Fragments vs BACE1: again, and sometimes unintentionally

If I had to pick one target as a poster child for fragment-based lead discovery, it would probably be BACE1, a hot but controversial enzyme implicated in Alzheimer’s disease. Indeed, several inhibitors that have entered the clinic trace their origins to fragments (though unfortunately LY2886721 was just dropped due to liver problems). Four recent papers give a good flavor for where things stand.

The first paper, published in Bioorg. Med. Chem. Lett. by Thomas J. Woltering and colleagues at Roche, is not really a fragment story. Rather, it describes how a high-throughput screen against BACE1 identified a fragment-sized hit that had first been synthesized at Roche in the 1970s as part of an analgesic program. Despite relatively low affinity, compound 1 had good ligand efficiency, and its similarity to other reported BACE1 inhibitors suggested how to grow into the so-called S3 pocket of the enzyme. At the same time, the cyclic amidine “head group” was modified to try to modulate the pKa of the molecule and thus improve the pharmaceutical properties, leading ultimately to compound 12, with good biochemical and cell potency and marginal activity in a mouse model.

In a related J. Med.Chem. paper by Hans Hilpert and colleagues, the Roche researchers further optimized this series of molecules, most notably by introducing electron-withdrawing fluorine substituents around the cyclic amidine ring to further tweak its basicity. Compound 89 was potent, exhibited good pharmacokinetics, and showed impressive target modulation in both mice and rats. The authors state that “a compound from this chemical class is currently undergoing clinical evaluation.” Thus, even though this program did not start explicitly from fragment screening, an initial fragment hit ultimately led to a clinical candidate.

The third paper, in Curr. Opin. Chem. Biol., is much more fragment-centric. In this brief but lucid review, Merck researchers Andrew Stamford and Corey Strickland describe how FBLD has played an integral role in developing BACE1 inhibitors and highlight several successful examples; given that MK-8931 is the most advanced clinical candidate for BACE1, they know of what they write. They note that:

Key elements of successful fragment based drug discovery (FBDD) approaches targeting BACE1 have been the use of X-ray co-crystal structures to design optimal starting points for subsequent optimization and an emphasis on ligand efficiency (LE) rather than affinity to drive the discovery of drug-like, brain penetrant inhibitors.

And if this just whets your appetite, check out the 25 page review in a recent issue of J. Med. Chem. by Suresh Singh and colleagues at Vitae Pharmaceuticals, which contains more than 100 chemical structures of BACE1 inhibitors. The review is certainly not limited to fragment-derived molecules, but it does note that these are superior to the peptidic inhibitors discovered using more traditional approaches.

MK-8931, BACE1 inhibitor, enters Phase 2/3 for Alzehimer’s

Perhaps no other single target so successfully demonstrates the potential of fragment-based approaches as BACE1, a challenging aspartyl protease implicated in Alzheimer’s Disease. Practical Fragments has previously written about efforts from Merck, Lilly, Pfizer, Evotec, and Amgen (there’s also the Astex-AstraZeneca collaboration).

Today Merck announced that their MK-8931 has entered a Phase 2/3 clinical trial, a randomized placebo-controlled study which will run for 78 weeks and enroll up to 1700 patients in the phase 3 portion.

There have been concerns lately as to whether or not BACE1 is a viable target for Alzheimers; it will take large studies like this to answer that question. Practical Fragments wishes them luck.

There and Back Again (and Back Again)

BACE is a very popular target (there are potentially 20 Billion reasons for it). As we noted in April, Pfizer has entered the contest (publicly now). Pfizer utilized a subset (340 fragments) of their recently described Fragment library (GFI) used X-ray as the discovery platform soaked in 4 at a time. At an intial concentration of 20 mM, 58 of the 85 mixes yielded useable diffraction data. They then repeated the screen at 2mM and 200uM to attempt to gather data on compounds which disrupted the crystal lattice at higher concentrations. All of this led to the discovery of one fragment (the spiropyrrolidine).
They then threw the biophysical and biochemical book at this compound to establish it as a bona fide inhibitor: Octet (1.4mM Kd, 0.31 kcal/mol/atom), STD-NMR, 1H-15N HSQC NMR, functional NMR assay to determine weak Kds, and a BACE inhibition assay (1.1mM). It was found that this fragment had excellent permeability and low potential PGP efflux.
They then did their SAR to optimize the core and develop "growth" vectors. They ended up improving potency by three orders of magnitude with seriously affecting the ligand efficiency nor the in vitro properties predictive of good brain penetration.
To me, this is the most interesting point in the paper. Does ontogeny recapitulate phylogeny for drugs? If you start with good properties, do you keep them? I know there is a good amount of debate on whether or not a fragment will keep its binding mode as it is optimized/expanded. What is the general thinking on properties? Do people screen (at least in silico) their libraries for things like permeability?

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.

Seventh Annual Fragment-Based Drug Discovery Meeting

CHI’s annual FBDD meeting took place in San Diego this week, and since this was the first time in a while both Teddy and I have been in the same place we’ve decided to make this a joint post. As with last year this does not aim to be comprehensive.

One of the highlights of the conference was a set of three talks on BACE1 inhibitors from Amgen (Ted Judd), Lilly (David Timm), and Pfizer (Ivan Efremov), the first two of which have been discussed here and here. It’s nice to see fragments playing a pivotal role in delivering advanced leads and – at least in the case of Lilly and Merck – clinical candidates against what has been one of the most difficult drug targets in industry.

Speaking of difficult targets, Till Maurer of Genentech gave a lovely presentation on using NMR-based fragment screening to discover inhibitors of the holy grail of oncology, Ras. They’ve recently published some of this story, which we’ll highlight in an upcoming post.

A common question is ‘how often do you find the same fragment using different methods?’ (see here for an ongoing discussion on LinkedIn). Cynthia Shuman from GE gave a nice case study in which she screened the protein PARP15 against 987 fragments using a Biacore T200. Of the 15 fragments with shapely, well-behaved sensorgrams, 14 were confirmed by NMR. On the other hand, only one of these hits was detected in a differential scanning fluorimetry (thermal melt) assay.

Marcel Verdonk at Astex described general trends from mining in-house and published data. After looking at 43 in-house targets, he found that 8000 compounds had been tested against 2 or more proteins, and after plotting by molecular weight found that, consistent with the original Hannian model, larger compounds are more selective. In a separate analysis of 53 fragments that had been advanced to leads, he found that in most cases the initial fragment maintained roughly the same position and orientation from start to finish.

Rod Hubbard, Teddy and I all ran round-table discussions, but only Teddy kept notes, which are summarized here.

The topic started as a discussion of 2D vs. 3D fragment libraries. In the recent Pfizer fragment build, a group of diverse chemists eyed every compound, and at least five had to agree to each molecule before it went into the library. 

The discussion went briefly to the old fight: Are nitros masked amines or noxious moieties?  The table ended up agreeing that if you would remove the nitro group or change it anyways, why put it in the first place?

We then dove right back into the 2D vs. 3D debate. Kinases seem to love 2D fragments, while other classes of targets seem to NEED 3D fragments. One idea discussed was 3D fragments as complements to 2D fragments. It was mentioned that 3D fragment libraries would need to be MUCH larger to cover equivalent chemical space. I thought the idea that 3D fragments would be exploring “vector” space rather than “chemistry” space would mean that you could go with a much smaller library, if you want to use it for vector space searching. It was also proposed that 2D fragments tend to be much smaller (~150-180Da-ish) and 3D fragments would be, by necessity, bigger (~250 Da).

The topic then changed to SBDD (structure-based drug discovery) as part of FBDD. Most people at the table were of the opinion that they wouldn’t use FBDD (on a normal priority target) without SBDD. And with SBDD, you don’t need 3D fragments to explore vector space since you will have the X-ray to guide you. 

The point was made that 3D fragments also HAVE to be scaffolds which would end up in the final compound. If you are simply using a scaffold to explore vector space without any hope of it ending up in the final product, why bother. [TZ Note: I think this is very shortsighted and people do not understand that targets will most likely NOT have SBDD to guide them, at least in the fragment-based lead generation stage.] 

The question was asked to the table: is FBDD a valid approach in the absence of structure? Three people said yes, the rest (~8) said no. All three who said yes were small company/ CRO people. Everyone agrees if you do go with FBDD without structure you need to have a HEAVY investment in biophysics to characterize the protein and the hits. 

One person asked about low confirmation hits following a fragment screen: the table agreed that this is most likely the result of the library being “wrong”. We finished the discussion by asking if 2D fragments are more pan-class (not targeted to a specific class of targets) and 3D fragments may be more target-focused. The resounding answer was “Who knows, but why would they be?”

As this post is already getting long we’ll stop here, but for those of you who were also at the conference please add your comments. And if you missed this one, there are still several exciting upcoming events this year!

Fragment-based drug discovery and X-ray crystallography

I’m holding in my hands a book of this title, edited by Thomas Davies and Marko Hyvönen and published this year as part of Springer’s Topics in Current Chemistry series. I believe this is the fourth book entirely devoted to fragment-based drug discovery, which shows both the vitality and rapid development of the field.

The book starts with an introduction to fragment-based drug discovery by me. If you’re new to the field, this chapter should serve as a self-contained summary.

In the next chapter Thomas Davies and Ian Tickle describe how FBDD is practiced at Astex, paying particular attention to the use of X-ray crystallography. Notably, researchers from this company “do not consider a fragment hit to be ‘validated’ and suitable as a starting point for medicinal chemistry until it has been observed to bind by crystallography.” This chapter also contains a nice analysis of fragment library design and a couple case studies, including the discovery of the clinical-stage CDK2 inhibitor AT7519.

Rod Hubbard and colleagues at Vernalis and the University of York next describe their efforts to discover Hsp90 inhibitors using a combination of virtual and fragment screening. We’ve covered some of this before (here and here), but it’s nice to see the full story.

The next chapter also focuses heavily on a single target: Daniel Wyss and colleagues at Merck describe their success in discovering BACE inhibitors. This chapter also includes an excellent review of NMR methods for finding fragments.

Michael Hennig and colleagues at Roche (Basel) contrast the various biophysical methods used to discover fragments, with a heavy emphasis on SPR. Crystallography is also covered, in particular co-crystallization of fragments with protein. Co-crystallization is more time-consuming than soaking fragments into preformed crystals, so compound prioritization techniques such as SPR are especially useful.

One of the most promising applications of fragment-based methods is tackling tough targets such as protein-protein interactions, the subject of a chapter by Marko Hyvönen and colleagues at the University of Cambridge. The chapter contains a nice discussion of energetics and hot spots as well as a detailed analysis of methods to find fragments which complements some of the other chapters.

Eddy Arnold and colleagues at Rutgers discuss the use of crystallographic fragment screening against two HIV-1 targets, HIV protease and HIV reverse transcriptase (RT). We’ve previously discussed the former here. In the case of RT, fragments were soaked into crystals in the presence of a high affinity inhibitor, effectively blocking its binding site from fragments. More than 30 fragments were identified binding to multiple other sites on the protein – one fragment bound at 11 distinct sites! Interestingly, the fragments were enriched for halogen-containing molecules. Several also had functional activity with respectable ligand efficiencies. The authors also discuss other published fragment work on HIV RT.

Finally, Didier Rognan at the University of Strasbourg discusses computational approaches to library design, binding site determination, and predicting druggability. Fragment docking is extensively covered, along with a discussion of what factors contribute to success. It seems that docking is particularly good at identifying negatively charged, relatively buried fragments that make similar hydrogen bonds as the substrate. De novo ligand design, both the successes and challenges, is also covered.

Like last year’s book, all the chapters in this one are published online, but it is worth getting a bound copy as it is nicely put together, with color figures liberally integrated throughout rather than banished to plates at the back.

And once more into the breach...

When the market is more than 20 Billion dollars, you will find everyone working there. And so, with this recent publication, we have another entrant into the BACE inhibitor from Fragments competition, discussed previously here. This is the fifth by my count, the first being from Astra Zeneca.

In this paper, Eli Lilly describes their efforts using fragments to generate "the first orally available non-peptidic BACE1 inhibitor that produces profound Abeta-lowering effects in animals." They screened ~8000 compounds at 4.76mM that generated a number of low-affinity, but highly "LEAN" fragments (discussed below). Of most interest were the amino-benzothiazine (1) and amino-thiadiazine (2) compounds.

The authors note that co-crystallilzation was a key advance for their understanding of this system. The co-crystal showed two copies of (1) with high active site occupancy and in the "open-flap" conformation. One copy engaged the catalytic dyad and the other spanned the S1-S3 cavity. This data let them recognize that the planarity of the molecules were not optimal for fragment growth, so they "de-planarized" them, leading to (3). Only one enantiomer of (3) was recognized by BACE. The co-crystal of this compound showed binding identical to the original fragment, one copy engaging the catalytic dyad and one in the S1-S3 region. Addition of the S3 moiety pyrimidine led to (4). Fluorination of the central ring reduced in vivo clearance and and realized a significant increase in potency, while maintaining atom efficiency (5).

The crystal structure of (5) shows that this molecule retains an optimal H-bonding network, efficiently traverses S1, and projects the pyrimidine into S3.

Compound (5) was tested in animal models and pre-clinically in healthy human volunteers given orally. It showed significant reduction in Abeta levels in brain and CSF. Retinal pathology became a concern in longer term animal studies and the compound was not taken any further.

This paper shows the power of Fragments in discovering novel scaffolds for important targets. It is also important to note that the modified fragment hit retained the same binding as the original fragment hit.

The other contribution that the Lilly group brings out in this paper is the concept of LEAN (Ligand Efficiency by Atom Number): -log (IC50)/Number of heavy atoms. This is one of many ways people have developed to gauge the efficiency of their ligand hits, I think this is the simplest to use. As can be seen from the Lilly data, a LEAN of >=0.30 is an efficient molecule. For those of us who don't do logs in our head well, this lends it itself to a simple cheat sheet:

I can send a copy of this spreadsheet to anyone who wants.

Fragments vs BACE1: Amgen’s story

Some targets that have proven recalcitrant to standard screening approaches seem to be particularly amenable to fragment-based approaches. Beta-site amyloid precursor protein cleaving enzyme 1 (BACE1) is one such example: Practical Fragments has previously discussed programs from both Evotec and Schering/Merck, the latter of which has resulted in more than one clinical candidate. In a recent issue of J. Med. Chem., researchers at Amgen describe their adventures with this Alzheimer’s disease target.

The researchers started by using SPR to screen a library of about 4000 fragments (which had MW < 300, polar surface area < 30 Ų, and ≤ 2 hydrogen bond donors). This led to 106 hits with 10 mM or better potency, of which 8 confirmed in an orthogonal assay with potency better than 1 mM. Among these was fragment 1, which was also discovered as a BACE1 binder by researchers at Astex using crystallographic screening.

Astex’s crystallographic structure showed compound 1 packed pretty tightly into BACE1, but surprisingly, the Amgen team found that walking a bromine atom around the phenyl ring produced gains in potency at all four positions. In fact, adding an aromatic group off the 6-position, as in compound 34, led to a dramatic increase in potency, and crystallography revealed that the protein undergoes a conformational change to accommodate the extra bulk and form an edge-face interaction between a phenylalanine side chain and the added aromatic group.

Putting substituents off the 3-position, as in compound 44, led to molecules that could access either the P1 pocket or the P2’ pocket of the enzyme, but adding the ortho-tolyl group from compound 34 to give compound 43 locked the binding mode down to the P2’ pocket and gave a satisfying boost in potency such that standard enzymatic assays could be used instead of SPR. Further medicinal chemistry led to picomolar binders such as compound 57 as well as compounds less active in the biochemical assay but with better permeability and lower efflux, such as compound 59. This compound also showed in vivo activity in a rat model, though it is rapidly metabolized.

Although crystallography was clearly enabling throughout the process, this paper is a warning not to be too slavish in adherence to structure, as the initial break (compound 1 to compound 34) would not have been predicted to be active based on the co-crystal structure of compound 1 with BACE1.

This is also another nice example of starting with a rather generic fragment (heck, one published by another group!) and advancing it to a potent, proprietary series.

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.

Evotec and BACE

Certain targets seem to be particularly popular with fragment-based methods, perhaps in part because they are recalcitrant to other approaches. One of these is the Alzheimer’s target BACE, as described in a post earlier this year on work from Schering-Plough (Merck). Now, in a recent issue of Bioorg. Med. Chem. Lett., James Madden and colleagues at Evotec describe their approach to this challenging protease.

The researchers started by screening their 20,000-fragment library in a functional assay at 1 mM, an endeavor that led to a number of hits, some of which were confirmed by surface plasmon resonance and crystallography. One of these, Compound 3 (see Figure), bore some resemblance to and bound in a similar fashion as a compound previously reported in the literature. The researchers were able to use the binding mode of this other compound to help them improve their fragment. After a couple cycles of synthesis, assays, and crystallography, the researchers arrived at compound 14.

The final molecule shows a 100-fold improvement in potency over the initial fragment and some cellular activity, and the researchers were able to maintain ligand efficiency throughout optimization, albeit at lower values than some previously reported molecules. However, the final compound is still relatively weak, and there is no information on brain penetration. Moreover, it shows activity against hERG, leading Evotec to deprioritize this series. Still, the paper is an easy read and a clear example of what has been called “fragment-assisted drug discovery,” in which traditional medicinal chemistry approaches (in this case borrowing from a competitor compound) are applied along with fragment methods to generate new molecules.

Fifth Annual Fragment-Based Drug Discovery

The first of two conferences in 2010 exclusively devoted to fragment-based drug discovery concluded in San Diego this week, and I thought I’d jot down some observations while my memories are still fresh.

The pre-conference short courses were quite successful (and I’m hopefully only slightly biased by the fact that Teddy and I were both instructors). Participants included folks with considerable experience in fragments, which allowed good discussion.

One talk from the conference that stands out in my mind was by Sandy Farmer of Boehringer Ingelheim. BI is a relative late-comer to fragment-based methods, really only starting in late 2004. Sandy described how fragment efforts are run in parallel with HTS. They use an intentionally modest fragment library of 2000 diverse compounds; increasing the size of this library tended to overwhelm downstream efforts. Fragments are confirmed using multiple assays, including SPR and size-exclusion chromatography coupled with mass spectrometry, with crystallography playing a pivotal role in determining which fragments to advance. Part of the challenge at BI has been getting chemists to accept FBS, or “faith-based synthesis,” particularly where initial fragments have low affinities. A focus on ligand efficiency helps, as do organizational strategies such as establishing a dedicated group of chemists focused on fragment projects.

Often at conferences you hear about success stories, but sometimes the continuing challenges are more instructive, as when Ravi Kurumbail at Pfizer discussed his efforts to discover drug-like inhibitors of the serine protease Factor XIa. One of the sobering findings was that, although a functional assay of 2500 fragments yielded a 6.5% hit rate, adding 0.01% detergent eliminated activity and revealed most ‘hits’ as false positives. Even one crystallographically characterized fragment with an apparent IC50 of 75 micromolar turned out to be an artifact after subsequent analysis – a reminder to always be vigilant at higher concentrations.

But back to success stories: Daniel Wyss gave an update on the BACE program from Merck (legacy Schering-Plough, which has run more than 30 fragment screens on various targets). We highlighted a couple publications resulting from this effort earlier this year. It turns out there are now three molecules from this program in early clinical trials – a clear indication of the importance of this target and the utility of fragment screening.

Finally, Rick Artis, formerly of Plexxikon (now Elan) gave an update on the PLX4032 Raf kinase program. This project demonstrates the potential for fragment-based efforts to move quickly: it was started in February 2005, the clinical candidate was identified in January 2006, the IND was filed in September, and the first patient was dosed in November of that year. The molecule has continued to move at warp speed through the clinic: it is now partnered with Roche in Phase III testing for metastatic melanoma, and was recently profiled in the New York Times. This lengthy but excellent article is well worth reading for a bit of perspective when life in the lab gets you down.

These are just a few of many nice talks and breakout discussions. I know that at least some readers of this blog were there – what were your impressions?