Fragments vs TLR7/8, starting from HTS

The toll-like receptors TLR7 and TLR8 are closely related proteins that respond to single-stranded RNA, often associated with viral infection, to activate the immune system. While this is useful to ward off disease, when the proteins become overactivated they can lead to autoimmune disorders such as lupus (see here for a recent discussion by Derek Lowe). In a recent ACS Med. Chem. Lett. paper Claudia Betschart and colleagues at Novartis describe advancing a fragment to a potent inhibitor of both proteins.

 

The researchers built a biochemical (specifically, a TR-FRET competition) assay in which they screened 50,000 molecules, each at 20 µM. The campaign yielded some 1500 hits, and this 2020 paper describes the optimization of one of these.

 

The new paper describes the optimization of a completely different molecule, compound 2. This rule-of-three compliant fragment was not only potent in the biochemical assay, it also showed low micromolar cell activity. A crystal structure of the compound bound to TLR8 revealed that it binds at the interface of a homodimer, making hydrogen bonds to both monomers and stabilizing an inactive conformation of the receptor. 

 

A carbon atom in compound 2 was replaced with a nitrogen in compound 3 in the hopes of picking up an additional hydrogen bond, and this led to a ten-fold increase in potency. TLR8 is located in acidic endosomes, and adding a basic piperidine moiety to try to optimize the subcellular localization did in fact improve cellular potency for compound 5. However, basic amines are often associated with hERG binding, which can cause cardiac problems, and this turned out to be the case for this series. This liability was addressed by adding a fluorine to lower the pKa of the amine. Further addition of small moieties to complement the protein led to additional increases in potency, ultimately yielding compound 15.

 

In addition to low nanomolar and even picomolar cellular activity against TLR7 and TLR8, respectively, compound 15 is selective against other TLRs as well as a panel of 100 off-targets. The compound has good DMPK properties in mice and reduced TLR7-dependent interferon-α release in a mouse model.

 

This is a nice medicinal chemistry story focusing on all aspects of optimization, not just potency. Like last month’s Notum and SARM1 posts, it is also another example of a fragment rising to the top of a high-throughput screen. Fragments don't have to be weak.

Deconstructing an HTS hit for GyrB inhibitors

COVID-19 is deservedly engaging most of our collective mindspace when it comes to infectious diseases. Unfortunately, plenty other threats are out there, including antibiotic-resistant bacteria. A paper recently published in ACS Omega by Fumihito Ushiyama and colleagues at Taisho reports progress in this area.

The researchers were specifically interested in the protein DNA Gyrase B (GyrB), which is essential for bacterial replication (see here for previous work on the same target). A high-throughput screen against the E. coli protein led to a few dozen hits that were validated using a variety of biophysical methods including SPR, isothermal titration calorimetry (ITC), and crystallography. Compound 1 binds in the ATP-binding site, which is also where the natural product inhibitor novobiocin binds. The latter molecule makes an interaction with an arginine residue in the protein, but introducing a carboxylic acid moiety onto compound 1 to make a similar interaction was not successful (compound 8e).

Taking a step back, the researchers stripped compound 1 down to the core fragment 2a, which makes both polar and hydrophobic interactions with GyrB. Unfortunately, this fragment was too weak to show any affinity by ITC, as were 120 related fragments.

Looking closer at the structure of compound 1 bound to the protein revealed a small unfilled hydrophobic pocket near the 2-quinolinone fragment. Making appropriately substituted fragments was “relatively complicated,” and most of them were inactive. However, compound 2d showed binding by ITC as well as excellent ligand efficiency. Growing from this fragment ultimately led to compound 13e, with low nanomolar affinity. In addition to binding, compound 13e is a potent inhibitor of GyrB and is selective against a panel of 96 human kinases. Unfortunately though, it displays only modest antibacterial activity, likely due to efflux.

Nonetheless, this is a nice example of thoughtful structure-based design. In particular, the dramatic boost in potency gained by filling a small pocket (nearly 400-fold from compound 8e to 13e) validates the willingness to explore difficult chemistry rather than sticking with available analogs. The paper ends by noting that optimization is continuing, and I wish them well. By my count only a single fragment-derived antibacterial agent has entered clinical development, and that program is no longer active. We could use more.

Fragments and HTS vs BCATm

One of the themes throughout this blog is that fragments are useful not just in and of themselves, but as part of a broader tool kit, what Mark Whittaker referred to as fragment-assisted drug discovery, or FADD. A nice example of this has just been published in J. Med. Chem. by Sophie Bertrand and colleagues at GlaxoSmithKline and the University of Strathclyde.

The researchers were interested in mitochondrial branched-chain aminotransferase (BCATm), an enzyme that transforms leucine, isoleucine, and valine into their corresponding α-keto acids. Knockout mouse studies had suggested that this might be an attractive target for obesity and dyslipidemia, but there’s nothing like a chemical probe to really (in)validate a target. To find one, the researchers performed both fragment and high-throughput screens (HTS).

The full results from the fragment screen have not yet been published, but the current paper notes that the researchers screened 1056 fragments using biochemical, STD-NMR, and thermal shift assays. Compound 1 came up as a hit in all three assays, and despite modest potency and ligand efficiency, it did have impressive LLE_AT. The researchers were unable to determine a crystal structure of this fragment bound to the protein, but STD-NMR screens of related fragments yielded very similar hits that could be successfully soaked into crystals of BCATm.

The HTS also produced hits, notably compound 4, which is clearly similar to compound 1. In addition to its increased biochemical potency, it also displayed good cell activity. Moreover, a crystal structure revealed that the bromobenzyl substituent bound in an induced pocket that did not appear in the structure with the fragment, or indeed in any other structures of BCATm.

The researchers merged the fragment hits with the HTS hits to get molecules such as compound 7, with a satisfying boost in potency. Interestingly, the fragment-derived core consistently gave a roughly 10-fold boost in potency compared to the triazolo compounds from HTS. Comparison of crystal structures suggested that this was due to the displacement of a high-energy water molecule by the nitrile.

Extensive SAR studies revealed that the propyl group could be extended slightly but most other changes at that position were deleterious. The bromobenzyl substituent was more tolerant of substitutions, including an aliphatic replacement, though this abolished cell activity. Compound 61 turned out to be among the best molecules in terms of potency and pharmaceutical properties, including an impressive 100% oral bioavailability and a 9.2 hour half-life in mice. Moreover, this compound led to higher levels of leucine, isoleucine, and valine when mice were fed these amino acids.

This is a lovely case study of using information from a variety of sources to enable medicinal chemistry. Like other examples of FADD, one could argue as to whether the final molecule would have been discovered without the fragment information, but it probably at least accelerated the process. More importantly, molecules such as compound 61 will help to answer the question of whether BCATm will be a viable drug target. 

When Fragments don't deliver...

In the olden days (1980s), during the cold war, Russia was "a riddle wrapped in a mystery inside an enigma".  Kremlin Watching was serious and important thing. When I write up papers, I do the same thing but trying to figure out what the actual story is.  We all know a lot more happened than is written down in 10-20 pages of an article.  This paper has me really doing it; so follow along.

Tuberculosis is a scourge caused by a mighty nasty bug.  People have been using fragments to try to combat it for a long time: 2009 and 2014: targeting pantothenate synthesis and biotin synthesis. AstraZeneca join the party (just as Entasis spins out) with this paper.  In it, they describe their NMR fragment screen combined with a HTS biochemical screen targeting thymidine synthesis.  All the TK inhibitors are TMP or thymidine analogs.  The HTS of 120,000 compounds lead to multiple 1-30 uM active site binding (confirmed by HSQC NMR) inhibitors.  Compound 1

Cpd 1.  3.6 uM, 0.46 LE, 3.54 LLE.  

Figure 2.

was chosen as the basis for the hit to lead campaign.  Modeling suggested that the pyridone core is a thymidine mimic (Figure 2). This novel core allowed to reach sub micromolar potency within 10 compounds of the original hit.  The pyrimidine core was also potent, but not as much as the pyridone.  Pyranones were inactive, as was any other group but the cyano at the 2 position. Crystallography was a key to verifying the binding mode of the compounds.  One point of this is that verified means within 1 A of the predicted pose.  SAR led to the fused pyridinone, a 2 nM inhibitor, which nonetheless had no cellular activity.  The propose that this is due to the ionic nature of the compound, but ureas, amides, and sulfonamides did not afford the desired activity. 

Figure 3.  Fused Pyridinone showing X-ray Contacts

So, as is becoming a very common theme in fragments, they decided to use fragments to try to discover an alternate scaffold.  Using TROSY (HSQC for big proteins), they screen 1200 fragments in pools of 6.  Those fragment hits, termed FRITs which is a first for me (I think I like it.), with a LE greater than 0.25 were followed up by X-ray crystallography.

Figure 4.  Napthyridinone FRIT.  590 uM, LE=0.3. 

Figure 4. shows the best FRIT and its crystal contacts.  Combining this with the knowledge from the cyanopyridinone series, a virtual library was created and docked.  Hidden in their description, it appears that the library was passed by real chemists to prioritize the cpds.  Kudos.  With very limited SAR, they achieved significant potency (Figure 5), but still without cellular potency. 

Figure 5. 200 nM, LE=0.34.  

But, WAIT, this series wasn't advanced any further because the cyanopyridinone was in "advanced lead generation".  Why, you ask?  Well, the oxidized form of Cpd 1 had exhibited moderate cellular activity.  While they don't say it, I would imagine that this means that in doing the analytical work on the compound they found a portion that had oxidized, cleaned it up, and then tested the "bad" part.  I would love to know if this is how it happened.  I would hate to learn they had planned on an oxidized compound all along.

So, on to sulfone and sulfoxides of Cpd 1.  Knowledge from the cyanopyridinone series was used to select appropriate substituents, which seems to indicate a timeline of how things happened or a "we've got nothing left to try" issue.  Again, I would love to know which.  Both the sulfones and sulfoxides showed cellular activity with increase in IC50.  And again X-ray showed that the binding mode was retained, with the sulfoxide adjacent to Arg95.  This then caused them to go back and look at the cyanopyridinones again and realize that the sulfone/sulfoxides might have just the right physicochemical properties.

I think this is a really good paper, and hopefully indicates that more work on this target and with these series are coming.So, I don't know if the fragments failed, or if something better came along.  I would think the latter, but it could be the former.  Again, I would love to know.

Druggable is as Druggable Does; Or a Million Ways to use NMR

As we all know, the closure of sites is a bad thing for those of us in Pharma.  One very small silver lining is that this frees up a lot of very nice work to be published.  The former BI site in Laval has been closed for a year and we are still seeing great papers coming out.  In this one in JMed Chem,  LaPlante and co-workers tell us about their fragment efforts against HCV helicase. 

HCV has recently had drugs approved for its treatment, but as with any virus, different modes of treatment are important.  The ATP-dependent helicase activity is found in the C-terminal 2/3 of the NS3 protein. Helicase activity is straight forward to measure and there has been some success in terms of non-viral specific inhibitors.  The inhibitors found to date have been found to act through undesireable mechanisms, but with a wealth of structural information there is no reason why helicase is inherently undruggable.  With this information in hand, they decided to target site 3+4 (green sticks are DNA from the structure), near the most conserved residue W501.  The ATP-binding site is 1+2 for reference. 

 Their first approach was to screen the 1,000,000+ corporate compound collection.  As you would expect for a paper blogged about here, they failed to find anything interesting (all the inhibitors worked by undesireable modes).  So, on to the FBDD campaign, to save the day once more.  The used a "shotgun" approach with their fragment screen:

One source of compounds came from an earlier HTS where they rejected fragment-like molecules for lack of potency, additional HCS screening of in house fragment collection, commercial fragments were screened in an SPR assay, virtual screening, and NMR.  They had a stringent workflow aimed at producing quality compounds for X-ray.  [The in-house fragment collection was 1000 compounds.]  This, along with NMR, validated ligands that bound to site 3+4.  They note one particularly noteworthy problem: high false positive rates due to the high ligand concentrations needed for the assays.  This lead to aggregation, solubility, and promiscuity.  This lead them to implement specific assays designed to eliminate these compounds (two NMR papers published in 2013, ref 18). 

They then clustered the best hits into 9 chemotypes:

 They used an "Analog by Catalog" approach and soaked or co-crytallized the best compounds into crystals.  S6, S7, and S9 were not found to bind to helicase in the crystallization trials and were deprioritized.  S5 was found at Site 3+4, but also others.  S1-4, and S8 were found to bind solely to site 3+4 (12 examples shown overlain). The key feature of this is the compounds are centralized in a wide groove over W501.  The topology of the binding site (wide groove and small lipophilic pocket) meant that optimizing for potency could be challenging.

From this, they decided S2-S4 were the most promising.  In the end, the focused on the S2 indole series as the most promising.  The S2 stereotype 1

was found from an STD-NMR screen of 3 fragment per sample (300 uM fragment and 3.5 uM helicase).  They then, much to my heart's delight, they reached into the NMR cabinet for line broadening and competition experiments confirming it binds in site 3+4.  X-ray confirmed the binding mode, but potency was not improved with chemistry.  So back into the NMR cabinet they went: a methyl resonance assay, 

 15N TROSY showing peaks shifting upon addition of a derivative of 1, and 19F NMR!  OMG, how awesome is this?  

In terms of the chemistry, removing the Br does not change the potency, but did change the orientation of the compound in the binding site.  Further elaboration led to this compound 19 (3 uM and 0.23 LE):

It contains a nitro group, think what you may.  In order to confirm the binding affinity of the compound without immobilizing protein, they used the methyl resonances to do the titrations.  The two separate peaks they followed gave values of 32 and 28 uM (+/- 8).  Given the broadness of these peaks, I think this is a pretty decent assay, although it is an order of magnitude different than the biochemical Kd.  However, subsequent structural studies revealed that there is significant structural dynamic differences between pH 6.5 and 7.5.  ITC gave the same number (33 uM and enthalpy driven); however, the ITC had to be run at high compound concentration and a different pH.  They then went off the deep end and decided to use CD (I can't link to a previous post of using CD because we have never had a post where someone used it).  With a horrible assay (don't even get me started on near-UV CD as a readout of tertiary structure), they got reasonably close to the Kds determined by ITC and methyl-NMR.  

This is a very nice example of not being afraid of a target and using all available tools to advance hits against it.  It also shows the WIDE range of NMR experiments that can be used and that are easy and practical.  In terms of full disclosure, Steven LaPlante is a FOT (Friend of Teddy) and I have been working with him. 

Experiences in fragment-based drug discovery

This is the title of a new review published in Trends in Pharmacological Sciences by Christopher Murray, Marcel Verdonk, and David Rees of Astex Pharmaceuticals. Although there is certainly no shortage of reviews on fragment-based lead discovery (a situation to which I have admittedly contributed), this one is notable both for its clarity and for being able to draw upon a deep wealth of institutional knowledge.

The review starts by discussing three notable case studies: Plexxikon’s discovery of the mutant B-Raf inhibitor vemurafenib, Astex’s Hsp90 program, and Merck’s BACE program.

Next, the authors describe some key concepts and challenges of FBLD.

Concept 1: Inappropriate physical properties are a major cause of attrition for small-molecule drugs

This should not come as a surprise to readers of this blog; the discovery of compounds with superior properties is one of the key selling points for FBLD. In support, the researchers compare 39 leads against 20 targets from Astex’s fragment-based programs with 335 published HTS-derived leads and 592 oral drugs. The FBLD-derived leads are on average 62 Da smaller and 1 log unit less lipophilic than are the HTS leads, and are much more similar to the oral drugs.

Concept 2: Although weak in potency, fragments actually form high-quality interactions

The position and the orientation of fragments tend to be conserved during the course of optimization (though see here for a notable exception). Of the 39 internal fragment-to-lead programs, roughly 80% of the atoms in the original fragment (which averaged 13 atoms total) were retained in the lead. Moreover, the mean shift in position as judged crystallographically was only 0.79 Å.

Concept 3: LE can be used to judge the relative optimisability of differently sized molecules

I like to think of fragments as ants: small and weak when considered from a human perspective, but impressively strong when considered for their size. Ligand efficiency and its many permutations are tools to assess molecules in a size-appropriate manner.

Concept 4: Relatively small libraries of fragments are required to sample chemical space

There is plenty of theory to support this (see for example here and here). The authors note that a library of 1000 compounds with 12 or fewer heavy atoms would sample ~0.001% of possible molecules with MW < 170 Da, while 1000 compounds with 25 or fewer heavy atoms would sample only 10^-14 percent of the possible larger molecules. But while theory is fine, the real proof is in the number of molecules that have entered the clinic that can trace their origins to small fragment libraries.

Of course, FBLD does have challenges.

Challenge 1: Specialized methods are needed to detect fragment binding

You don’t hunt ants with an elephant gun, and you’ll have a hard time finding fragments using standard procedures. The need for specialized methods was once a major impediment to FBLD, but happily today there are many options, and using two or more of these in combination is the best strategy.

Challenge 2: Efficient optimisation of fragment hits is required

In other words: you’ve found a fragment, now what? Structural biology is extremely helpful to figure out how the fragment binds and suggest what to do next, especially since proteins can be surprisingly flexible: of crystal structures from 25 fragment screens at Astex, 12 proteins showed movement of at least 5.0 Å upon fragment binding.

Of course, it takes more than a crystal structure to advance a fragment, and the challenges can be institutional as much as scientific. But given the proven success of the technique, these are challenges worth facing.

Finally, it’s worth checking out the entire issue of Trends in Pharmacological Sciences, which is devoted to structure-based drug design. There are some nice papers by Zhaoning Zhu on BACE, Tom Blundell and colleagues on protein-protein interactions, Stephen Wasserman and colleagues on high-throughput crystallography, and lots more.

Fragments vs Pharma

As the year winds down I’ve been catching up on some reading, and finally got to the study that Paul Leeson and Stephen St-Gallay published a couple months ago in Nature Reviews Drug Discovery. They analyzed compounds disclosed in patent applications from 18 large companies (mostly pharmaceutical companies, but also Amgen and Vertex) between 2000 and 2010. Even controlling for different targets, the companies differed considerably in the drug-likeness of their compounds, with some companies producing compounds that are considerably larger and more lipophilic than other companies. In the Pipeline has an excellent summary of the paper overall.

But what caught my eye as being of special interest to readers here is a small part of the main paper. In addition to analyzing large companies, Leeson and St-Gallay dug into the patent applications of a fragment-focused company, Astex Therapeutics (now Astex Pharmaceuticals). A dozen of the kinase targets pursued by Astex were also pursued by one or more of the large companies, and by analyzing the inhibitors from each organization, the authors could compare leads derived from fragments with leads derived using conventional approaches. The results were striking:

With the exception of chirality and sp³ measures, molecular properties are more drug-like in the compounds patented by Astex Therapeutics. This specific application of fragment-based drug design is perhaps the most compelling realization to date of the principle of lead-like chemical starting points that was first proposed more than a decade ago.

This does not mean that FBDD is a panacea: as noted previously, it is all too easy to take a perfectly good fragment and turn it into an obese grease-ball. But an attractive fragment, combined with adept medicinal chemistry and intolerance for unnecessary lipophilicity, can be a powerful combination.

And with that, Practical Fragments says goodbye to 2011. Thanks to all of you for reading, and special thanks for posting comments. May you all have a happy and successful 2012!

Ligandability

The sequencing of the human genome has thrown up lots of potential targets, but choosing which ones to pursue is difficult: many are not biologically relevant and many are shaped such that small molecules are unable to affect their activity. “Druggability” is a popular neologism that captures both of these ideas; it refers to whether a protein can be targeted by a small molecule – preferably an orally bioavailable one – to treat a disease. However, the two components of druggability are really separate concepts, and in this month’s issue of Drug Discovery Today Fredrik Edfeldt, Rutger Folmer, and Alex Breeze coin a new term – “ligandability”. A protein is ligandable if potent small-molecule ligands can be found for it. Obviously for a protein to be druggable it needs to be ligandable, and thus it would be nice to assess this characteristic as quickly as possible. How can this be done?

Enter fragments. Because fragments have lower complexity than lead-sized (let alone drug-sized) molecules, hit rates from fragment screens tend to be higher. If a binding pocket exists in a protein, a small library of just 1000 fragments or so should produce a good range of hits. In fact, Phil Hajduk and colleagues at Abbott found several years ago that fragment screens predict the success of lead discovery campaigns. In the new paper, Edfeldt and colleagues, all at AstraZeneca, analyzed 36 internal discovery projects where both fragment screens and HTS had been conducted. They used data from the fragment screens to categorize targets into three ligandability bins:

• Low: low hit rate, best affinities > 1 mM, low diversity of hits
• Medium: intermediate hit rate, best affinities 0.1 – 1 mM, some diversity of hits
• High: high hit rate, best affinities < 0.1 mM, high diversity of hits

Remarkably, all 12 targets with a low ligandability score failed HTS. Of targets that scored medium or high ligandability, 17/24 were successful in HTS screens, and 20/24 were advanced into hit-to-lead studies. These successes include targets such as BACE1 (medium ligandability), which failed HTS but which led to potent leads using fragment-based approaches. Of course, a ligandable protein may still not be druggable if it is ultimately not essential for a disease, but you often don’t discover this until after years of clinical trials.

AstraZeneca is now using fragment-based ligandability screening to help assess which targets to pursue: those with low ligandability are only pursued when the biology is truly compelling. On the flip side, targets that have failed conventional HTS but have high ligandability are reexamined using alternative hit discovery techniques, such as fragment-based methods. This seems like an appealing approach: fragments not only help drug hunters avoid throwing out the baby with the bathwater, but also to avoid drowning in dirty bathwater. I wonder how many other companies are using similar strategies.

Sixth Annual Fragment-Based Drug Discovery

The only US-based conference completely devoted to fragment-based drug discovery ended in San Diego this week. As with last year, I won’t attempt to summarize all of the talks – there was far more information presented than I have time to write (or that you probably have patience to read!) For those of you who were there, please feel free to mention some of the things I missed.

One of the points that Don Huddler (GlaxoSmithKline) and I (Carmot) made in the pre-conference short-course is that finding fragments is a solved problem. As Rod Hubbard (Vernalis, University of York) noted in his opening presentation, “it’s pretty simple to find fragments that bind; a graduate student can do it in a couple months.” Even membrane proteins are starting to yield to fragment-based screening, as Gregg Siegal (ZoBio, Leiden University) discussed in his closing session (see also here).

That’s not to say that new methods for finding fragments aren’t useful, particularly if they open new target space, are faster or more reliable, or provide new information. An example of the latter was the presentation by Denis Zeyer (NovAliX) on native mass-spectrometry (see also here). Because hydrophobic interactions are weaker in the gas phase than in water, it should be possible to select for molecules that bind predominantly through polar interactions. In fact, by gradually increasing the voltage in their MS instrument, Zeyer and colleagues generated “VC50” curves, the voltage at which half the compound dissociates from the protein. At least in one case, a higher VC50 correlated with the presence of an additional hydrogen bond to the protein compared with related molecules.

Polar contacts are generally associated with enthalpic rather than entropic interactions, and whether such fragments are preferable was the subject of some discussion, particularly at a breakfast round-table discussion. In contrast to a meeting just last year, several participants were actively collecting thermodynamic data, though there was some uncertainty as to what to do with it. This is a controversial subject; one person suggested that enthalpic binders are likely to be more hydrophilic than entropic binders, so just keeping an eye on lipophilicity is likely to be just as useful and far easier than actually measuring thermodynamic parameters. Charles Reynolds (Ansaris) provided an analysis that illustrates some of the difficulties in using thermodynamic data – I’ll follow up on this in a later post.

The shape of fragments has been previously discussed, and Ivan Efremov (Pfizer) gave a nice case study of a strikingly three-dimensional fragment: an X-ray screen of 340 molecules against BACE resulted in a single hit, a spirocyclic pyrrolidine. The electron density of this was so clear that it didn’t even need to be deconvoluted from the other three compounds in the pool, and medicinal chemistry ultimately led to low micromolar inhibitors.

There was general consensus that ligand efficiency (and various lipophilicity adjusted versions) is a helpful metric. One practitioner said that his company had sometimes pursued more chemically tractable but less ligand efficient fragments and generally came to regret those decisions. But a fragment with lower ligand efficiency could still be interesting: with fragments, even small changes could have huge effects on binding (see for example AT13387, which was discussed by Chris Murray of Astex). Thus, a bit of initial fragment optimization could be a good investment before pursuing more intensive chemistry, particularly if commercial or in-house analogs are available. Interestingly, I couldn’t find anyone who uses either fit quality or %LE.

In the early days of fragment-based lead discovery a common selling point was that it sped up drug discovery, but a theme in this meeting was that it is not necessarily faster but can provide leads against more difficult targets or better leads against “normal” targets. Of course, one has to be wary of taking a good fragment, slapping a bunch of grease on it, and turning it into a lipophilic monster.

Indeed, an analysis of fragment-derived leads published a couple years ago was not flattering. Taking up the thrown gauntlet on behalf of fragments, Chris Murray presented a retrospective analysis of all 42 fragment to lead programs at Astex (including 21 kinases and 9 proteases). The average parameters of these leads were considerably more attractive in terms of both molecular weight and ClogP that the published values of the HTS hits. At least according to this analysis, fragment approaches have the potential to deliver superior molecules, as long as one is disciplined and creative in how these approaches are applied.

FBLD 2009

Fragment-based Lead Discovery Conference 2009 just concluded in York, UK; it was the second in what will hopefully be a continuing series. With more than two dozen talks and as many posters spread over three days, most of them very high quality, it is impossible to summarize even the highlights (and I don’t want to scoop pending publications). Instead I’ll just jot down a few impressions.

On the broad topic of why FBLD is useful, an interesting shift in emphasis seems to have occurred. A few years ago a key argument in favor of fragments was getting compounds to the clinic faster, but there is now a greater focus on quality over speed. In summarizing over a decade of fragment work at Abbott, Phil Hajduk noted that FBLD hits consistently bind more efficiently than those from HTS. Similarly, Chris Murray of Astex noted that, among their five clinical candidates (four of which target kinases), the average ClogP was 1.7 (vs 4.1 for a set of 45 reported orally active kinase inhibitors), while the average molecular weight was 390 (vs 457).

One theme that differentiated this meeting from others was a strong focus on modeling: an entire day was devoted to sessions on “fragments, scoring functions and docking” and “design from fragments.” This concluded with a lively round table discussion, chaired by Vernalis’ James Davidson, titled “Chemistry challenging modeling.” But challenges didn’t only come from chemists: one prominent modeler noted that there have been no fundamentally new approaches to modeling in the past two decades; another asked why, despite the number of interesting new chemistries out there, so many modelers restrict themselves to the same old standbys such as amide bonds.

Part of the problem with modeling, of course, is separating hits from noise: true hits often show up near – but not at – the top of a ranked list, so how does one decide what is worth pursuing? Phil Hajduk discussed the use of “Belief Theory”, in which the similarity of an unknown molecule to a known active is used to evaluate the unknown.

Another problem is the quality of primary data: As Hajduk noted, “no one takes experimental error into account” when predicting ligand binding, and a recent analysis suggests that over-fitting data is a substantial problem with many computational approaches. This is all the more problematic when the data are not just noisy but spurious; Practical Fragments has noted the problem of aggregation, and UCSF’s Brian Shoichet emphasized this point, noting that 85-95% of hits from a high-throughput screen could be artifacts, while 85-100% of what remains could also be bogus. He did note, though, that fragments are less problematic in this regard than larger molecules. And Genentech’s Tony Giannetti, Vernalis’ James Murray, and others illustrated how surface plasmon resonance is effective at weeding out bad actors.

Getting better data will clearly be essential to getting better models, but one essential category, the forces involved in protein-small molecule interactions, is still poorly understood. Gerhard Klebe of the University of Marburg presented a detailed and elegant set of experiments exploring the effects of chemical structure on the enthalpy and entropy of binding to the protein thrombin. He emphasized that desolvation of fragments from water is critical, and only possible if compensated by strong interactions with the protein. This also implies that you want fragments that have low desolvation penalties as well as high solubilities – a tricky balancing act.

FBLD 2009 was held barely six months after Fragments 2009, and it is a testament to the vibrancy of the field that both conferences managed to be so successful and exciting while sharing very few speakers in common.

For the other two hundred plus attendees at the conference, what were some of your impressions?

LELP fragments reach their potential

In last month’s issue of Nature Reviews Drug Discovery, György Keserü of Gedeon Richter and Gergely Makara of Merck published a thought-provoking analysis of recent trends in lead discovery. Their results illustrate the potential of fragment-based methods, but also point out the still sizable gap from current practice.

The authors assembled a database of 335 hit-lead pairs derived from high-throughput screening (HTS) that were published between 2000 and 2007. They also assembled a database of 84 non-HTS hit-lead pairs published between 2000 and February 2008, consisting of fragment-based, virtual screening, natural product, and miscellaneous examples. They then compared properties – such as potency, molecular mass, logP, logS (a calculated measure of solubility), and ligand efficiency – of the initial hits with the resulting leads.

The results for HTS hits are not pretty: the lipophilicity as assessed by logP was considerably higher on average for HTS hits than for hits from any other methods, and this only increased as the hits were progressed to leads. The same goes for (in)solubility (as measured by logS). Even more alarming, the average properties of even the hits are worse than those of a collection of 541 approved drugs.

Fragment hits start out with the lowest lipophilicity and highest predicted solubility, but during hit-to-lead optimization these properties deteriorate to the point where they are similar on average to leads derived from HTS. Also surprisingly, the ligand efficiency of fragment hits and leads are, if anything, lower than their HTS counterparts, contrary to expectations. Even the average molecular weight of fragment-derived leads is not much lower than HTS-derived leads.

So what’s going wrong? The authors point out that, at most larger companies, fragment-based approaches are often only attempted after HTS has failed, suggesting that the targets tackled by fragment-based methods may be inherently more difficult. But they also suggest that in the early stages of hit-to-lead optimization the primary measure of success is how many compounds are delivered to lead optimization, which could encourage rapid hit expansion with simple chemistries to rapidly boost potency by adding grease, leading to more hydrophobic, less soluble molecules that will ultimately struggle in the clinic.

The authors suggest a new metric, ligand-efficiency-dependent lipophilicity, or LELP, to help avoid this trap:

LELP = (log P / LE)

Since a desirable logP range is between 0 and 3, and a desirable ligand efficiency is above 0.4, one should strive for LELP values between 0 and 7.5. There are already lots of metrics out there for evaluating molecules: see, for example, discussions of %LE, antibacterial efficiency, and fit quality (also here and here). Is a new one really necessary? Perhaps, if it gets people to focus on non-lipophilic means of increasing potency.

The authors end on a positive note for fragments:

Bearing in mind the sampling of chemical space, hit properties and synthetic accessibility, we consider that fragment hits are the optimum starting points for lead discovery and optimization.

There is, however, a burden on the team transforming a fragment hit into a viable lead: it is important to focus not merely on improving potency, but on maintaining as many of the fragment-like properties that make fragments attractive starting points in the first place. Although this goes without saying, analyses like this one suggest that it still needs to be said – and heard.