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.

Fragments and nanodiscs: beware nonspecific binding

Membrane proteins make up roughly a quarter of human proteins, including many important drug targets. Biophysical methods for fragment screening typically require pure, isolated proteins, and removing membrane proteins from their native environment is not always possible. One solution has been to create nanodiscs which, as we described previously, are isolated little membranes containing the protein of interest. These nanodiscs can be immobilized to the sensor chips used for surface plasmon resonance (SPR), one of the most popular fragment finding methods. But in a recent open-access Chem. Biol. Drug Des. paper, Marcellus Ubbink and collaborators at Leiden University and ZoBio show that the precise composition of the nanodiscs can have a profound effect on the results.

 

The researchers chose cytochrome P450 3A4 (CYP3A4) as a model membrane protein. This enzyme metabolizes a large fraction of drugs and has a capacious active site able to bind a wide variety of substrates. Four different lipids were chosen for the nanodisc, all of which contained phosphatidylcholine headgroups and differing hydrophobic tails: POPC, DPPC, DMPC, and DPhPC.

 

Nanodiscs were prepared either with or without CYP3A4 and immobilized to SPR chips. Unlike some membrane proteins, it is possible to isolate and immobilize CYP3A4 in the absence of membranes, though the protein forms physiologically less relevant oligomers.

 

Next, the researchers examined 13 known (non-fragment) CYP3A4 ligands. Unfortunately, most of these bound to the empty nanodiscs, and in some cases more than ten ligands bound to a single empty nanodisc. This nonspecific binding correlated with lipophilicity, with only the three least lipophilic molecules showing no binding to empty nanodiscs. One of these was the antifungal drug fluconazole, with a clogP = 0.4. Happily though SPR studies using either free or nanodisc-bound CYP3A4 yielded dissociation constants of 10-20 µM, consistent with published values.

 

Thus encouraged, the researchers screened a diverse set of 140 fragments at 250 or 500 µM against empty and CYP3A4-loaded nanodiscs using SPR. Just as with the larger molecules, there was a good correlation between cLogP and nonspecific binding to empty nanodiscs. Fragments that bound to one type of nanodisc (POPC, for example) also tended to bind nonspecifically to other types of nanodiscs (DPPC, DMPC, and DPhPC). Fewer fragments bound nonspecifically to DMPC nanodiscs than to the others, suggesting this may be the best lipid to use.

 

Fragment hits were defined as those binding to CYP3A4-containing nanodiscs more than they bound empty nanodiscs (or, for isolated CYP3A4, the unmodified SPR chip). Hit rates varied dramatically, from 9 of 140 fragments tested against CYP3A4 in POPC nanodiscs to 33 of 140 tested against CYP3A4 in DMPC nanodiscs. There were also 33 hits against free CYP3A4, 11 of which were unique. However, all 11 of these are somewhat lipophilic (average cLogP ~2.3) and most also bound significantly to empty nanodiscs. The researchers suggest that these bind “aspecifically” to CYP3A4.

 

A Venn diagram of all the hits shows only two that bind to free CYP3A4 as well as all nanodiscs containing CYP3A4, and the researchers highlight these two as the most promising. Unfortunately these are not further characterized.

 

Near the beginning of the paper, the researchers note that very few fragment screens have been conducted against membrane proteins incorporated into nanodiscs. This analysis suggests why this is so. If you use nanodiscs, make sure to consider different types of ligands. And look carefully for nonspecific binding.

Fragments vs GPx4 – in reverse micelles

Membrane proteins account for more than half of drug targets, but the fraction is far smaller for fragment-derived drugs. In part this is because biophysical methods, the mainstay of FBLD, have been harder to apply to membrane proteins. A recent (open-access) paper in JACS Au by Courtney Labrecque and Brian Fuglestad at Virginia Commonwealth University tackles this challenge.

 

The researchers use an approach called membrane-mimicking reverse micelles, or mmRM: tiny water-filled bubbles surrounded by lipids and suspended in an organic solvent. We last wrote about reverse micelles back in 2019, where they were being used to study high local concentrations of water-soluble proteins and ligands. Here, the researchers turned to membrane proteins.

 

There are actually two types of membrane proteins: integral membrane proteins and peripheral membrane proteins. The former, as their name implies, have at least part of the protein anchored in the membrane at all times; GPCRs are a prominent class. Peripheral membrane proteins are water soluble but associate with the membrane, and this interaction is often required for folding or function. One example is glutathione peroxidase 4 (GPx4), which reduces oxidized lipids. It is an intriguing but  challenging cancer target, with the only ligands being fairly reactive covalent modifiers. Thus the researchers turned to mmRMs, hoping these could both stabilize the protein in a biologically relevant state and also present binding opportunities unavailable in standard screens.

 

A library of 1911 fragments from Life Chemicals was screened against mmRM-encapsulated GPx4 using ¹⁵N-¹H HSQC protein-detected NMR. Fragments were chosen to have high aqueous solubility (at least 1 mM in PBS) and were screened in mixtures of 10 at 400 µM per fragment. After deconvolution, 14 hits were identified, and dose-response titrations revealed that 9 had apparent dissociation constants < 1 mM, with the most potent having a K_d = 105 µM.

 

Three fragments were studied in greater detail, and these were chosen to have a range of hydrophobicities from clogD = -2.1 (most polar) to clogD = 2.1 (most hydrophobic). Chemical shift perturbation (CSP) analyses suggested that the two more lipophilic fragments bind to the membrane-interacting region of the protein, while the more polar fragment likely binds to a water-exposed site. SAR-by-catalog was applied to find analogs, some of which had increased affinity for the protein, with the best being around K_d = 15 µM.

 

Interestingly, the fragments showed minimal binding to GPx4 under normal aqueous conditions (ie, in the absence of the mmRMs), even at very high fragment concentrations. The researchers suggest this is because the fragments are binding to the membrane-bound state of the protein found in mmRMs, which may adopt a different conformation than that in the absence of membranes. Perhaps. But as prior work shows, it is possible to detect extraordinarily low affinity interactions inside reverse micelles, so maybe these are just very weak binders. Ultimately it remains to be seen whether these fragments will have practical applications. I hope so, and look forward to seeing how they progress.

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 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.

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.

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!

FBLD 2010

The last major fragment event of this year is over, but it ends on a high note: FBLD 2010 has remained true to its predecessors in bringing together a great group of fragment enthusiasts in a Gordon-Conference-like environment. With 30 talks and even more posters I won’t attempt to be comprehensive or even representative, but will instead just pick out a few themes. Those of you who were there, please chime in with your own observations.

One of the themes was the shape of chemical space, and what makes a good binder. Jean-Louis Reymond, who has been systematically enumerating all stable molecules containing carbon, nitrogen, oxygen, and a few other atoms, has already published up to 13 heavy atoms but is now expanding his analysis to molecules containing up to 17. The issue of whether more attention should be given to three-dimensional fragments was discussed, with Ken Brameld reporting that fragments in crystal structures at Roche and the protein data bank contain fewer “flat” compounds than does the ZINC database of commercial molecules. However, analyzing 150,000 molecules with MW < 300 that had been screened in 40-100 high-throughput screens at Roche did not show any shape differences between the 50,000 molecules that showed up in at least one screen and those that didn’t. Interestingly, this ratio also came up in a talk by Tony Giannetti of Genentech, who said that across 13 screens 36% of their fragments hit at least one protein, while the rest didn’t hit any. Vernalis has found similar results; is there any way to enrich for the productive binders?

While FBLD 2009 had a strong computational theme, a major thrust of this conference was using biophysics to detect and confirm fragment binding. Tony discussed best-practices in SPR, and noted that since small molecules are “brighter” in NMR assays than proteins it is possible to find even very tiny fragments, including a 6 heavy-atom compound with a Kd of 600 micromolar. Tony also described the use of SPR for weeding out badly behaved compounds. Spookily, he noted that promiscuity is a function of compound, protein, and buffer, so it is not possible to weed out bad actors in a library before screening: one compound that was promiscuous against 8 targets bound legitimately and gave a crystal structure with a ninth. Adam Renslo of the University of California San Francisco described how easy it is to be misled by such phenomena. Glyn Williams described how Astex uses biophysical techniques to detect problem compounds, and noted that oxidizers can be particularly insidious – a trend that will likely continue as people explore novel heterocycles.

Glyn also presented a fascinating if slightly depressing discussion of ligand efficiency. As many have found, it can be challenging to maintain ligand efficiency during the course of fragment optimization. Yet even this goal is too modest. A fragment pays about 4.2 kcal/mol in binding energy when it binds to a protein due to loss of rotational and translational entropy; since this enropy cost is only paid once, atoms added to this molecule do not have this liability . Thus, merely maintaining ligand efficiency means that the atoms being added are binding less efficiently. This point was also emphasized by Colin Groom of the Cambridge Crystallographic Data Centre.

Membrane proteins are increasingly being targeted by fragment-based methods, as recently discussed on this site, and both Gregg Siegal of ZoBio and Rebecca Rich of the University of Utah presented progress against GPCRs.

There was general agreement that many approaches can find fragments, and that using several orthogonal methods is a good way to separate the true binders from the chaff, but a continuing challenge is what to do next. The last two sessions were devoted to chemical follow-up strategies and success stories. Some of these have been at least partially covered on Practical Fragments (for example here, here, and here) but there were a number of unpublished examples too – we’ll try to discuss these individually as they emerge.

If you missed this or the previous two conferences you’ll have another chance in 2012, when the meeting will be held in my fair city of San Francisco. And if you can’t wait that long, there are at least two fragment conferences scheduled for next year – details to come shortly.

Fragments vs membrane proteins with TINS

Fragment-based ligand discovery owes much of its success to the rise of biophysical techniques such as NMR, crystallography, and – more recently – surface plasmon resonance. These have allowed the discovery of fragments against a wide range of proteins, but one notable exception has been membrane proteins, the targets of more than half of marketed drugs. In a recent issue of Chemistry and Biology, Gregg Siegal and colleagues take a crack at this diverse group of proteins.

The researchers, from Leiden University, ZoBio, and elsewhere, use an NMR-based technique called target immobilized NMR screening, or TINS. In this method, a protein is immobilized onto a solid support. A reference protein is also immobilized; this reference is usually a well-characterized protein that does not bind to many small molecules. Each protein is then put into its own compartment of a two-compartment flow-cell, and this is inserted into an NMR spectrometer. Mixtures of fragments are then flowed through both chambers: those that interact with protein show a reduction in the amplitudes of their NMR spectra. By choosing fragments that show such a reduction for the target protein and not the reference protein, fragments that bind to the target can be differentiated from those that bind to proteins in general. After each NMR experiment, the fragments are washed away and replaced with a new set of fragments. TINS has been applied to a number of soluble proteins, as reviewed here. Remarkably, the immobilized protein samples often remain stable through hundreds of screening cycles.

Membrane proteins are notoriously difficult to crystallize or characterize by NMR. Moreover, it is often difficult to obtain enough protein to work with. However, since TINS relies on a decrease in signal from the fragment rather than a signal from the protein itself, Siegal and colleagues tested whether they could use the technology to discover fragments that bind to membrane proteins.

The researchers chose a protein called disulphide bond forming protein B (DsbB), which is found on the inner membrane of E. coli and other Gram-negative bacteria and may be important in virulence factor folding. One of the challenges of membrane proteins is keeping them properly folded, and the researchers used two different approaches to do this, either detergent micelles or “nanodiscs,” lipid bilyaers surrounded by a scaffold protein. Using less than 2 milligrams of DsbB, the researchers used TINS to screen a set of 1071 fragments in groups of about 5 each, with each fragment present at 500 micromolar concentration, a process that took 5 and a half days.

The TINS process led to 93 hits, a respectable hit rate of 8.7%. Each of these was then tested in a functional assay at 250 micromolar concentration, and more than half of the hits inhibited DsbB activity by at least 30%. Eight of these were subsequently characterized using full IC50 curves and kinetic analysis. The potencies were impressive, ranging from 7 micromolar to 193 micromolar, with ligand efficiencies as high as 0.45 kcal/mol/atom. DsbB has the advantage that it has been characterized structurally, and the researchers used chemical shift information from 2-dimensional NMR experiments to show that the fragments could be divided into two groups, with one set competing with a quinone cofactor and the other binding at a different site.

This paper demonstrates that it is possible to find fragments that bind to membrane proteins. Of course, the next question is, what can you do with the fragments? In this case there were structural data about the target, but this will not generally be true for membrane proteins, and in the absence of structure, advancing fragments to leads can be challenging. On the other hand, medicinal chemists have been developing drugs against membrane targets for decades without knowing their precise structures, so perhaps the challenge is as much psychological as scientific.