solution. A smaller 1000-fragment subset is also available.

Otava: >12,000 fragments with various subsets including fluorinated, brominated, and metal-chelating

Prestwick: 910 mainly derived from drugs, RO3 compliant

Timtec: 3200 compounds, structurally diverse with predicted high solubility

Vitas-M: ~19,000 fragments, RO3 compliant

Zenobia:  968 fragments from different design paradigms, cores from drugs, higher Fsp3, flexible cores

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.