Practical Fragments

Fragment linking: flexible rules

2012-01-30T07:24:00.000-08:00

Linking two fragments together to achieve a boost in potency has been done a number of times (see here, here, here, and here), though it often doesn’t work as well as might be hoped (see here). To better understand the energetics of fragment-linking, Marc Nazaré, Hans Matter, and colleagues at Sanofi-Aventis Deutschland have analyzed ligands for the blood coagulation enzyme factor Xa (fXa) and published their results in a recent issue of Angew. Chem. Int. Ed.

The researchers “deconstructed” potent fXa inhibitors into component fragments, measured their inhibition constants (and thereby inferred their binding energies), and compared these binding energies with those of the original linked molecules. One of the first observations was that many of the component fragments bound so weakly as to show no measurable activity, a phenomenon that has been observed previously.

In an exemplary case, cleaving a single bond connecting the two component fragments of a 2 nM ligand (1a, below) yielded one fragment (1g) with 58 micromolar activity and another (1d) whose activity was worse than 10 millimolar. Because the second fragment has such low affinity, the binding energy of linking is really just a lower estimate, but it seems to be at least 3.3 kcal/mol, which is greater than the binding energy of fragment 1d itself. In other words, the affinity brought about by linking is greater than the affinity of the weakly binding fragment. The superadditivity provided by the linker in this case is about 300-fold, a similar value to that observed in the unrelated MMP-12 system. This is perhaps all the more remarkable given the fact that the fragments are connected by a linker containing several rotatable bonds, the entropy of which should partially counter the advantages of linking.

In fact, a common strategy to improve the potency of two linked fragments is to rigidify the linker. Often this doesn’t work: in a second case, the Sanofi-Aventis researchers cleaved one bond of a 3 nM ligand (2a, below) to yield two fragments with roughly equal potency. However, even though the linker is more rigid than in the previous example, the binding energy due to linking is less – just 2.0 kcal/mol, representing a boost of about 30-fold.

As the authors note:

The introduction of rigid aromatic moieties as a common approach to increase affinity does not necessarily maximize the benefit from the linker effect as detrimental affinity contributions might originate from suboptimal orientation and accommodation of specific binding elements.

There are many more examples in this paper than can be covered in a blog post; the authors dissect compounds 1a and 2a at a number of different points, and while the component fragments typically bind less tightly than simple additivity would suggest, there are lots of interesting details.

Finally, it is interesting to note that ligands 1a and 2a consist of a relatively hydrophobic fragment (1g or 2g) connected to a more polar fragment (1d or 2h). The fact that these show superadditivity is consistent with Mark Whittaker and colleagues' proposal last year that linking such fragments is likely to maximize additivity, although given the precise interactions made by both parts of the molecules the details get a bit messy. We’re not yet at the point where the universe of molecular interactions can be distilled to rigid rules.

Fragment events in 2012

2012-01-17T07:14:00.000-08:00

2012

February 19-23: Molecular Medicine Tri-Con 2012 will be held in San Francisco, with a section on fragments on February 21.

March 13-14: Select Biosciences is holding its Discovery Chemistry Congress in Munich, Germany, with a full two days devoted to fragment-based lead discovery.

March 19-23: Keystone Symposium: Addressing the Challenges of Drug Discovery – Novel Targets, New Chemical Space and Emerging Approaches will be held in Tahoe City, CA. Although not exclusively devoted to fragments, there are many speakers I look forward to hearing.

April 17-18: Cambridge Healthtech Institute’s Seventh Annual Fragment-Based Drug Discovery will be held in San Diego, with short courses on SPR and FBLD taking place on April 16. This is a chance to meet both editors of Practical Fragments! You can read impressions of last year’s meeting here and 2010’s here.

May 13-17: The 30th Noordwijkerhout-Camerino-Cyprus Symposium Trends in Drug Research will be held in Amsterdam, including a session on fragment-based drug discovery.

August 19-23: The Fall 2012 ACS meeting will take place in Philadelphia, PA, and has at least one section on fragment-based drug discovery.

September 23-26: Finally, FBLD 2012, the fourth in an illustrious series of conferences, will be held in my fair city of San Francisco. This should be a biggy – the first such event in the Bay Area (and the weather in September is usually decent too). You can read impressions of FBLD 2010 and FBLD 2009.

2013

March 4-5: Fragments 2013, the 4th RSC-BMCS Fragment-based Drug Discovery meeting will be held at the Harwell Science and Innovation Campus near Oxford, UK.

Know of anything else? Organizing a fragment event? Let us know and we’ll get the word out.

Enthalpy Arrays

2012-01-16T07:07:00.000-08:00

As regular readers know, there are lots of ways to find fragments, each with its own strengths and weaknesses. Isothermal titration calorimetry (ITC) is useful for being able to extract thermodynamic values from an experiment, but it tends to be low-throughput and is thus used more as a secondary rather than a primary assay. To make calorimetry more convenient, Michael Recht and colleagues at Palo Alto Research Center have constructed nanocalorimeters. They describe using these “enthalpy arrays” for fragment screening in a paper just published online in the Journal of Biomolecular Screening.

In a typical ITC experiment, a protein is mixed with a ligand and the tiny temperature change that occurs upon binding is detected. In the case of nanocalorimeters, up to 96 detectors are arranged on a plate, and sample volumes are typically a few hundred nanoliters. At this scale, the enthalpy of binding becomes very challenging to measure, but it is possible to measure the heat generated during the course of a reaction as an enzyme processes its substrate. This allows one to follow the reaction in real time without any dyes, labels, or artificial substrates. Also, since an inhibitor will change the reaction profile in a predictable manner, one can determine its mechanism of action.

Each detector in the enthalpy array is set up such that droplets are rapidly mixed together in sets of two. In the experimental set, one droplet contains the protein of interest while the other contains a substrate and a fragment. (Each detector also incorporates a control pair – one droplet containing the substrate/fragment mixture and another containing bovine serum albumin.) In the current paper, the researchers were looking for competitive inhibitors of PDE4A10, a phosphodiesterase implicated in inflammatory disorders. The protein was present at a final concentration of 5 micromolar, substrate was at 2 mM, and each fragment was present at up to 2 mM. 160 very small fragments (average molecular weight only 154 Da) were screened individually, resulting in 11 competitive hits with Ki < 2 mM; 2 other hits displayed more complex kinetics.

The 11 competitive hits were characterized in more detail; the most potent had a Ki of 0.32 mM and the most ligand efficient had LE = 0.43 kcal/mol-atom. In collaboration with Vicki Nienaber and colleagues at Zenobia, all 11 of these were taken into crystallography experiments. This proved challenging: unliganded PDE4A10 crystals suitable for fragment soaking could not be grown, necessitating more labor-intensive co-crystallography. Unfortunately, although some crystals were obtained, they did not diffract at high enough resolution to unambiguously fit the electron density of the fragments, though there was evidence for binding in the active site. The researchers were able to crystallize PDE4A10 with pentoxifylline, a known phosphodiesterase inhibitor. Since many of the fragments have structural features reminiscent of other phosphodiesterase inhibitors, this suggests starting points for modeling.

As described in this paper, enthalpy arrays could be used as a primary screen for fragment hits with defined modes of action before follow-up by slower methods. Although in this particular case crystallography was not successful determining co-crystal structures of the novel fragments, in a recent talk Michael described a related system which did yield good crystal structures. I look forward to seeing additional applications of this approach.

19F NMR...Just Like 1H NMR

2012-01-04T06:40:00.000-08:00

Fluorine is a powerful nucleus for NMR: it has almost the same sensitivity as 1H and is 100% abundant. 19F NMR based screening is relatively new in the pharmaceutical industry. One of the biggest proponents of this approach has been Claudio Dalvit. In 2009, Dalvit and colleagues (J. Am. Chem. Soc. (2009) 131:12949) proposed the LEF (Local Environment of Fluorine) approach which allows for efficient screening of even weak binding fragments containing fluorine and the discovery of fluorophilic protein environments on the target. Despite the obvious advantages of 19F, it still has not been taken up widely in the industry. A new paper in J. Med. Chem. from Amgen may change that.

In this paper, they demonstrate multiple practical applications of 19F in FBDD, essentially demonstrating congruence for 19F-based methods with 1H-based methods. This is a particularly important as most people are conversant with how to understand and utilize 1H-based data; there is no "re-learning" necessary to adopt 19F based data. One potential obstacle to adoption is the argument that the 19F fragments would not be "fragment-y" or would be unlike other libraries and thus have little cross-fertilization. As shown in the table below, their 19F Fragment library is based on typical Ro3 rules with similar size and diversity.

As can be seen here, this library is relatively diverse. The authors argue that ~30% of "Fragment Space" is covered by this library. But, due to congruency with 1H molecules, this is more than sufficient to give adequate screening hits.The paper demonstrates the utility of this approach on BACE (one of everybody's favorite targets). In less than 24 hours they were able to screen the entire library and identified five compounds (out of 6 hits) for follow-up. They introduce a method for Kd determination by NMR which cannot be done by 1H-based methods, differential Chemical Shift Perturbation: which utilizes changes in the 19F chemical shifts to determine the Kd. In cases where chemical shifts are not observed, the authors state you can use differences in line broadening as the measurement. This is an interesting and novel approach to Kd determination and they validated this approach by using SPR in parallel. The authors also demonstrate that the Holy Grail of FBDD (simultaneous binding fragments) can be identified and oriented based upon 19F-19F iLOE, exactly analogous to 1H-1H NOEs.

This is an excellent paper, that I hope sparks more people to investigate the utility of 19F-based screening and post-screening confirmation.

Fragments vs Pharma

2011-12-29T07:12:00.000-08:00

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!

Fragments vs matrix metalloproteinase-13: avoiding the metal

2011-12-19T06:34:00.000-08:00

Matrix metalloproteinases (MMPs), as their name suggests, are metal-dependent proteases that cleave the extracellular matrix. They have been implicated in a wide variety of diseases including cancer and inflammation. MMPs have also been used as model systems to study the effects of fragment linking. (In fact, the first successful example of SAR by NMR was conducted against MMP-3.) Most inhibitors, including those starting from fragments, interact with the catalytic zinc in order to achieve potency. However, with roughly two dozen human MMPs, all dependent on a zinc ion, selectivity has been tricky. A recent paper in J. Med. Chem. mostly from researchers at Boehringer Ingelheim sidesteps this problem nicely.

MMP-13 is one of the more interesting members of the family due to its apparent role in rheumatoid arthritis. The enzyme is crystallographically well-behaved, and has a large substrate-binding pocket (the S1’ pocket) near the catalytic zinc that is dissimilar from other S1’ pockets. Even better, there is an adjacent side pocket (S1’*) that can open when the S1’ pocket is occupied, providing further selectivity.

The researchers started by performing a virtual screen of their entire corporate library to look for fragments that might bind in the S1’ pocket. These were added to an in-house fragment collection, and the combined set of roughly 1000 compounds was screened at 0.5 mM concentration in a biochemical screen. Compounds were also assessed using NMR (saturation transfer difference) and size exclusion chromatography mass-spectrometry. One of the best hits was Compound 1, which came from the virtual screen and was originally made as a synthetic intermediate in a completely different program.

Crystallography revealed that Compound 1 does in fact bind in the S1’ pocket, making several hydrogen bonds, with the amide moiety pointed towards the S1’* portion of the protein. This compound also displayed some selectivity towards two other MMPs. Fragment growing towards the S1’* pocket led to compound 11, with increased potency and ligand efficiency, and ultimately to compound 15, with low nanomolar potency and > 1000-fold selectivity against 9 other MMPs. Crystallography revealed that, as expected, the compound binds with the benzoic acid moiety in the S1’* pocket. And despite the presence of the ethyl ester, compound 15 is orally bioavailable in rats.

The paper gives no indication of where the program is today, but it is another nice example of fragment growing, as well as taking an unconventional approach to achieve selectivity.

Are enthalpic binders more selective than entropic binders?

2011-12-06T06:44:00.000-08:00

Thermodynamics is one of those abstract subjects that can have surprising real-world implications. The two components of free energy, enthalpy and entropy, are simplistically associated in drug discovery with polar interactions for the former and hydrophobic interactions for the later. Some researchers have suggested that enthalpically-driven binders are better starting points for optimization, and that best-in-class drugs rely more on enthalpy than entropy. In a recent paper in Drug Discovery Today, Yuko Kawasaki and Ernesto Freire at Johns Hopkins University suggest that enthalpic binders may also be more selective.

Medicinal chemists apply two general strategies to improve selectivity: increase the affinity of a compound for its target more than for off-targets, or decrease the affinity of a compound for off-targets. Kawasaki and Freire argue that the first is more likely to result from entropic interactions, while the second is more likely to result from enthalpic interactions. This is because nonpolar (entropic) interactions are often tolerant of mismatches; a hydrophobic substituent might improve the affinity of your ligand for its target, but, unless it causes a severe steric clash, it may also improve activity for off-targets – though hopefully less. Indeed, recent findings suggest that more lipophilic molecules tend to be more promiscuous than similarly-sized but less lipophlic molecules. On the other hand, due to the highly directional nature of polar interactions, a mismatched polar (enthalpic) interaction in an off-target is likely to be highly detrimental to binding.

The researchers consider two case studies involving HIV-1 protease inhibitors. In one example, adding two (non-polar) methyl groups improves the affinity of the inhibitor for its target as well as for two off-targets, though it improves the potency towards HIV-1 protease more, thus improving selectivity.

In the second case, a non-polar thioether is replaced with a polar sulfone. This slightly decreases the overall binding affinity for HIV-1 protease, but has a much larger negative effect on two off-targets, resulting in greater selectivity. In this case, the enthalpy of binding for HIV-1 protease is considerably improved, though the effect is compensated for by unfavorable changes in entropy. As the authors note, “even if a strong hydrogen bond does not contribute to affinity, it might contribute significantly to selectivity.”

Ideally you would want to use both strategies (improving affinity for your target and decreasing affinity for off-targets). However, since you probably don’t know all your off-targets, focusing on enthalpic binders may be the way to go, as mismatched polar interactions are likely to exclude lots of unknown off-targets.

Of course, two examples may not make a trend, but they do make a testable hypothesis. For example, there is a veritable plethora of kinase inhibitors with known specificity profiles: it would be interesting to correlate these with their thermodynamic profiles. But at any rate, this is yet another reason to hold down the hydrophobicity of your compounds.

Kinetic efficiency and slow-binding fragments

2011-11-28T07:18:00.000-08:00

We’ve previously discussed the proliferation of metrics used to evaluate fragments. Ligand efficiency is by far the most popular, and what it and most other measurements have in common is that they represent binding affinity (or inhibition, or some other surrogate). Binding affinity is associated with thermodynamics – how well a molecule binds to a target – but this measure says nothing about how rapidly a molecule associates and dissociates from the target (kinetics). In the November issue of Drug Discovery Today Geoffrey Holdgate and Adrian Gill at AstraZeneca propose a new metric, kinetic efficiency (KE), to address this issue:

KE = τ / (# of heavy atoms) = t1/2 / (0.693 * (# of heavy atoms))
where τ is the residence time or relaxation constant and is, in the simplest case, 1/koff
koff is the dissociation rate constant
and t1/2 is the half-life for dissociation

Why are the kinetics of dissociation important? Holdgate and Gill list a series of drugs for hypertension and note that compounds that remain bound to the receptor longer avoid rapid clearance and thus have superior clinical activity. On the other hand, drugs for schizophrenia that bind the D2 dopamine receptor can cause side effects if they remain bound too long. Thus, optimal kinetic efficiency is case-dependent .

Though kinetics of ligand binding can be assessed with techniques like SPR, this parameter is often ignored. However, as Holdgate and Gill point out, slow-binders are likely to be lead-sized or drug-sized molecules. Indeed, none of the roughly two-dozen examples they present would satisfy the rule of 3.

This raises an interesting question: how often do fragments dissociate slowly? Slowly-dissociating fragments are often flagged as pathological in SPR studies. Intuitively it seems that smaller molecules would have faster kinetics; a small fragment is likely to be able to dart in and out of a protein-binding site more rapidly than a larger molecule that requires some movement on the part of the protein to accommodate its binding. Still, there must be some cases of fragments with slow dissociation rate constants. If you know of any please mention them in the comments section.

And once more into the breach...

2011-11-18T05:50:00.001-08:00

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.

What do fragment hits look like?

2011-11-17T07:10:00.000-08:00

Our last post highlighted a study showing that most of the best fragment hits loosely followed the Rule of 3, even though the library from which they were selected was not strictly Rule of 3 compliant. As it happens, Chris Swain at Cambridge MedChem Consulting has been tabulating fragment hits reported in the literature and has assembled a database of more than 280. Previously he has assessed the physicochemical properties of commercially available libraries; now, he’s analyzed the fragments that have actually been reported as hits and has published the results here.

For the most part the fragments conform to the Rule of 3. Size-wise most of them are truly fragments, with the majority having molecular weights less than 250 Da. Not surprisingly, they also tend to be fairly aromatic. Interestingly, roughly one third of the fragments are charged at physiological pH, with a pretty even split between acids and bases.

Of course, despite the overall Rule of 3 compliance, there are outliers in all the parameters, especially hydrogen-bond acceptors. So perhaps, to paraphrase Darren Begley channeling Bill Murray, the Rule of 3 should be renamed the Guideline of 3.

Pushing the Rule of 3

2011-11-10T07:41:00.000-08:00

The Rule of 3 (Ro3) is commonly used to design fragment libraries. First published as a brief 450-word (shorter than this post!) “update” in the discussion forum of Drug Discovery Today in 2003 by researchers at Astex, it has become the fragment equivalent of Chris Lipinski’s famous Rule of 5. Like that rule, it has its critics, notably our friends at FBDD and Molecular Design. A key point of contention is whether the Ro3 is too restrictive. A new paper in J. Med. Chem. from Gerhard Klebe’s group at Philipps University Marburg addresses this question.

The definition of the Rule of 3 provided by Astex is as follows:

The study indicated that such hits seem to obey, on average, a ‘Rule of Three’, in which molecular weight is <300, the number of hydrogen bond donors is ≤3, the number of hydrogen bond acceptors is ≤3 and ClogP is ≤3. In addition, the results suggested NROT (≤3) and PSA (≤60) might also be useful criteria for fragment selection.

One of the criticisms leveled at the Ro3 is that it is vague in terms of what constitutes a hydrogen bond acceptor. For example, does the nitrogen in an amide count? What about the nitrogen in an indolizine? Presumably for simplicity Lipinski assumed that any nitrogen or oxygen atom would count as a hydrogen bond acceptor. At the risk of engaging in exegesis, I propose that only oxygen or nitrogen atoms most medicinal chemists would consider as acceptors should be counted as acceptors, and that the limits on the number of rotatable bonds (NROT) and polar surface area (PSA) are optional.

In the recent paper, which is also discussed at FBDD and Molecular Design, Klebe and colleagues assembled a library of 364 fragments in which the average properties of the fragments were within Ro3 guidelines (with the exception of “Lipinski acceptors,” which would include the nitrogen of a tertiary amide), but there were some outliers. They then performed a fluorescence-based competition screen against the model protein endothiapepsin, resulting in 55 fragments that inhibited at least 40% at 0.5 or 1 mM concentration. These fragments were taken into crystallography trials, resulting in 11 structures. The paper presents lots of nice analysis of how these fragments bind to the protein. It also notes that:

Only 4 of the 11 fragments are consistent with the rule of 3. Restriction to this rule would have limited the fragment hits to a strongly reduced variety of chemotypes.

This may be an overstatement. Looking at the fragment hits more closely, all of them have molecular weights less than 300, and only one has ClogP > 3. Personally, given the problems of molecular obesity and the dangers of lipophilicity, I’d say that these aspects of the Ro3 are the most important, and find it notable that the hits were so compliant given that the library did contain larger, more lipophlic members.

All 11 of the crystallographically characterized fragments also have 3 or fewer hydrogen bond donors and TPSA < 60 Å². Only two of the fragments have more than 3 rotatable bonds, but where the majority of the fragments fail to pass Ro3 is in the number of “Lipinski acceptors,” where 6 of the 11 have > 3. However, if you count hydrogen bond acceptors more judiciously (ie, compound 291 would have 3 acceptors rather than 4, since the aniline nitrogen would not be counted), only 1 of the 11 fragments has more than 3 acceptors.

Like most rules, the Rule of 3 should never be treated as a strait-jacket. That said, given the number of possible small fragment-sized molecules, and the necessarily limited size of any fragment collection, there seems to be plenty of room within the Rule of 3 for attractive chemical diversity.

Privilege or selectivity?

2011-10-31T06:35:00.000-07:00

Fragment selectivity is something we’ve covered before (see here and here). Sarah Barelier and Isabelle Krimm at the Université de Lyon have published on this topic (see here), and in a recent issue of Current Opinion in Chemical Biology they review the subject and its implications.

The authors document what many investigators have independently observed: some fragments, as expected theoretically, are less selective than larger molecules, but other fragments are quite selective.

They also note that fragments that bind to any protein tend to be slightly more lipophilic than fragments that don’t bind to any target proteins, suggesting that hydrophobic interactions are important:

Hydrophobic interactions play a major role in protein–ligand interactions and are known to be non-directional, thus allowing binding to a multitude of pockets in different conformations. By contrast, hydrogen bonds were shown to confer specificity but do not always add much binding free energy. This is due to the cost of desolvating both the donor and acceptor of the hydrogen bond, which can nearly equal the benefit of the hydrogen bond formation. Therefore, if the hydrogen bond acceptors or donors are not satisfied in the complex, it is likely that more hydrophobic fragments will be preferred.

This observation—lipophilicity for binding energy, hydrogen bonds for specificity—is consistent with the recent publication from Mike Hann and Andrew Leach, which finds that promiscuity increases with increasing lipophilicity.

One figure in the Barelier and Krimm paper shows 30 fragment-like “privileged scaffolds” that should bind to multiple proteins. What struck me is these molecules’ overwhelmingly planar character: more than half are completely aromatic (such as quinoline and indole), and only one is completely aliphatic. Barelier and Krimm note that:

The low specificity of these molecules is probably owing to their rigid and aromatic structures, well-adapted to protein hydrophobic pockets where π-stacking with phenylalanine and tyrosine are commonly observed.

This reminds me of Tony Giannetti’s talk at the FBLD San Diego meeting earlier this month, where he also noted that fragment hits tend to be relatively flat. Of course, given the negative correlation between aromaticity and good pharmaceutical properties, just because aromatics are frequent hits doesn’t mean they are necessarily the best hits – they may be tricks rather than treats. All of which comes back to a key question for library design: do you focus on the flat “privileged” scaffolds that will likely have high hit rates in your assay but may have baggage, or on the more three-dimensional compounds that may have lower hit rates but may ultimately be more developable?

Fragment Based Lead Discovery San Diego 2011

2011-10-25T06:32:00.000-07:00

Zenobia Therapeutics hosted a one-day FBLD meeting in San Diego last Friday. It was a very full day of seven talks and plenty of informal discussion, with both lunch and happy-hour on a rooftop terrace overlooking the ocean. I’ll try to give some flavor of the event below – those of you who were there, please chime in with your own impressions.

In the first talk of the day, Michael Recht of Xerox’s PARC discussed the construction and use of array-based nanocalorimetry devices, which analyze samples as small as a couple hundred nanoliters. Although conceptually related to isothermal titration calorimetry, the scale of nanocalorimetry makes direct measurement of binding enthalpy difficult. However, the devices are well-suited to measuring the heat output from enzymatic reactions, thus allowing detailed study of enzyme kinetics and inhibitor characterization (see here for a full description and here for a review, both open-access).

Maurizio Pellecchia of the Sanford-Burnham Medical Research Institute gave a wide-ranging talk with the common theme of NMR as an enabling method. In particular he noted that, due to its low protein requirements, ILOE (which we’ve written about previously) could be considered the “homeopathy of NMR;” a recent paper in J. Med. Chem. describes its application to generate hits against Bcl-family proteins. He used a different NMR technique to discover a potent and selective JNK inhibitor that binds in both the ATP and substrate binding sites. On a completely different topic, Maurizio noted that roughly one-third of drug targets contain metals, prompting the construction of a fragment-library designed with metal-chelation in mind, a strategy we’ve written about previously (see also here). Many of these techniques and libraries have now been licensed into a new company, AnCoreX Therapeutics, founded by Maurizio.

Schrödinger was a major sponsor of the meeting, and company scientist Kathryn Loving gave a good overview of the potential of their suite of software tools for fragment-based lead discovery. After lunch I presented a PDK1 story (see here) as well as applications of Carmot’s Chemotype Evolution, and Michelle Arkin from UCSF discussed some of the capabilities of the university’s Small Molecule Discovery Center, with special focus on protein activators and protein-protein disruptors.

Tony Giannetti of Genentech gave a nice presentation on caspase-6 inhibitors and also discussed the power of SPR, a topic on which he’s written extensively. He noted that as long as one is careful about conducting the experiment, the number of promiscuous or non-specific binders found by SPR tends to be less than the number of true hits – he described the former as “a managed headache.”

Tony is in the enviable position of having screened numerous targets using the same platform, allowing him to do some very interesting data mining. One phenomenon that we’ve previously commented on is the fact that, across multiple companies, only about a third of fragments hit in one or more screens, and Roche is no exception (36% across 13 screens). With the merger of Genentech and Roche now complete, Tony has been able to compare the fragment libraries assembled separately at each institution. Interestingly, although they contain < 5% common fragments and < 10% similar fragments, the libraries are, by broad measurements such as size or lipophilicity, statistically indistinguishable. However, the hits from the Roche collection seem to have higher ligand efficiencies. Also, the most potent binders tend to have 13-17 atoms, with the most ligand-efficient molecules generally having a molecular weight < 200. Finally, there has been a lot of recent discussion on making fragments less flat (aromatic) and more three-dimensional (often aliphatic). However, as I predicted 2 years ago, one needs to be cautious: it turns out that hits were actually enriched for flatter fragments, although Tony did mention that most of the screens were against kinases, which may be particularly “flatophilic”.

Vicki Nienaber, founder and president of Zenobia, closed the conference by discussing the potential for fragment-based approaches to tackle diseases of the central nervous system (CNS). The rationale is that, since CNS drugs need to be small to cross the blood-brain-barrier, it pays to start with fragments. Indeed, Zenobia’s fragment library has a molecular weight averaging just 150-175, with an upper limit of 225, which should allow them to avoid molecular obesity. Vicki described the discovery of nanomolar leads against LRRK2, a Parkinson’s disease target, and against PDE10, a Huntington’s disease target.

As far as I know this was the last face-to-face fragment event this year, but there are still several webinars this month and next, and it’s not too soon to start planning for 2012; please see here for upcoming events.

Fragments vs PI3 kinase

2011-10-13T07:15:00.000-07:00

The phosphatidylinositol-3 kinases (PI3Ks) comprise a family of lipid kinases that are important in a variety of biological pathways and have thus become popular targets for drug-discovery; earlier this year we highlighted a fragment screen out of AstraZeneca against four members of the family. In the most recent issue of Bioorg. Med. Chem. Lett., researchers from Pfizer have published their approach to one of these targets.

Samantha Hughes and colleagues first tested 5960 fragments in a biochemical assay (at 0.5-1.5 mM) to find molecules that inhibited PI3gamma. Hundreds of hits resulted, of which 150 were confirmed in full dose-response curves. These were further triaged using orthogonal methods, ultimately resulting in five X-ray structures of co-complexes, including compound 1, which binds to the hinge region of the kinase. Virtual screening of the larger Pfizer library led to the discovery of additional compounds such as compound 2. Growing compound 1 by adding an acetyl group generated compound 9, improving both potency and ligand efficiency, but synthetic challenges stymied further work. However, a closer examination of the crystal structure of compound 1 suggested a merging strategy with the previously reported compound 10 to generate compound 12, with high potency and ligand efficiency.

Astute (or paranoid) readers will notice that compound 12 contains a Michael acceptor that looks suspiciously reactive. In fact, it is closely related to the notorious rhodanines, many of which form covalent bonds with proteins and, because of the resulting promiscuity, have been accused of “polluting the literature.” Nonetheless, crystallography revealed that the compound binds (noncovalently) to PI3gamma exactly as designed. Moreover, it is fairly selective for other kinases, inhibiting only 3 out of 43 tested at 1 micromolar compound. Compound 12 is also metabolically stable, permeable, and cell active. This is a good example of why it is important not to be overly dogmatic in compound triaging, particularly at an early stage in a project.

Finally, it is worth noting that this paper comes from the storied Sandwich Laboratories, which are being closed down. If there is a silver lining to this tragedy it is that the closure has resulted in a flurry of nice publications from the site. Still, such papers hardly offset the opportunity cost of the drugs that would otherwise have been discovered there – nor the disruption caused to hundreds of scientists. Practical Fragments wishes the best of luck to all of them.

Poll results: fragment screening methods

2011-10-05T07:11:00.000-07:00

The fragment-screening methods poll is now closed, and the results are pretty interesting:

As expected, people are using multiple techniques – an average of 2.4 according to this poll.
No technique is dominant, though SPR and ligand-detected NMR are each used by more than 40% of respondents. Thermal shift assays are also popular, with about one-third of people using them.

X-ray crystallography was used by just under a quarter of respondents, less than computational screening and not much more than reported using protein-detected NMR, which is surprising given the challenges of advancing fragments in the absence of structures.

Some of the other techniques such as ITC are still pretty niche at less than 10%, though it will be interesting to revisit this survey in a couple years and see how things change.

A decade of molecular complexity

2011-09-29T07:48:00.000-07:00

Molecular complexity is one of the key reasons why fragment-based lead discovery should work. As described in 2001 by Mike Hann and colleagues at GlaxoSmithKline, the idea is that very small, simple molecules are likely to be able to bind to many different sites on many different proteins; think of the water molecule as being an extreme example of this. As molecules become larger and more complex, they are less likely to bind to any given site on a protein, though if they are complementary to a site the potency will be greater. Similarly, more complex molecules are more likely to have a single binding mode than smaller, less-decorated molecules, which could assume multiple orientations at a single site. These intuitive ideas were supported by a simple computational model that suggested that there is an optimum complexity where molecules would be simple enough that they would bind to several different targets (and thus be useful in a screening collection) while still being complex enough to bind in single, defined orientations with sufficient potency to permit detection. Mike Hann and Andrew Leach now have a new paper in Current Opinion in Chemical Biology that analyzes how this idea has weathered the past decade.

A central tenet of the molecular complexity model is that more complex molecules should be less promiscuous (bind to fewer protein targets) than less complex molecules. Although defining complexity is itself complex, the authors summarize a number of studies that examine promiscuity as a function of various molecular properties that could be used as proxies for complexity. Interestingly, many of these studies find that as molecular weight or – especially – lipophilicity increases, promiscuity actually increases, an apparent contradiction of the complexity model. Indeed, Hann and Leach present internal data showing that, for a given molecular weight, promiscuity increases with increasing lipophilicity.

The authors consider several explanations for this, such as the notion that larger, lipophilic molecules may not need to be perfectly complementary to a protein: one portion could bind, while the rest of the molecule remains unbound. One explanation that the authors don’t address but that could account for much of the discrepancy is the validity of the measurements from the studies surveyed. Practical Fragments has previously discussed the issue of aggregation artifacts, which can occur even at nanomolar concentration – well below the 10 micromolar cutoff used in many of the cited studies. Indeed, Brian Shoichet has commented that the majority of hits from HTS screens could be artifacts, and an alarming proportion of "active molecules" in published work are also bogus. Thus, the apparent promiscuity of more lipophilic compounds may reflect merely assay artifacts, not true binding.

In other words, I propose at least two kinds of promiscuity. “Legitimately promiscuous” compounds actually bind to multiple proteins in a one-to-one defined fashion. Perhaps these are rare, in line with the complexity model. “Apparently promiscuous” compounds simply interfere with the assay, whether through aggregation, fluorescence artifacts, or other PAINful mechanisms. Given how many discovery programs get side-tracked by these phenomena, these compounds are likely to vastly outnumber legitimately promiscuous molecules, thus distorting the results of data-mining exercises.

There is plenty more in the paper than can be summarized here, and if this piques your interest Mike Hann will be discussing both molecular complexity as well as molecular obesity at the SLAS webinar series starting next month.

Updated: fragment events in 2011 and 2012

2011-09-25T12:45:00.000-07:00

As 2011 winds to a close there is still one more addition to the calendar, and 2012 is shaping up nicely.

August 16 - November 15: Is your travel budget limited? Emerald Biosciences is putting together a series of free webinars related to FBLD on August 16, September 20, October 18, and November 15. If you've missed any they are all archived online.

October 21: Zenobia Therapeutics is putting together a FBLD conference in San Diego. Although just one day, there is a nice lineup of speakers, so try to make it if you can.

October 25 - November 15: The Society for Laboratory Automation and Screening (SLAS) is holding a 4-part webinar titled "Interrogating Chemical Space — Rules, Filters, Fragment-Based Screening and Beyond," with presentations by Chris Lipinski (October 25), Mike Hann (November 1), me (November 8), and Dan Wyss (November 15).

2012

March 19-23: Keystone Symposium: Addressing the Challenges of Drug Discovery – Novel Targets, New Chemical Space and Emerging Approaches will be held in Tahoe City, CA. Although not exclusively devoted to fragments, there are many speakers I look forward to hearing.

April 17-19: Cambridge Healthtech Institute’s Seventh Annual Fragment-Based Drug Discovery will be held in San Diego. You can read impressions of this past year’s meeting here and 2010’s here.

August 19-23: The 244th National ACS meeting will be held in Philadelphia, and there will be at least one symposium on FBLD.

September 23-26: FBLD 2012, the fourth in an illustrious series of conferences, will be held in my fair city of San Francisco. This should be a biggy – the first such event in the Bay Area (and the weather in September is usually decent too). You can read impressions of FBLD 2010 and FBLD 2009.

Know of anything else? Organizing a fragment event? Let us know and we’ll get the word out.

Ultrafiltration to filter fragments

2011-09-15T07:19:00.000-07:00

If you’ve taken our poll on finding fragments you’ll have noticed ultrafiltration as one of the possibilities (and if you haven’t voted yet, please do so on the right-hand side of page). Ultrafiltration is grouped with affinity chromatography and capillary electrophoresis because all of these methods involve affinity-based separation of bound from unbound fragments. The technique is described in a recent paper in Anal. Bioanal. Chem.

The basic idea is simple: mix fragments with your protein of interest and then centrifuge through a membrane which retains large molecules such as proteins (and any bound fragments) but allows small molecules (unbound fragments) to pass through. If the composition of the filtrate differs from the composition of the initial mixture, one can assume that any depleted molecules are bound to the protein.

The researchers, all from the University of Washington, Seattle, have been using the technique on internal targets, and their recent paper gives a thorough account of how to do it and describes the results against two protein targets. In both cases, fragments were grouped into pools of 5 to 10 compounds, with each fragment at 0.098 mM and protein at 0.201 mM concentration; these conditions were chosen such that a 1 mM binder would give a 15% reduction in signal, which was roughly 3-fold over their standard deviation for control experiments. The ultrafiltration was done at 4 ˚C in 96-well plates, and the filtrates were analyzed by HPLC using a UV detector (all the fragments contained a chromophore, though the authors suggest that the experiment could also be done using mass spectrometry as a detector).

For the first protein, riboflavin kinase, the researchers found 4 hits out of 134 fragments tested, of which 3 confirmed as single compounds (ie, not in cocktails). Interestingly, these fragments were competed by the enzymatic product flavin mononucleotide but bound more tightly in the presence of the other product and cofactor, ADP and Mg(II). For the other protein, methionine aminopeptidase 1 from the parasite that causes malaria, 10 hits were found out of 243 fragments tested, of which 9 confirmed. The top 6 of these could be competed by methionine, the enzymatic product.

Overall this seems like an interesting method, though I do have one quibble: the authors do not report the activity of these fragments using other techniques. In theory it should be possible to extract dissociation constants from the % reduction in UV signal, and it would be very interesting to see how these values compare to dissociation constants measured using orthogonal methods. Has anyone out there done this?

Poll: fragment screening methods

2011-09-07T20:21:00.000-07:00

Finding fragments is now routine, but how are people doing it? NMR of course has a venerable history, but X-ray crystallography provides higher resolution data, SPR is faster than either, and there are all sorts of other methods. To learn what’s state of the art (and to help me gather some data for an upcoming talk) please vote for what method(s) you’re using. Note that the vote is on the right side of the page, and you can vote for more than one method.

Affinity chromatography, capillary electrophoresis, or ultrafiltration
Computational screening
Functional screening (high concentration biochemical, FRET, etc.)
ITC (isothermal titration calorimetry)
MS (mass spectrometry)
NMR – ligand detected
NMR – protein detected
SPR (surface plasmon resonance)
Thermal shift assay
X-ray crystallography
Other – please specify in comments

Fragments vs BACE1: Amgen’s story

2011-09-06T07:23:00.000-07:00

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 Å², 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.

Fragment docking: it’s all about ligand efficiency

2011-08-29T07:13:00.000-07:00

A widespread belief holds that it is more difficult to computationally dock fragment-sized molecules than lead-sized or drug-sized molecules. But is this really true? And if so, why? These questions are tackled by Marcel Verdonk and colleagues at Astex in a recent paper in J. Med. Chem.

The researchers examined 11 targets for which they had multiple crystal structures of each with bound fragments (which contained up to 15 non-hydrogen atoms) and larger molecules (which contained at least 20 non-hydrogen atoms); these crystal structures were the “correct” structures against which computational models could be judged. A total of 106 fragments and 100 larger molecules were then docked against their target proteins using a variety of different methods.

Surprisingly, the overall results were not overly impressive (<70% correct depending on methodology – often much less). But even more surprisingly, there was no difference between the success rates of the fragments and that of the larger molecules. However, the reasons for the poor performance were different. In the case of fragments, the problem was often that the scoring function didn’t recognize the correct solution; the energetics were just too subtle. In the case of the larger molecules, though, the problem was more often one of sampling: the docking program failed to produce the conformation of protein or ligand that corresponded to the correct solution, so it had no opportunity to score it. Potency made no difference: high-affinity compounds fared just as poorly as lower affinity compounds. What did make a difference, though, was ligand efficiency: compounds with high ligand-efficiency (> 0.4 kcal/mol/atom) were docked with considerably greater success than those with lower ligand efficiencies. As the authors point out, this makes sense intuitively:

High LE compounds form high-quality interactions with the target, which should make it easier for a docking program (both from a scoring and search perspective) to dock these compounds correctly.

So the next time you see a computational model of a protein-ligand complex, you might want to take a closer look at ligand efficiency to get a sense of how trustworthy the structure might be.

Journal of Computer-Aided Molecular Design 2011 Special FBDD Issue

2011-08-25T07:18:00.000-07:00

The most recent issue of J. Comput. Aided Mol. Des. is entirely devoted to fragment-based drug discovery. This is the second special issue they’ve dedicated to this topic, the first one being in 2009.

Associate Editor Wendy Warr starts by interviewing Sandy Farmer of Boehringer Ingelheim. There are many insights and tips here, and I strongly recommend it for a view of how fragment-based approaches are practiced at one large company. A few quotes give a sense of the flavor.

On corporate environment:

In most cases, the difference between success and failure has little to do with the process and supporting technologies (they work!), but rather much more to do with the organizational structure to support FBDD and the organizational mindset to accept the different risk profile and resource model behind FBDD.

On success rates:

We have found that FBDD has truly failed in only 2-3 targets out of over a dozen or so.

On cost:

FBDD must be viewed as an investment opportunity, not a manufacturing process. And the business decisions surrounding FBDD should factor that in. FBDD is more about the opportunity cost (of not doing it) than the “run” cost (of doing it).

On expertise:

Successful FBDD still requires a strong gut feeling.

On small companies:

In the end, FBDD will always have a lower barrier to entry than HTS for a small company wanting to get into the drug-discovery space.

The key to success for such companies is to identify or construct some technology platform.

There’s a lot of other really great content in the issue, much of which has been covered in previous posts on fragment library design, biolayer interferometry, LLEAT, and companies doing FBLD. The other articles are described briefly below.

Jean-Louis Reymond and colleagues have two articles for mining chemical structures, one analyzing their enumerated set of all compounds having up to 13 heavy atoms (GDB-13), the other focused on visualizing chemical space covered by molecules in PubChem. They have also put up a free web-based search tool (available here) for mining these databases.

Roland Bürli and colleagues at BioFocus describe their fragment library and its application to discover fragment hits against the kinase p38alpha. A range of techniques are used, with reasonably good correlation between them.

Finally, M. Catherine Johnson and colleagues present work they did at Pfizer on the anticancer target PDK1 (see here and here for other fragment-based approaches to this kinase). NMR screening provided a number of different fragment hits that were used to mine the corporate compound collection for more potent analogs, and crystallography-guided parallel chemistry ultimately led to low micromolar inhibitors.

Designing fragment libraries

2011-08-21T19:24:00.000-07:00

The topic of fragment library design is similar to foundation construction: most people don’t give it much thought, but any organization that doesn’t take it seriously could quickly find itself on shaky ground. Three recent papers cover different aspects of this topic.

The first paper, published in J. Comput. Aided Mol. Des. by researchers at Pfizer, describes the design and construction of their Global Fragment Initiative (GFI), a 2,885 fragment library meant to be broadly applicable to any target using any screening method (NMR, X-ray, SPR, MS, and biochemical assays). Most of these fragments came from commercial or in-house collections, but 293 were synthesized specifically for the library. All compounds were filtered to remove reactive or otherwise undesirable moieties. Interestingly, a large number of cationic and anionic molecules were included, based on the observation that many approved drugs are charged. Also, roughly a quarter of the compounds contained at least one chiral center.

Potential library members were put through a rather more rigorous selection than the standard Rule of 3 (for example, cLogP < 2.0). Molecular complexity was explicitly considered, and overly complex fragments were excluded. Fragments were also analyzed by 2D and 3D similarity and chosen to maximize diversity, though with the criterion that close analogs were available either in-house or commercially. Compounds were also chosen to allow rapid chemical elaboration. Finally, compounds were evaluated by NMR for purity and solubility at 1 mM in aqueous buffer and 50-100 mM in DMSO.

The bulk of the library (excluding custom-synthesized fragments) has been screened against at least 13 targets in 8 different protein families, mostly by NMR and biochemical assays, resulting in hit rates between 2.8 – 13%. Only one fragment hit all 13 targets, while 766 hit only one; in total 33% of the fragments hit one or more of the targets, a fraction eerily similar to that seen at Genentech and Vernalis. Overall this is a thorough, information-dense paper, and well worth reading if you are considering building or expanding a fragment library.

One of the most productive first steps you can take after identifying a fragment hit is to test close analogs or larger molecules that contain the fragment. Of course, it is easier to buy compounds than to make them, so a fragment library that effectively samples commercial compounds is likely to be useful. This “SAR by catalog” approach is the topic of the second paper, also in J. Comput. Aided Mol. Des., from Rod Hubbard and colleagues at Vernalis and the University of York.

The researchers analyzed catalogs of available compounds from each of three vendors (Asinex, Maybridge, and Specs). Filtering out undesirable functionalities and binning the molecules by size left 5600-7700 fragment-sized molecules and 28,600-252,000 larger molecules per vendor. Compound properties of the fragment sets (MW, polar surface area, number of hydrogen bond donors and acceptors, etc.) are summarized for each of the vendors, similarly to Chris Swain’s analysis. Six different algorithms were then tested to find sets of 200 fragments that would best represent the entire collection. In accordance with Murphy’s Law, the most complicated algorithm proved to be the most effective; it involves an iterative selection procedure with precisely defined similarity criteria. Still, this algorithm is not too difficult to implement, and it should prove a useful tool for selecting fragments from larger sets of commercial or in-house compounds.

Finally, a chapter by James Na and Qiyue Hu at Pfizer in a recent volume of Methods in Molecular Biology gives a broad overview of fragment library design. In addition to general considerations, the paper succinctly summarizes the design of the Pfizer Global Fragment Initiative as well as an earlier fragment library designed specifically for NMR screening. A more lengthy but instructive description of several Vernalis fragment libraries is also provided, as are some of the screening results. Finally, a nice table summarizes fragment libraries from more than a dozen companies.

First fragment-based drug approved

2011-08-17T12:47:00.000-07:00

Today marks history with the first FDA approval of a drug to come out of fragment-based screening. The drug is branded as Zelboraf (vemurafenib), but readers of this blog are probably more familiar with its previous name of PLX4032. Although widely expected to be approved, the FDA acted more than two months ahead of schedule. The drug targets a mutant form of BRAF and has received widespread media coverage because of dramatic clinical results showing that it extends life for patients with a particularly deadly form of skin cancer. FiercePharma has an article with links to several others.

The drug was discovered at Plexxikon and developed in partnership with Roche; Plexxikon was acquired earlier this year by Daiichi Sankyo. The PLX4032 story is a case study in how rapidly fragments can enable a program: initiated in Februrary 2005, it took just six years to reach approval. It’s also an example of starting with a profoundly unselective fragment and winding up with a very selective drug (see here for early discovery and here for characterization of PLX4032).

Although I claim no prescience, I did state back in 2008 that it would be nice if a fragment-based drug would be approved by 2011. But more importantly, it is worth pausing to remember that this is a victory not just for the field of fragment-based drug discovery, but for those patients afflicted with metastatic melanoma. In the end, that’s what this is all about.

Fragment selectivity

2011-08-12T07:38:00.000-07:00

A constant debate in fragment-based lead discovery is whether to focus on fragments that are selective for the target of interest. Because fragments have lower complexity than larger molecules they are likely to be less specific – that is, after all, one of the main arguments for why a small set of fragments can explore more chemical space than a much larger set of lead-like molecules. But does it make sense to prioritize those fragments that are more selective? In a recent issue of J. Med. Chem. Paul Bamborough and colleagues at GlaxoSmithKline address this question experimentally.

The broad family of kinases was chosen for the investigation. Protein kinases in particular have been a rich field for drug development, including fragment-based methods. The researchers assembled a library of 1065 commercially available fragments, most of which were designed to bind to the so-called “hinge” region of protein kinases where the substrate ATP binds. Of these fragments, 936 passed quality-control and maintained stability over the course of the year-plus study.

The researchers screened these fragments at 0.4 or 0.667 mM against a panel of 30 kinases using several different assay formats: FP (fluorescence polarization), IMAP (immobilization metal affinity phosphorylation), LEADseeker (a scintillation proximity assay), and TR-FRET (time-resolved fluorescence resonance energy transfer). Various experiments suggested that FP was most susceptible to assay artifacts, though the results were still usable.

17 of the fragments screened were chosen based on common fragment motifs in the literature. One example is adenine, a fragment of ATP, which of course is used by all kinases. Despite this universality, adenine actually showed surprising specificity, inhibiting some kinases strongly and not inhibiting others at all. The same goes for other hinge-binding fragments that we’ve seen before (such as indazole). On the other hand, biaryl urea fragments designed to bind to the less-conserved adaptive pocket of kinases were quite selective, hitting just 2 kinases strongly.

Of course, especially for kinases, the trick is not getting fragment hits but in figuring out which ones to pursue. Ligand efficiency is often used to prioritize fragments, but is this necessarily a good idea? The researchers compared published high-affinity inhibitors of several kinases with fragments contained within these inhibitors and found that the fragments often would not have stood out above the pack when compared solely on the basis of ligand efficiency. Even spookier, many of the most ligand-efficient fragments appear to be assay artifacts.

What about selectivity? Are non-selective fragments bound to become non-selective leads? The authors present one example of a rather non-selective fragment that could be optimized to a highly selective molecule; PLX4032, which started life as a promiscuous azaindole, is another example.

These are just anecdotes though, so to get a broader handle on this question the authors examined a set of 577 lead-like compounds that had been screened against 203 kinases. This led to a list of 592 matched pairs of lead-like compounds and fragment substructures (most of which are likely hinge-binders) which could be analyzed for selectivity. The results recapitulate a smaller, earlier study performed with a very different data set. As Bamborough et al. put it:

It is not uncommon to find selective lead-sized compounds based upon unselective fragments. Equally, unselective leadlike compounds are frequently based upon selective fragments. It seems that the property of selectivity need not be maintained between fragments and their related lead-sized molecules.

On one level, Bamborough’s study is a bit discouraging: fragment selectivity should be used cautiously if at all in prioritizing fragments. Even ligand efficiency should not be gating; last year we discussed how a fragment with relatively modest ligand efficiency was transformed into the clinical-stage (and more ligand efficient) Hsp90 inhibitor AT13387. Other factors, such as structural novelty or how amenable a fragment will be to further elaboration, are just as if not more important for choosing fragments. All of which serves to reemphasize the fact that drug discovery is less a series of hard and fast rules than a loose system of guidelines and hunches. This lack of predictability is part of what makes the process so frustrating – and fun.

Fragment-based events in 2011 and 2012

2011-08-07T11:09:00.000-07:00

If you missed the fragment events earlier this year there is still one late addition to the calendar as well as some webinars. And it’s not too soon to be thinking about 2012!

August 16: Is your travel budget limited? Emerald Biosciences is putting together a series of free webinars related to FBLD on August 16, September 20, October 18, and November 15.

October 21: Zenobia Therapeutics is putting together a FBLD conference in San Diego. Although just one day, there is a nice lineup of speakers, so try to make it if you can.

2012

March 19-23: Keystone Symposium: Addressing the Challenges of Drug Discovery – Novel Targets, New Chemical Space and Emerging Approaches will be held in Tahoe City, CA. Although not exclusively devoted to fragments, there are many speakers I look forward to hearing.

April 17-19: Cambridge Healthtech Institute’s Seventh Annual Fragment-Based Drug Discovery will be held in San Diego. You can read impressions of this past year’s meeting here and 2010’s here.

September 23-26: FBLD 2012, the fourth in an illustrious series of conferences, will be held in my fair city of San Francisco. This should be a biggy – the first such event in the Bay Area (and the weather in September is usually decent too). You can read impressions of FBLD 2010 and FBLD 2009.

Know of anything else? Organizing a fragment event? Let us know and we’ll get the word out.

Ligand efficiency metrics poll results

2011-08-03T06:42:00.000-07:00

Poll results are in, and not surprisingly, ligand efficiency (LE) comes out on top, with 86% of respondents using the metric. What was a surprise to me is how many folks use ligand lipophilic efficiency (LLE) (46%). Coming in a distant third at 15% is LLEAT, but given that this metric was just reported it has a pretty strong showing, and I wouldn't be surprised to see this increase. Binding efficiency index (BEI) comes in fourth with 12% of the vote, and Fsp3 is tied with "other" with 8% of the vote. The other metrics only received one or two votes each.
Since people could vote on multiple metrics, there were more responses than respondents. Subtracting those who voted for "none" leaves 124 data points, suggesting that the average researcher is using 1.9 of these metrics (though unfortunately we don't have information on the median user).

Finally, for the 5 of you who selected "other", what else is out there that we've left out?

Fragments vs RNA revisited: the power of two

2011-07-30T13:07:00.000-07:00

RNA can assume complex three-dimensional structures just like proteins, and given the many roles it plays it is perhaps surprising that there are so few drugs that target this class of biomolecules. One problem is that ribonucleic acids are less diverse than amino acids, so there is less scope for developing small molecules that bind to specific regions of RNA. Nonetheless, a few brave souls have tried, some using fragment-based approaches. The latest such effort appears in J. Mol. Biol.

The researchers, led by Gabriele Varani of the University of Washington, Seattle, took a two-step approach to find two fragments that could simultaneously bind to the TAR element of HIV-1, a short stem-loop element essential for viral replication. The protein that normally binds to TAR contains a critical arginine residue, so the researchers started by purchasing a set of 16 arginine mimetics and using NMR to determine if any of them bound to TAR RNA. Several did, and one guanidine-containing molecule (MV2003) gave a strong NMR signal and also contained a hydrophobic element. The researchers decided to use this to hunt for a second fragment.

To find the second binder, the team screened 250 generic (ie, not targeted to RNA) fragments from Maybridge in pools of 5-8 in the presence of the first fragment. Remarkably, saturation transfer difference (STD) experiments, which detect changes in ligand NMR signals upon binding to macromolecules, suggested that more than 100 of these generic fragments appeared to bind to TAR RNA. However, more careful study of 20 representative fragments from 13 different scaffolds rapidly winnowed the set: 5 didn’t repeat when tested outside the pool, 6 gave signals in the absence of RNA, and 3 were not dependent on the presence of MV2003, suggesting that they bind nonspecifically. However, the remaining 6 only produced signals in the presence of both TAR RNA and MV2003, indicating a specific ternary complex. Although two of these fragments contain a (positively charged) primary amine, the rest are likely either neutral or only partially protonated at physiological pH. Interestingly, one of these is closely related to an RNA-binding fragment identified in previous work by a different group.

Next, the researchers constructed a model of how MV2003 bound to RNA. They used NMR data (nuclear Overhauser effects, or NOEs) to determine which atoms of MV2003 were close to which atoms of TAR RNA. Unfortunately no intermolecular NOEs were observed between any of the six fragments and the RNA, but it was possible to observe interligand NOEs (ILOEs) between the fragments and MV2003, and this enabled additional modeling suggesting that the fragments bind in a small pocket that only forms when MV2003 binds to RNA.

The paper ends with a cliff-hanger:

The formation of a new binding pocket allows binding of other fragments and suggests that more powerful ligands can be generated by linking the fragments together.

Although fragment linking is easier said than done, the hydrophobic moiety in MV2003 may improve the odds here, as described in the previous post. Practical Fragments hopes they will give it a shot!

Fragment linking: oil and water do mix

2011-07-25T07:27:00.000-07:00

Fragment linking is one of the most seductive forms of fragment-based lead discovery: take two low-affinity binders, link them together, and get a huge boost in potency. But what’s appealing in theory is difficult in practice: the linked molecule rarely binds more tightly than the product of the fragment affinities, and sometimes there is not even an improvement over the starting fragments. In a recent paper in Molecular Informatics, Mark Whittaker and colleagues at Evotec suggest a strategy to maximize the chance of success.

The researchers start by briefly reviewing nine published examples of fragment linking where affinities for both fragments as well the linked molecule are provided (some of these have been discussed previously here, here, and here). Of these, only three examples showed clear superadditivity (in which the linked molecule has a significantly higher affinity than the product of the affinities of the individual fragments), and two of these examples are rigged systems in which a molecule already known for its potency (such as biotin) is dissected into fragments. The challenges of linking are succinctly summarized:

The keys to achieving superadditivity upon linking are to maintain the binding modes of the parent fragments, not introduce both entropy and solvation penalties while designing the linker, and also make any interactions with the intervening protein surface that need to be made.

Also, of course, the resulting molecule needs to be synthetically accessible. Having a certain amount of flexibility in the linker can be useful, as this will allow the fragments some room to shift around, but too much flexibility introduces an entropic cost that defeats the purpose of linking in the first place. Software tools such as those by BioSolveIT can help design the linker, but what if some fragments themselves are inherently better suited for linking?

All three of the examples that show superadditivity start with one fragment that is highly polar and makes hydrogen bonds or metal-mediated bonds with the protein. The researchers suggest that such fragments are likely to pay a heavy thermodynamic penalty when they are desolvated, and that this cost can be reduced by linking them to a hydrophobic fragment. Thus, to maximize your chances of successful linking, the authors suggest you should choose
a fragment pair that consists of one fragment that binds by strong H-bonds (or non-classical equivalents) and a second fragment that is more tolerant of changes in binding mode (hydrophobic or vdW binders).

This is an interesting proposal, though because there are so few examples it is hard to assess. Indeed, the only other case of clear superadditivity I found involves dimerizing a fragment that is reasonably hydrophobic (ClogP = 2.4), albeit negatively charged. Hopefully we’ll see more examples in the coming years, but in the meantime, linking a water-loving fragment to an oily one is worth a shot.

Who's doing FBLD in 2011?

2011-07-14T06:55:00.000-07:00

It’s been almost two years since our last attempt at cataloging companies doing fragment-based lead discovery. That list contained 19 entries, and 5 others were mentioned in the comments section. A paper just published online by Phil Hajduk and colleagues at Abbott in J. Comput. Aided Mol. Des. provides another list of 19 companies, which has inspired Practical Fragments to combine the two to provide what we hope is the most comprehensive list of companies working in FBLD. (The paper itself is worth reading too for insights into how fragment screening has evolved. For example, Abbott pioneered the use of NMR for finding and characterizing fragments, but now functional screening, modeling, and X-ray crystallography are dominant.)

Companies doing FBLD:

Abbott Laboratories
Ansaris (previously Locus)
AstraZeneca
Astex
Beactica
BioFocus (Galapagos)
BioLeap
Biosensor Tools
BioSolveIT
Boehringer Ingelheim
Carmot Therapeutics
Crelux
Crown Biosciences
Crystax Pharmaceuticals (web site seems down - are they still around?)
Eli Lilly
Emerald BioStructures (from deCODE)
Evotec
Genentech (Roche)
Genzyme (Sanfi-Aventis)
GlaxoSmithKline
Graffinity Pharmaceuticals (NovAliX)
iNovacia
IOTA Pharmaceuticals
Johnson & Johnson
Kinetic Discovery
MEDIT
Merck
Nerviano Medical Sciences
NovAliX
Novartis
Pfizer
Pharma Diagnostics
Plexxikon
Polyphor
Proteros
Pyxis Discovery
Roche
Schrodinger
Selcia
Sprint Bioscience
Structure Based Design
Vernalis
Zenobia Therapeutics
ZoBio

Unlike the previous list, this one also includes large pharmaceutical companies known to be active in FBLD. Companies that have been acquired or merged are listed separately if they maintain separate web sites. The list excludes companies solely focused on selling fragment libraries, as these are covered separately.

The current list includes some 44 companies, which illustrates how widespread FBLD has become. The continuity is also encouraging: despite the challenging economic environment of the last few years, aside from a few acquisitions, a name change, and a spin-off, all the companies from the 2009 list are still around (with the possible exception of Crystax).

I’m sure the list is still incomplete, so if you know of someone else please add them to the comment section.

Biolayer interferometry (BLI)

2011-07-07T07:20:00.000-07:00

Surface plasmon resonance (SPR) has become a primary tool for finding fragments. One of its attractions is that, in addition to requiring only small amounts of protein, it can provide dissociation constants (Kd values) and, for tighter binders, on-rates and off-rates. However, SPR is not the only biosensor-based technology out there. Biolayer interferometry is a related technique, and, as judged by the discussion following the FBLD 2010 meeting, is clearly of interest to many people. A paper published online by Charles Wartchow and colleagues in J. Comput. Aided Mol. Des. provides a description of the technology and comparison with other methods.

Like SPR, BLI requires immobilization of the protein target to a surface; the current paper uses biotin-labeled proteins and streptavidin coated biosensors from ForteBio. Unlike SPR, the technology does not rely on samples flowing through tiny capillaries, and up to 16 protein-labeled sensors can be simultaneously dipped directly into different solutions of small molecules arrayed in a 384-well plate. BLI relies on changes in the interference pattern of light between the sensor and the solution caused when a small molecule binds to a protein on the surface of the sensor.

In the current study, the authors studied three proteins: Bcl-2, JNK1, and eIF4E. Initially a library of 140 fragments was screened in triplicate at 200 micromolar concentration against each of the three targets. Both JNK1 and Bcl-2 gave very high hit rates (24 and 21%, respectively), but eIF4E gave a much more “fragment typical” hit rate of 3.5%. This protein was subsequently screened against 6500 compounds, a task which required 1 mg of protein, 10 days, and 700 sensors (which needed to be periodically replaced throughout the campaign).

After curating the eIF4E hits to remove compounds that gave anomalously high signals or slow off-rates, the remaining molecules were then retested in a second screen, which confirmed 50% of the remaining hits, for an overall hit rate of 1.3%. However, many of these still looked suspicious when they were tested in 8-point titration curves; it seems that, like SPR, BLI is also prone to false-positive problems.

The researchers also ran biochemical and SPR screens on some of the targets. For eIF4E, the overlap between hits coming from BLI and those from biochemical screens was 52%, though many of these are derivatives of a single scaffold. Another subset of the common hits gave non-ideal behavior, calling into question their mechanism of action. It remains unclear whether the BLI hits that were not active in biochemical assays are real, and if so, relevant.

In the end, the authors conclude that:

These fragment screening studies demonstrate that BLI is suitable for small molecule characterization and fragment screening.

But they continue:

Hit assessment… with BLI and SPR is non-trivial, however, and although numerous hits from the BLI, SPR, and biochemical assays were characterized, most of the BLI and SPR data obtained from the examination of a concentration series in the micromolar range showed linear relationships with respect to concentration, unreasonably high signals, or slow off-rates.

Clearly, like all techniques, one should not rely on BLI alone. What remains to be seen is whether BLI has advantages over related techniques such as SPR, whether in terms of speed, sensitivity, resistance to artifacts, or cost. Several of the authors of the paper are from Roche, but the paper does not make clear whether BLI is becoming integrated into the workflow there. Is anyone else out there using BLI? If so, what has been your experience?

How effectively can fragments sample chemical space?

2011-06-30T20:18:00.000-07:00

One of the key advantages of fragment-based drug discovery is that, since there are fewer fragments than lead-sized or drug-sized molecules, it is possible to sample chemical space far more efficiently with fragments than with larger molecules. At least, that’s the theory, but does is it hold true in the real world?

To put it another way, do fragments sample all of the space in which drugs are found? And what kinds of fragments are best for this sampling? In the most recent issue of J. Med. Chem., Stephen Roughley and Rod Hubbard of Vernalis address such questions.

The system they investigate, heat shock protein 90 (Hsp90), is an ideal model system: it is both a popular anti-cancer target as well as structurally tractable, and is thus arguably the most heavily explored single target in terms of fragment-based lead discovery. At least 8 antagonists have entered the clinic, of which at least 2 have come from fragments (see the posts on AT13387, NVP-BEP800/VER-82576, and posts on Evotec compounds discovered by fragment growing or linking.)

Vernalis has had a long-running fragment-based program targeting Hsp90, which has resulted in numerous fragments whose binding modes have been determined by X-ray crystallography. Roughley and Hubbard analyzed these fragments and compared them to published inhibitors. Just 5 distinct fragments can be mapped onto all of the clinical compounds: a handful of fragments effectively samples relevant chemical space. As the authors put it:

For Hsp90 at least, the fragments do cover an appropriate chemical space; what is then important is the imagination of the chemist in evolving the fragments into potent inhibitors.

The second point – about the imagination of the chemist – is critical. Mapping fragments onto elaborated molecules is easier to do retrospectively than prospectively; a cynic could argue that methane is a fragment of just about any drug out there. However, Roughly and Hubbard also point out that, particularly in cases such as this where there are many co-crystal structures, fragments can help identify bioisosteres, including cryptic ones that would not be obvious purely from studying functional SAR.

The paper also addresses the issue of optimal library design, in particular the dilemma of size. Although all five representative fragments were found in an initial set of just 719 fragments, subtle changes can dramatically change the binding mode, an issue we’ve touched on previously. It may not be practical to have multiple similar fragments present in a primary screening library, but testing close analogs after identifying initial fragment hits is likely to be worthwhile.

Finally, one of the concerns about fragment-based approaches is that, if everyone is buying the same set of fragments from the same suppliers and screening them against the same targets, they will end up in the same place – and stumbling over each others’ intellectual property. Reassuringly, this turns out not to be the case:

Even though the various companies discovered rather similar compounds from a fragment screen, exploiting similar binding motifs, there were no exact matches. [Also], the subsequent evolution of the fragments sometimes took very different paths and produced mostly very different chemical leads and candidates.

If this holds true for such heavily mined targets as Hsp90 (and kinases, as discussed previously) it should be even more true for newer classes of targets.

There is a wealth of information in this paper, and it is worth perusing, especially if you find yourself longing for some science over the long holiday weekend.

Ligand efficiency and related metrics (Poll)

2011-06-26T18:43:00.002-07:00

The discussion following the recent post on LLEAT got me thinking that metrics could be a good topic for a poll (see right side of page).

Click below to see definitions or references, and vote on the right side of the page. Note that you can choose multiple answers.
Antibacterial efficiency
Binding efficiency index (BEI)
Fit quality (FQ)
Fsp3
Ligand efficiency (LE)
Ligand-efficiency-dependent lipophilicity (LELP)
Ligand lipophilic efficiency (LLE)
LLEAT
%LE
Percentage efficiency index (PEI)
Surface-binding efficiency index (SEI)
Other
None

Also, if you use any additional metrics or want to be more specific about how or why you use (or don’t use) the above metrics, please comment.

Ligand Lipophilicity Efficiency AT Astex Therapeutics

2011-06-20T07:19:00.000-07:00

Our last post discussed the growing plague of molecular obesity, and how numerous metrics have been designed to control it. In a paper published online in J. Comput. Aided Mol. Des. Paul Mortenson and Chris Murray of Astex describe a new one: LLEAT.

Although ligand efficiency (LE) is probably the most widely used and intuitive metric, it does not take into account lipophilicity. Other indices do, notably ligand lipophilicity efficiency (LLE) and ligand-efficiency-dependent lipophilicity (LELP), but these both have drawbacks for evaluating fragments. LLE (defined as pIC50 – log P) is not normalized for size; for a fragment to have an (attractive) LLE ≥ 5 it would need an exceptionally low log P or an exceptionally high affinity. LELP, defined as log P / ligand efficiency, is also potentially misleading since a compound could have an acceptable LELP value even with a low ligand efficiency if the log P is also very low.

To address these problems, Mortenson and Murray have tried to strip out the non-specific binding a lipophilic molecule experiences when going from water to a binding site in a protein. They define this modified free energy of binding as:

ΔG* = ΔG - ΔGlipo
≈ RT ln (IC50) + RT ln (P)
≈ ln (10) * RT (log P - pIC50)

In order to put values coming out of this metric on the same scale as those from ligand efficiency, they add a constant, such that:

LLEAT = 0.11 – ΔG* / (number of heavy atoms)

Thus, just as in ligand efficiency, the goal is for molecules to have LLEAT ≥ 0.3 kcal/mol per heavy atom.

The index has some interesting implications. For example, the two fragments below have the same number of heavy atoms, and thus if they had the same activity they would have the same ligand efficiency; on this measure alone, neither would be preferred as a starting point for further work. However, because of their very different lipophilicities, fragment 2 would need to be 45 times more potent than fragment 1 in order to have the same LLEAT of at least 0.3.

A similar analysis can be done during optimization. For example, adding either a phenyl or a piperazinyl substituent should produce a 20-fold boost in potency in order to maintain ligand efficiency at 0.3, since both have 6 atoms. However, in order to maintain LLEAT at 0.3, the phenyl would need to produce a 460-fold boost in potency while the piperazinyl would need to improve potency only 3-fold. This is consistent with what other folks have reported qualitatively, but it’s nice to have a simple quantitative measure.

Although some people may groan at yet another index, and no metric is perfect, I like the fact that this one is intuitive and has the same range of “acceptable” values as ligand efficiency. What do you think – is it useful?

Beware molecular obesity

2011-06-12T12:56:00.000-07:00

Obesity in humans is a growing problem, and not just aesthetically: the condition may be responsible for millions of premature deaths. In a recent article in Med. Chem. Commun., Mike Hann of GlaxoSmithKline notes that “molecular obesity” is also leading to the untimely demise of far too many drug development programs.

Hann, who is especially known for his work on molecular complexity, defines molecular obesity as the “tendency to build potency into molecules by the inappropriate use of lipohilicity.” This is the result of an unhealthy “addiction” to potency. Hann suggests that since potency is easy to measure it is pursued preferentially to other factors, particularly early in a program. This is all too often achieved by adding mass, much of it lipophilic. The problem is that all this grease decreases solubility and increases the risks of off-target binding and toxic side effects.

Tools such as the Rule of 5 have been developed in part to avoid this problem, and a number of other indices have been introduced more recently. For example, lipophilic ligand efficiency (LLE) is defined as pIC50 – LogP; molecules with an LLE > 5 are likely to be more developable. Other guidelines that Hann mentions and that have been covered here include LELP, number of aromatic rings, and fraction of sp3 hybridized carbon atoms. But this is not to say that metrics will save the day:

The problem with the proliferation of so many “rules” is the trend to slavishly apply them without really understanding their required context for use and subsequent limitations.

Starting a program with the smallest possible lead should in theory lead to smaller drugs, and this is one of the key justifications for fragment-based approaches, though even here it is important that the molecules do not become obese during optimization. One of the themes at the 6th annual FBDD conference was to do a bit of optimization around the fragment itself before growing or linking. On a related note, Rod Hubbard warned in his opening presentation at the conference to “beware the super-sized fragment.” Not only are larger fragments likely to be less complementary to the target, the number of possibilities increases (and thus the coverage of chemical space drops) by roughly ten-fold with each atom added to a fragment.

Hann also argues that potency itself is over-rated: many teams seek single digit nanomolar binders even though approved drugs have average potencies of 20 nM to 200 nM.

The paper is a fun read (and is free after registration too). Also, Hann one-ups Donald Rumsfield’s (in)famous “known knowns, known unknowns, and unknown unknowns” by pointing out that much of this information falls into the category of “unknown knowns”:

Those things that are known but have become unknown, either because we have never learnt them, or forgotten about them, or more dangerously chosen to ignore

This review is an excellent corrective to the first two problems, and a clear warning about the third.

Perverse trade-offs: the maximal enthalpy of ligands

2011-05-30T12:04:00.000-07:00

Most readers of this blog are familiar with the concept of ligand efficiency:

LE = (free energy of ligand binding) / (number of heavy atoms)

The metric is easy to calculate, intuitive, and useful for evaluating fragments. Weirdly, as ligands get larger, the ligand efficiencies tend to decrease. This is a consequence of the fact that the maximal affinities of ligands also start to plateau as their sizes increase, a fact noted more than a decade ago by Kuntz and colleagues. The reason for this has never been satisfactorily explained, but the effect is so pronounced that some researchers have proposed alternatives to LE that take it into account, for example %LE and fit quality. In a paper published online in ACS Med. Chem. Lett., Charles Reynolds and M. Katherine Holloway have delved into the origins of declining LE with increasing size in more detail.

The researchers analyzed 102 ligand-protein complexes representing 14 target classes for which thermodynamic data had been collected using isothermal titration calorimetry (ITC). They calculated ligand efficiency as well as “enthalpy efficiency” and “entropy efficiency”, where enthalpy or entropy takes the place of free energy in the numerator. In the case of enthalpy efficiency, the trend was the same as for ligand efficiency: as molecules got larger, the enthalpy efficiencies tended to decrease. For entropy efficiencies, however, there was essentially no trend. In other words, the leveling out of binding energy is due to enthalpic effects more than to entropic effects. The authors suggest that:

The size effect on enthalpy is a result of increasing ligand complexity and the need to satisfy multiple geometric constraints simultaneously.

The findings thus provide further support for trying to identify fragments whose binding is largely enthalpically driven, but, as usual in the real world, things are not quite so easy. One of the frustrating things about medicinal chemistry is the phenomenon of enthalpy-entropy compensation: if you try to improve the enthalpy of binding, say by adding a hydrogen-bond acceptor, you may end up paying an entropic penalty such that overall binding increases only modestly, if at all. Indeed, the data in the paper show a very strong correlation between enthalpy and entropy: enthalpic binders tend to have negative (unfavorable) entropy, and the most entropic binders actually have positive (highly unfavorable) enthalpies of binding.

Worse, despite the striking correlation between enthalpy and entropy, there is almost no correlation between free energy of binding and enthalpy or entropy. The researchers suggest that these perverse trends (or lack thereof) explain why computational approaches to drug discovery are not more successful: most modeling relies on one or a few low-energy conformations, in effect ignoring entropy. However, there is a correlation between overall binding energy and enthalpy for certain targets, such as HIV protease and aldose reductase; perhaps such targets are more amenable to modeling.

In summary, the message seems to be that you should try to find enthalpic binders if you can, though the binding energetics may change unpredictably during optimization. For modelers, the research suggests that ignoring entropy is unwise. For medicinal chemists, I’m not sure how much of this is actionable, but sometimes it’s nice to know the origins behind the perversity of the universe.

Fragments vs Pim-1

2011-05-19T06:50:00.000-07:00

The three members of the Pim family of serine/threonine kinases help cancer cells proliferate and survive, and are thus interesting as potential anti-cancer targets. Structurally the kinases are also intriguing because they have a proline residue in the “hinge” region of the purine binding site, differentiating them from the other 500+ kinases in the human genome. Two recent papers describe different fragment-screening approaches against Pim-1: one case rediscovers fragments of a previously reported compound and the other identifies a new series of potent inhibitors unlike other reported kinase inhibitors.

In the first paper, published in Acta Cryst. Section D, researchers from Bayer Schering Pharma AG performed a crystallographic screen of just 36 fragments against Pim-1. Despite the small library size, a dozen of the fragments produced interpretable electron density, although only 4 of these showed activity better than 10 mM. Fragment 3, with an IC50 of 130 micromolar in an enzymatic assay, was the most potent. Interestingly, a close analog of this cinnamic acid fragment was also part of a Pim-2 inhibitor previously identified through HTS by a group from Boehringer Ingelheim. The Bayer folks synthesized this molecule (compound 1), confirmed that it is also potent against Pim-1, and found that, crystallographically, it overlays beautifully with the fragment.

The second paper, published in Bioorg. Med. Chem. Lett., describes how researchers at Genzyme used a fragment-based approach to develop potent Pim-1 inhibitors. The researchers used SPR to screen a library of about 1800 fragments at 75 micromolar concentration and then used a biochemical assay to characterize the active molecules. Benzofuran-2-carboxylic acids such as compound 10 (below) were particularly interesting: not only did they have high ligand efficiencies, they don’t look anything like typical kinase inhibitors. X-ray crystallography revealed that the bromine atom is binding in a hydrophobic pocket, while the acid is making hydrogen bond contacts with the catalytic lysine and other residues. A related fragment with comparable potency had a methoxy substituent in the 7-position, and by transforming this into a positively charged moiety the researchers were able to improve the potency to low nanomolar with a dramatic increase in ligand efficiency.

What’s also interesting is that if you overlay the two fragments from the two papers, they superimpose almost exactly on top of one another, with the carboxylic acid moieties making the same interactions – clearly a hot spot.

On a side note, as most readers are probably aware, sanofi-aventis has recently acquired Genzyme. Practical Fragments wishes all the folks in Massachusetts well during the integration.

Native MS: turning up the voltage

2011-05-16T07:43:00.001-07:00

At the FBDD meeting in San Diego last month there was some discussion of the connection between protein-ligand binding in the gas phase (ie, in native mass-spectrometry experiments) vs in solution; the discussion continued in the comment section here. Valerie Vivat, head of the mass spectrometry, molecular & cell biology department at NovAliX, has now provided a thorough response.

When analyzing non-covalent complexes by mass spectrometry under non-denaturing conditions, one must keep in mind indeed how interactions stabilizing the complex in solution will be affected by the ion transfer in the gas phase. Basically, interaction based on hydrophobic effect is lost while the electrostatic-based interactions (Van der Waals, H-bonds, ionic interaction) are preserved (and are even strengthened due to the absence of solvent shielding). Regarding water molecules now, during the ESI process, biomolecules are transferred in the gas phase as partially hydrated ions and complete ion desolvation is subsequently achieved through low energy collisions with the residual gas molecules in the mass spectrometer interface. This complete desolvation is required for accurate mass measurements. Consequently, in most cases, molecular mass measurement of the complexes is accurate enough to rule out the possibility that water molecules remain after ions are transferred from the atmospheric pressure to the deep vacuum of the TOF analyzer, even in the case of crystallographic water molecules.

Regarding gas phase stability : Reports in the literature mention that collision-induced dissociation experiments and the determination of Vc50s can be used to monitor gain or loss in polar interaction. Indeed, we have now accumulated a variety of in house examples showing that increase in the gas phase stability of a complex is correlated with a gain in polar interactions as shown by X-ray or ITC. Monitoring the complex gas phase stability is thus an attractive feature to quickly evaluate, for example, gain or loss in polar interaction of analog series targeting the same protein binding site.

Importantly, the gas phase stability is not an indication of the complex binding affinity. Evaluation of complex affinity (after complexes are formed in solution) is done under instrumental conditions showing no dissociation of the non-covalent complexes. For complexes stabilized by electrostatic-based interactions (and thus rather stable in the gas phase), it is indeed much easier to find optimal instrument settings compared to complexes stabilized by hydrophobic effect. However, this does not preclude complexes mainly stabilized in solution by hydrophobic effect to be detected at all. For example, nuclear hormone receptors in complex with fatty acids or phospholipids are readily detected with appropriate settings. In this case, the polar head of the ligands is likely to act as a stable anchor in the gas phase, resulting in non-covalent complexes which remain intact during the ca. 1 millisecond flight of the ion from the ionization source to the detector.

To sum up, native MS can be run under two different modes:

1. Low energy conditions where no complex dissociation occurs are used to assess the binding affinity of protein / ligand complexes,

2. High energy conditions inducing complex dissociation provide insight into the extent of polar interaction involved between the protein and the ligand. This type of experiment makes sense to compare a series of molecules binding to the same protein binding site.

Valerie makes some interesting points here, in particular the statement that "the gas phase stability is not an indication of the complex binding affinity." Still, I do like the fact that native MS could be used as a quick way to sort enthalpic from entropic binders. What do you think?

Fragments vs ion channels

2011-05-11T07:32:00.000-07:00

Ion channels represent an intriguing class of targets for a variety of indications, but it is difficult to develop robust high throughput assays. The gold standard is to actually measure the electrical conduction of the channels using techniques such as patch clamping, but this is time-consuming and tedious. Unfortunately, faster indirect methods are prone to high rates of false positives. Medium throughput automated patch clamp technologies are now available, and in a recent issue of Bioorg. Med. Chem. Lett. Scott Wolkenberg and colleagues at Merck decided to use one of these for a fragment screen.

The researchers screened 1280 fragments against the sodium ion channel acid-sensing ion channel 3 (ASIC3), a potential target to treat pain. Compounds were screened at 1 mM concentration, and 56 of them inhibited >50%. Interestingly, this 4.4% hit rate is comparable to other fragment screens at Merck on completely different target classes. Dose-response curves were generated for the 56 compounds, yielding 32 hits in 12 separate chemical series with ligand efficiencies > 0.3. Similarity searching led to the testing of 250 analogs, but most of these were less active than the original fragments.

In the absence of structural information, two strategies were used to try to improve the potencies. First, a series of 220 analogs were synthesized in which small (approximately 64 mass units) substituents were systematically added at various positions around the fragments. Unfortunately, most of the compounds were inactive, and those that were active were only marginally better than the starting fragment. The second strategy was to make more dramatic changes using parallel chemistry of up to a few hundred compounds. This was more successful: for example, fragment 3 led to compound 24, with 200-fold improved activity, albeit with a loss in ligand efficiency.

Unfortunately the best compounds reported still do not break the micromolar barrier, and the pharmacokinetics are not encouraging. The authors conclude that:

The present results are consistent with the analysis that advancing fragment hits to high potency (<100 nM) and/or to a preclinical development milestone in the absence of structural information is unlikely.

I think this may be overly pessimistic. While optimizing fragments in the absence of structure is certainly challenging, it is possible. Fragment screening ultimately delivered several distinct series of low micromolar compounds against ASIC3. Had these come from an HTS assay, the job of optimizing them further would not be any easier. Moreover, this report represents another example of using fragment approaches to tackle membrane proteins.

Not fragments versus DOS, fragments from DOS

2011-04-29T07:24:00.000-07:00

A few months ago we highlighted a forum in Nature comparing fragment-based lead discovery with diversity-oriented synthesis, or DOS. This was quite a vigorous debate and was covered on our sister blog as well as In the Pipeline and second messenger. Personally I’ve never been a this or that kind of guy – more of a this and that – so it is refreshing to see a paper in this week’s issue of PNAS describing a DOS approach to building fragments.

Damian Young and colleagues at Harvard and the Broad Institute, ground zero for DOS, noted that many commercial fragments contain a sizable percentage of sp2 carbons: aromatic rings, for example. Because a larger number of aromatic rings correlates with lower solubility and higher attrition in lead development, the researchers focused on using DOS to generate fragments that would have a higher fraction of sp3 carbons at the expense of sp2 carbons. They used a “build/couple/pair” approach, in which chiral “building blocks” (in this case proline derivatives) were “coupled” to another building block and then functional groups were “paired” to generate bicyclic molecules. The result was about three dozen fragments.

So how do they look? Actually, not so bad. Superficially they all resemble one another, but because they contain up to three stereocenters they cover quite a bit of chemical space while still conforming to the rule of 3. Significantly, they are in fact more three-dimensional than commercially available fragments (from ZINC) having the same molecular formula or the same set of calculated physical properties (molecular weight, cLogP, number of hydrogen-bond donors and acceptors, etc.). The DOS fragments contain a larger fraction of methyl esters and carboxylic acids than I would want to see in a library overall, but this was intentional, and none of them are downright ugly.

Unfortunately the paper provides no screening data, so it is anyone’s guess whether any of the fragments will turn out to be active. Still, the approach is likely to probe new areas of chemical space. Hopefully some of the commercial purveyors of fragments will start making and selling these types of molecules.

Ligandability

2011-04-23T18:20:00.000-07:00

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

2011-04-15T07:17:00.001-07:00

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.

Wedding announcement: SuperGen and Astex

2011-04-07T19:59:00.000-07:00

It’s wedding season in the world of fragments – last month we noted the merger of Daiichi Sankyo and Plexxikon, and today SuperGen and Astex Therapeutics announced that they are tying the knot. Unfortunately the “dowry” in this case is considerably smaller: SuperGen will pay Astex shareholders $25 million cash upfront, with an additional $30 million in deferred payments. Astex shareholders will, however, still retain 35% equity in the combined company.

Astex has long been a leader in fragment-based drug discovery, having taken at least three programs from fragments to clinical compounds (see blog entries on AT13387, AT9283, and AT7519). Perhaps it is in recognition of this that the combined entity will be called Astex Pharmaceuticals. Practical Fragments wishes everyone involved the best of luck.

Fragments in vivo

2011-04-01T06:36:00.000-07:00

The number of ways to find fragments just keeps growing. A few weeks ago we discussed WAC, which takes its place alongside ITC, SPR, MS, TINS, and more traditional methods such as NMR, X-ray and biochemical screening. However, all of these approaches are somewhat reductionist, relying on isolated target proteins. In an effort to bring the whole organism into the picture, our friends at the University of Shutka, Russia, have come up with an approach they call “Fragments in Bodies,” or FIB.

The researchers have assembled a collection of very small fragments, purchased for the most part from Lilliput Pharmaceuticals. These are then screened in mouse models to look for positive phenotypic effects.

The researchers face some unique challenges. For example, it is difficult to measure changes in body mass as the animals need to consume such large amounts of fragments that they can become somewhat bloated. Still, if the animals can be safely dosed with massive amounts of micro-molecules, "FIB"ing could provide very good starting points for further work!

Methods in Enzymology: Fragment-Based Drug Design

2011-03-29T06:34:00.000-07:00

In addition to dozens of reviews on fragment-based drug discovery, entire books have been published, the first in 2006 and the second in 2008. Now a third has joined the list: Volume 493 of the venerable Methods in Enzymology series, edited by Lawrence Kuo at Johnson & Johnson, is titled Fragment-Based Drug Discovery: Tools, Practical Approaches, and Examples. With 21 chapters and roughly 600 pages, it is a comprehensive addition to the field. Whether you’re just starting out in the field of fragments or already an expert, this is an invaluable resource.

As the subtitle suggests, the book is divided into three sections. The first, Tools, is the shortest, consisting of just 6 chapters. Chapter 1, by Brett Tounge and Michael Parker, describes how they assembled a 900 fragment library at Johnson & Johnson for use in crystallography-based screening. Chapter 2, by Gaetano Montelione and colleagues, discusses the high-throughput protein preparation approach that the Northeast Structural Genomics Consortium has taken, including advice on what to do when problems arise. The next two chapters are devoted to crystallography: Jark Böttcher and colleagues from Proteros Biostructures provide a general overview including practical tips in Chapter 3, while Doug Davies and colleagues from Emerald BioStructures analyze the results of 18 in-house campaigns to try to draw general conclusions of why some targets are more successful than others in Chapter 4. On the subject of difficult targets, Chapter 5 is devoted to GPCRs, specifically the stabilized versions being generated by Miles Congreve and coworkers at Hepatares Therapeutics and analyzed by SPR and TINS NMR in collaboration with researchers at the University of Utah and ZoBio. Finishing out this section, Renee DesJarlais of Johnson & Johnson provides an overview and practical tips for applying computational approaches to FBDD.

The second section, Practical Approaches, begins with a chapter by Lawrence Kuo on how to ensure that hits from fragment screens will be distinct from those coming out of HTS. Chapter 8, by Tony Gianetti at Genentech, is a valuable and comprehensive tutorial on using SPR for fragment screening. The next two chapters are devoted to NMR: Chapter 9, by Christopher Lepre at Vertex, discusses such practicalities as library preparation and NMR screening conditions, while Chapter 10, by Joshua Ziarek and colleagues at the Medical College of Wisconsin provides more detail on specific NMR techniques. The following two chapters discuss a couple less common techniques. Chapter 11, by James Kranz at GlaxoSmithKline and Celine Schalk-Hihi at Johnson & Johnson, gives an excellent description of the protein thermal shift technique for identifying and characterizing fragments, complete with all the mathematics. And Chapter 12, by Lars Neumann and colleagues at Proteros Biostructures, describes the reporter displacement assay and its use to select for fragments with desirable kinetic and thermodynamic profiles. In Chapter 13, John Spurlino of Johnson & Johnson describes crystallography-based fragment screening and advancement without collecting affinity data; this was recently discussed here, but the chapter provides additional details and examples. Finally, the last chapter in this section, by Zenon Konteatis and colleagues at Ansaris, discusses the incorporation of protein flexibility into computational fragment-based screening.

The last section, Examples, opens with a chapter by Masaya Orita and colleagues at Astellas that covers ligand efficiency and related indices and an overview of strategies to advance fragments, with a particular emphasis on “anchor-based drug discovery.” Chapter 16, by James Lanter and colleagues at Johnson & Johnson, emphasizes the importance of engaging medicinal chemists in fragment projects from an early stage. In Chapter 17, Hugh Eaton and Daniel Wyss at Merck describe using NMR in FBDD both in general terms and with respect to their BACE1 program, which has entered clinical trials. Chapter 18, by Till Maurer at Genentech, is also devoted to NMR, focusing on the specific steps involved. Chapter 19, by Marta Abad and colleagues at Johnson & Johnson, returns to crystallography, further discussing the electron-density guided FBDD approach in the context of the target ketohexokinase. In Chapter 20, Rod Hubbard and James Murray discuss a decade of fragment work at Vernalis, integrating many of the techniques discussed in the rest of the volume (as well as a few new ones!) and providing a valuable discussion on why orthogonal biophysical fragment-finding methods are necessary. The book closes with a chapter by Darren Begley and colleagues at Emerald BioStructures and collaborators at the University of Washington on a structural genomics initiative to use crystallography-guided methods to tackle proteins important in infectious diseases.

Although each of these chapters can be downloaded individually, it is well worth getting a copy of the book itself. Like other members of the series, it is beautifully put together. Having all the papers in one place is extremely convenient, and simply paging through the volume is bound to generate new ideas.

Fragments vs. PDK1 again: into the adaptive pocket

2011-03-22T19:47:00.000-07:00

PDK1 holds a certain appeal for fragment-based approaches. This kinase, an upstream member of the phosphatidylinositol-3 kinase (PI3K) signaling pathway, is an attractive anti-cancer target and has been successfully targeted using FBDD by researchers at Vernalis and GlaxoSmithKline (see here for a very recent publication). A series of allosteric activators was also discovered by researchers at Pfizer. The latest report on this target, an inhibitor which is particularly potent against the unphosphorylated form of PDK1, was just published online in Bioorg. Med. Chem. Lett.; it describes some of the work my colleagues at Sunesis and I did in collaboration with researchers at Biogen Idec.

To find inhibitors against PDK1, we used Tethering with extenders. This approach starts by covalently modifying a protein of interest with an “extender,” which is a fragment designed to bind in a desired site on a protein and to capture other fragments; it contains a protein-reactive functionality as well as a masked thiol. In this case, we used a generic fragment known to interact with the purine-binding pocket of kinases, a diaminopyrimidine (red in upper left of figure). The protein-extender complex was then screened against a library of several thousand disulfide-containing fragments under partially reducing conditions; only fragments with some affinity for the protein will remain covalently bound to the protein and thus be detectable by mass-spectrometry. The pyridinone (blue in figure) was one of the strongest hits.

We synthesized several molecules containing purine-pocket binding elements connected to pyridinones by flexible linkers and found compound 25 to be one of the most potent. The SAR revealed the importance of a hydrogen-bond donor-acceptor pair (green atoms in figure) a specific distance from the pyridinone fragment, and further medicinal chemistry led ultimately to compound 33. In addition to being quite potent, compound 33 was remarkably selective for PDK1: in a panel of 241 kinases screened at 10 micromolar concentration of compound 33, only PDK1 and one other kinase were inhibited by 80% or more.

The selectivity of compound 33 was partially explained by the X-ray crystallographic structure, which revealed that the pyridinone fragment discovered through Tethering binds in the so-called adaptive pocket with the activation loop in the “DFG-out” conformation. I believe this is the only series of inhibitors for which this binding mode has been observed for PDK1. Consistent with the structure, these inhibitors are more potent against the unphosphorylated (inactive) form of PDK1 than against the phosphorylated (active) form.

Compound 33 was effective at preventing phosphorylation of the PDK1 substrate Akt both in cells as well as in a xenograft model. Though I may be biased in thinking so, this is a nice application of a fragment-based approach to discover a strikingly specific kinase inhibitor. I hope that people will use compound 33 to further probe the biology of the PI3K pathway. Indeed, at least one completely independent team of researchers seems to already be doing so.

Weak affinity chromatography (WAC)

2011-03-18T07:17:00.000-07:00

There are many ways to find fragments: NMR and X-ray crystallography are old favorites, but SPR is quickly catching on. There are also more specialized approaches, such as ITC, MS, TINS, and biochemical screening. Now another 3-letter abbreviation has joined the list: a paper published online by Sten Ohlson and colleagues at Linnaeus University in Sweden in Analytical Biochemistry describes weak affinity chromatography, or WAC.

The principle is remarkably simple. First, a protein of interest is covalently immobilized onto a chromatography column packed with modified silica gel. This can be done on a standard high-performance liquid chromatograph (HPLC). Then each fragment to be tested is injected in buffer; those that have affinity for the immobilized protein will stay on the column longer than they would if they lacked affinity. The fragments can be detected with either UV spectrometry or mass spectrometry.

To demonstrate the technique, the researchers used two model enzymes, thrombin and trypsin, and a couple dozen fragments ranging in mass from 93 to 307 Da. Most of these fragments contained an amidine, a moiety known to bind to both proteins. Columns without any immobilized protein served as controls. Of course, fragments may associate non-specifically with proteins, so the researchers also treated protein-containing columns with irreversible or potent reversible inhibitors; a fragment that comes out later from a column containing an active protein than from a column containing an inactive protein is presumably binding specifically to the active site.

Remarkably, the technique appears to work: most of the amidine-containing fragments were retarded in columns containing active protein compared to columns containing inhibited protein. Moreover, the relative affinity ranking correlated with the inhibitory activity of fragments in enzymatic assays. Some of the fragments were quite weak, with calculated dissociation constants around 1 mM.

The researchers also demonstrated that they could screen a mixture of 11 fragments, using mass-spectrometry to follow each fragment, and that the change in retention time was comparable to that observed when running each fragment individually. In this case it was important to use low fragment concentrations so as to avoid saturating the protein active sites.

As with any technique, there are bound to be limitations. The immobilized protein needs to be stable for an extended time; in the current case there was some degradation in performance, albeit over the course of months and more than 200 injections. A more serious constraint is the need for a proper reference. Inactivating an enzyme provides an ideal solution, but one that won’t be so easily generalized to all targets.

In some ways WAC could be seen as a low-price cousin of TINS: both methods rely on an immobilized protein, but while TINS uses a custom modified NMR spectrometer, WAC can get by with a much less pricey HPLC (though a mass-spectrometer seems nearly indispensible). It will be fun to see how WAC develops, and in particular whether it can be used to discover novel fragments against more challenging targets.

Growing into closed pockets

2011-03-10T07:23:00.000-08:00

Fragment-growing is a popular way to increase the activity of fragments, all the more so when there is an obvious place towards which to grow. In a paper published online in the J. Am. Chem. Soc., Iwan de Esch and colleagues at VU University Amsterdam describe the structural and thermodynamic consequences of one such effort, and conclude that binding in a certain normally closed pocket is enthalpically rather than entropically driven.

The researchers were interested in acetylcholine-binding protein (AChBP), a soluble and crystallizable homolog of an important class of ligand-gated ion channels. This is the same protein (and the same group) highlighted last year in the context of ligand efficiency hot spots. In the current work, a fairly potent fragment, compound 1, was co-crystallized with AChBP and the structure solved. This fragment binds in roughly the same position as the more potent natural product lobeline (compound 2), but lobeline contains a hydroxyphenethyl group that the fragment lacks (see figure). This moiety binds in a hydrophobic pocket that does not appear in the fragment complex due to the movement of a tyrosine residue. Recognizing the potential for the pocket to form, the researchers introduced this moiety into their own molecule, producing compound 3.

Gratifyingly, compound 3 binds about 50-fold more tightly than the initial fragment. This molecule was also co-crystallized with AChBP, and, as designed, the phenyl group binds in the “lobeline pocket". Moreover, compound 3 does not show a corresponding increase in affinity towards a version of AChBP from a different organism that does not have this pocket.

To correlate binding mode with thermodynamics, the researchers also characterized the binding of their compounds using surface plasmon resonance (SPR) and isothermal titration calorimetry (ITC). ITC measures enthalpy directly, and performing SPR analyses at different temperatures can also be used to dissect enthalpic and entropic terms. The two methods generally concurred, though the numbers did jump around a bit, and in a few cases SPR predicted negative (ie, unfavorable) entropy where ITC suggested positive (favorable) entropy for the same compound.

Both SPR and ITC indicated that the increase in potency for compound 3 over compound 1 is driven by enthalpy, not entropy. This is somewhat unexpected, as the contacts made by compound 3 are largely hydrophobic, and the simplistic view is that such contacts are usually entropy-dominated. (The added hydroxyl in compound 3 doesn’t appear to be doing anything useful, and in fact removing it increases potency roughly three-fold). The researchers suggest that, for poorly solvated hidden pockets such as this, enthalpy may dominate. Perhaps also the protein rearrangement necessary to open the pocket is entropically costly.

There is much more data in the paper than can be summarized here, and the notion that ligands that induce conformational changes in proteins could be enthalpic rather than entropic binders is an intriguing hypothesis. However, as a vigorous debate last year demonstrates, it is still unclear whether knowing the answer – as scientifically interesting as it may be – will have practical implications for drug discovery.

Wedding announcement: Daiichi Sankyo and Plexxikon

2011-03-01T18:03:00.001-08:00

Practical Fragments has highlighted several mergers and acquisitions of fragment-based companies over the years, but yesterday’s announcement that Daiichi Sankyo plans to acquire Plexxikon for $805 million in up-front cash plus an additional $130 million in near-term milestones is definitely the largest. You may recall that PLX-4032, Plexxikon’s B-Raf kinase inhibitor, is currently in Phase 3 trials and a favorite to be the first fragment-based drug approved.

According to FierceBiotech, Plexxikon has raised a total of $67 million in venture funding, so a number of investors are likely popping Champagne. This is a nice validation of the value of fragment-based drug discovery, so let’s all raise a glass!

Not all aromatics stink the same

2011-02-27T16:33:00.000-08:00

A couple years ago we highlighted research suggesting that the more aromatic rings in a molecule, the less “developable” it is likely to be. In the February issue of Drug Discovery Today, the same researchers have now published an update in which they dig into the data in more depth and find that not all aromatic rings are created equal.

As before, the researchers turned to the GlaxoSmithKline internal database of tens of thousands of compounds to correlate chemical features with a variety of measured properties that have an impact on drug development, including solubility, logD, human serum albumin binding, inhibition of several cytochrome P450 isozymes, and hERG inhibition. What they found is summarized in the figure:

In short, while an increase in the number of all-carbon aromatic rings (carboaromatics) had a serious negative effect on nearly all parameters, an increase in the number of heteroaromatic rings was much less problematic. All-carbon aliphatic rings were relatively benign (albeit also relatively rare), while heteroaliphatic rings actually improved most of the properties with the exception of hERG inhibition (and this was only a problem with charged molecules).

One point that was unaddressed in the previous paper was whether an increasing number of aromatic rings is problematic in and of itself, or if this is merely a proxy for larger molecules. In this paper, the authors probed this question directly by examining the properties of molecules with similar molecular weights and lipophilicities but different numbers of aromatic rings. Significantly, the deleterious effects of aromatics appear relatively independent of both size and lipophilicity.

The authors also analyzed ring counts in 1200 oral drugs and found that, while the number of carboaromatic and aliphatic rings has remained relatively constant over time, the number of heteroaromatic rings has roughly doubled from the 1960s to today.

These results provide more support for making sure that fragment libraries contain a good assortment of aliphatics - particularly heteroaliphatics. Aromatics are still very useful of course: as the researchers note, there are thousands of commercially available aromatics, many robust chemistries exist for modifying them, and aromatics provide rigid scaffolds. Thus, fragment libraries should still include a fair share of these moieties, but it is probably worth cutting the number of carboaromatics in favor of more heteroaromatics.

Updated: Fragment-based events in 2011

2011-02-18T15:07:00.001-08:00

The first few fragment events of 2011 are almost upon us, but so far it's looking like the second half of the year is completely empty. If you know of anything let us know and we'll get the word out.

February 21-22: SMi’s 10th Annual Advances & Progress in Drug Design Conference will be held in London, and has a number of fragment-based talks. There is also a separate half-day post-conference workshop on the topic on February 23.

February 23-25: CHI’s Molecular Medicine Tri-Conference will again be held in my beautiful city of San Francisco, with a program on medicinal chemistry that includes a fragment section. Notes on last year’s meeting can be found here.

March 7-8: Fragments 2011, the Third RSC-BMCS Fragment-based Drug Discovery meeting, will be held in Stevenage, UK. This is a biennial event; the last was in Alderley Park in 2009 (you can read about it here and here).

April 12-13: CHI’s Sixth Annual Fragment-Based Drug Discovery will be held in San Diego. I will be helping teach one of two pre-conference short courses on the topic on April 11. You can read impressions of last year’s meeting here.

June 8-10: CHI's Eleventh Annual Structure-Based Drug Discovery will be held in Cambridge, MA, with a full session on FBDD on June 9.

Finally, if anyone attends one of these and wants to write a summary please let us know and we'll post it.

Looks can be deceiving: Getting misled by crystal structures – part 3

2011-02-16T07:27:00.000-08:00

It’s been a while since we’ve touched on some of the hazards of interpreting crystal structures (see here, here, and here). In a recent issue of J. Comput. Aided Mol. Des., Alpeshkumar Malde and Alan Mark of the University of Queensland, Australia describe some mishaps taken from the literature, and how molecular modeling could have avoided them.

The authors start by noting that although protein structure determination using crystallography has been highly optimized, small molecule ligands are a different matter. Part of the problem is that small molecules may show more disorder than protein side chains, thus making it more challenging to fit the model into the observed electron density. Moreover, the parameters for refining protein structures do not always transfer to small molecules: electrostatic interactions are frequently ignored, as are alternative conformations.

As an example, the authors revisit the structure of noradrenochrome bound to an enzyme that synthesizes adrenaline. A racemic mixture of the ligand was used during crystallization, and when the crystal was solved at modest resolution it was possible to fit the ligand within the electron density in eight different orientations – four for each enantiomer. Despite this ambiguity, only a single structure was deposited in the protein data bank (pdb). Malde and Mark ran molecular dynamics (MD) simulations and free energy calculations and found that this structure is likely incorrect: it is higher energy than other structures and binds in a different orientation than the natural ligand, whose structure had previously been solved. In fact, the conformation suggested by MD is the opposite enantiomer from that deposited in the pdb and rotated 180 degrees.

In another example, the authors examine a high-resolution structure of a pyrazole-containing compound bound to the kinase CDK2. Pyrazoles can adopt two different tautomers in which the hydrogen is on either of two adjacent nitrogens, and in this particular case the original paper suggested that both tautomers were present in equal amounts, and both were deposited in the pdb. However, computations suggested that one tautomer is 7 kJ/mol higher energy than the other, and Malde and Mark suggest that in fact probably just a single tautomer is present in the structure.

Finally, the authors describe cases where a primary amide or primary sulfonamide group is in the wrong orientation. In most cases it is difficult to distinguish between a nitrogen and oxygen atom on the basis of electron density alone, and given that there are about 1000 ligands containing a -CONH2 group and about 200 containing a -SO2NH2 there are probably many mistakes.

The authors acknowledge that the examples they present are relatively simple, and one could argue that some of them would have been caught if they were critical structures in a lead optimization program. Nonetheless, the fact that they weren’t suggests that one must always be on guard, particularly in virtual screening where dozens or hundreds of structures are used in an automated fashion to develop or validate docking algorithms. Malde and Mark also note that, in the case of fragment screening with very small low-affinity ligands, one needs be especially cautious.

There is something extremely attractive about a crystal structure: it looks so real that it is easy to lose sight of the fact that it is just a model. Checking one’s assumptions with a bit of computation can prevent costly mistakes.

Paying the fee for ligand efficiency

2011-02-11T07:53:00.002-08:00

Practical Fragments has highlighted a couple cases in which larger molecules have been deconstructed into fragments and then analyzed for binding (see for example here and here). In the most recent issue of J. Med. Chem., Peter Brandt, Matthis Geitmann, and U. Helena Danielson of Beactica have applied this strategy to inhibitors of HIV reverse transcriptase (HIV-1 RT). They also delve into the theory and energetics.

The researchers dissect three non-nucleoside reverse transcriptase inhibitors (NNRTIs) into a total of 21 commercially available “fragments”. Each of these was then tested for binding using SPR (see also this paper for a detailed account of how they perform these screens, and this one for discovery of new fragments against this target). If the binding energies of the fragments were evenly distributed across the entire parent NNTRIs, most of the fragments would be predicted to be sub-millimolar. In fact, most of them were much worse: only 9 showed any evidence at for binding, and only 3 were fragment-sized (the other six had molecular weights above 300 Da).

This sort of result – that fragments of larger molecules bind less effectively than predicted – has now been seen several times, and the researchers asked why. One issue is that when a molecule binds to a protein it loses translational and rotational entropy, and this imposes an energetic cost. This “fee” is, unfortunately, hard to estimate, and complicated by the fact that there may be further energetic costs if the protein itself is flexible (as in the case of HIV-1 RT). The authors provide a nice review of the literature, where values range from 2.5 to a whopping 16 kcal/mol (see here for more discussion on this). When they (admittedly arbitrarily) subtracted 7.0 kcal/mol, the agreement between expected and observed binding of their fragments improved.

However, as the researchers acknowledge, this model still assumes that the binding energy is equally distributed over the entire parent molecule – in other words, it ignores the existence of hot spots. The fact that hot spots exist probably accounts for the decrease in maximum observed ligand efficiency with an increase in the number of heavy atoms:

Once [the hot spot] is occupied, larger molecules need also to interact with other parts of the ligand binding pocket. Hence, a decrease in ligand efficiency will be observed for larger molecules.

True, and to complicate things even more, different proteins will have hot spots of different sizes and “temperature” – or perhaps none at all. This variation calls into question the utility of using notions such as fit quality or %LE, which attempt to normalize ligand efficiency for the size of the ligand. The problem is that different proteins are likely to have different maximal affinity ligands; kinases tend to have high-affinity binding sites where high ligand efficiency can be achieved, while for protein-protein interactions the ligand binding site is likely to be larger and the ligand efficiencies lower. Thus, one-size fits all metrics could prove too stringent – or not stringent enough.

Fragments in Nature

2011-02-04T07:30:00.001-08:00

The most recent issue of Nature has a brief but trenchant summary of fragment-based screening (FBS) by Abbott’s Phil Hajduk, of SAR by NMR fame. This is the first half of a drug discovery forum comparing FBS with diversity-oriented synthesis, or DOS, covered by Warren Galloway and David Spring of the University of Cambridge.

Hajduk summarizes the advantages of FBS:

Fragment libraries are more diverse, synthetic resources are used more efficiently and the leads identified from FBS are more likely to yield drug candidates that have optimal physico-chemical properties.

He also points out that fragment-based approaches have led to a number of drugs in the clinic.

In the spirit of “vigorous debate,” Hajduk also takes aim at DOS. In comparison with fragment-based approaches, which start with small libraries of small fragments, DOS generally makes use of larger libraries of structurally diverse molecules which are usually drug-sized and are often inspired by natural products. However, Hajduk alleges that:

Most compounds in DOS libraries would be excluded from many corporate screening collections because of their poor physico-chemical properties.

I don’t know about “most”, but I will say that many DOS compounds look suspiciously like PAINS. Still, DOS does have at least one strength: FBS is generally limited to well-characterized systems with purified proteins, whereas DOS libraries can be used in complex phenotypic assays where the target may not be known. Whether these will ultimately yield new drugs remains to be seen.

What do you think?

18 PI3K fragments

2011-01-24T06:28:00.000-08:00

As we’ve noted before, kinases are a fertile field for fragment finding, but most of the targets have been protein kinases. Lipid kinases such as the phosphatidylinostide 3-kinases (PI3Ks), which mediate signal transduction by transferring a phosphate group to lipids, are also popular targets for a variety of diseases, but less has been disclosed about their suitability for fragment-based lead discovery. A paper in a recent issue of Bioorg. Med. Chem. Lett. remedies that.

Fabrizio Giordanetto and colleagues at AstraZeneca started with a homology model of p110beta (no crystal structure of this enzyme has been reported). They then used commercial software to dock 183,330 fragments selected from their corporate collection. All fragments that made at least two hydrogen bonds with the protein were organized into clusters of similar molecules and representatives of each cluster were visually inspected. This led to the selection of 210 fragments to be screened against the protein, of which 18 showed measurable activity. Structures of these fragments are provided in the paper; they range from kinase workhorses such as compound 1 to known PI3K motifs such as compound 10 to more unusual molecules such as compound 18. These hits were also tested on other members of the PI3K family, and while most showed activity across the board, others (such as compound 18) showed some selectivity.

There are some interesting structures in here; if I were starting a PI3K program I would definitely take a close look at them. Although the researchers have likely developed some of these into attractive leads, one of the virtues of fragments is that they are often so protean that different teams can start with the same fragment and end up in very different places.

Fragment linking in crystallo

2011-01-18T06:57:00.000-08:00

Of the many ways to link fragments, one of the most intriguing is when the protein itself catalyzes or templates the assembly of two fragments (see for example here and here). The latest example of such target-directed fragment linking was published in last month’s issue of J. Appl. Cryst.

The researchers, led by Isao Tanaka at Hokkaido University, were interested in ligating fragments together in protein crystals. They first took crystals of the model protein trypsin and soaked these with an “anchor molecule,” in this case one of two benzamidine-containing aldehydes (benzamidines are classic trypsin binders). The crystals were then transferred to a second solution containing a “tuning molecule,” each of which contained either an aminooxy or hydrazine moiety that could react covalently with the aldehyde of the anchor molecule. Finally, the crystals were analyzed by X-ray and structures of any bound ligands solved.

A total of 33 different tuning molecules were examined, and two of these produced clear electron density in the active site showing that ligation with the anchor molecule had occurred (for example ALD2 and OXA9). Three others produced structures that suggested some disorder in the binding mode of the tuning molecule, and a fourth showed an assembled product that extended from the active site to a second trypsin molecule in the crystal lattice.

A study similar to this was published a number of years ago, but in that case it was not clear whether the ligation occurred in the crystal or in solution. In the present case, soaking pre-assembled molecules into the crystals produced inferior electron density to the two-step process. More excitingly, time-resolved experiments actually showed structural snapshots of the complex forming, both in the active site (which occurred in under a minute) as well as at the dimer interface (which took over an hour).

Unfortunately, the assembled products are not notably better binders than the initial fragment. The authors attribute this to the fact that their library of tuning molecules was very small. However, it is also possible that the approach selects not for the best binders but for those that can best form complexes within a fairly rigid crystal lattice. As we’ve seen before, protein crystals are far from physiological. It will be interesting to see whether in-crystal chemical ligation can generate superior binders.

Ligand efficiency in action

2011-01-12T07:03:00.000-08:00

At an introductory talk I was giving recently on FBLD, someone asked how useful ligand efficiency (LE) really is. A paper published online in J. Med. Chem. by Daisuke Tanaka and colleagues at Dainippon Sumitomo Pharma illustrates how the metric can guide medicinal chemistry to superior molecules.

The enzyme soluble epoxide hydrolase (sEH) is a potential anti-inflammatory target. Inhibitors have been reported, but these tend to be quite lipophilic, so the researchers sought to find smaller, less hydrophobic inhibitors that bound with high-affinity to the target. A virtual screen against multiple ligand-bound crystal structures led to the selection of 735 diverse compounds which were tested in a biochemical assay, resulting in 68 compounds with IC50 values better than 1 micromolar. Most of these were relatively hydrophobic amides or ureas.

After removing known chemotypes and obviously unattractive molecules, the researchers were left with 42 compounds. They decided to eliminate compounds with MW > 380 or logP > 3.5, leaving 17 compounds; as might be expected, these smaller molecules turned out to be the most ligand-efficient of the bunch. Despite being one of the weakest hits identified, fragment-like compound 1 was the most ligand efficient and was chosen for lead optimization. A crystal structure of this compound bound to sHE guided parallel synthesis of 155 analogs, all with low molecular weights. Many of these compounds were very potent, and compound 11 not only showed a nice improvement in affinity but also demonstrated good ADME properties.

The authors conducted a retrospective analysis using some of the other ligand-efficiency-like indices such as %LE and fit-quality, which allow looser standards for affinity as molecule size increases. Interestingly, compound 1 was not an obvious starting point using these metrics. It is impossible to say what would have happened had these measures been prioritized over ligand efficiency, but the success of the simpler LE suggests that taking size into account would not have been useful, and could even have been misleading.

This paper is not a traditional fragment paper in which a low affinity lead is optimized; the initial hit was already quite potent. Rather, as the authors note, this is a nice example of “fragment-inspired medicinal chemistry, in which the essence and advantages of FBDD are faithfully respected.” It also provides another example of how focusing on ligand efficiency, rather than just potency, can lead to attractive chemotypes.

Flattening fragments

2010-12-30T07:23:00.000-08:00

If you want to visualize and manipulate crystallographic data there are plenty of options, such as PyMOL and OpenAstexViewer. However, powerful molecular graphics programs such as these have a learning curve associated with them, and sometimes it’s nice to get a simple two-dimensional image. In the December issue of ACS Medicinal Chemistry Letters, Katrin Stierand and Matthias Rarey describe software they’ve developed to do this.

PoseView, which can be used online free of charge, automatically generates a two-dimensional view of a protein-ligand complex and labels five different types of interactions: hydrogen bonds, metal interactions, pi-cation interactions, pi-pi stacking, and undirected hydrophobic contacts.

The researchers tested their software by using it to draw nearly every protein-ligand interaction in the Protein Data Bank (PDB) in which the ligand has 5 to 80 atoms, excluding crystallization buffer components and things like heme or iron-sulfur clusters. For the remaining 200,000+ complexes, PoseView successfully generated plots for 85% of them; interestingly, most of the failures resulted because there were no apparent interactions between the protein and “ligand.” Of the successes, 80% produced high-quality figures in which there were no overlapping features – not bad considering the challenge of reducing a three-dimensional model to a two-dimensional image.

The paper includes some interesting data about protein-ligand complexes in general. For example, over 90% of complexes in the PDB have less than 11 directed interactions (ie, interactions other than hydrophobic contacts), with the largest number having only a single directed interaction. It would be interesting to see how these statistics apply to fragment-sized ligands.

PoseView is incredibly easy to use: just enter a pdb code or upload a structure, and the program spits out an image. I tried it on the very first fragment I discovered, and the result looks quite attractive:

Of course, there is always room for improvement: for example, it would be nice if you could change fonts or colors (the output is a pdf). Still, this is a useful addition to the toolbox of modeling programs.

And with this post, Practical Fragments says goodbye to 2010 and wishes everyone a happy holiday season. We look forward to more exciting developments in 2011 – and if we miss any, please send them our way!

SAR by Crystallography – minus the “A”

2010-12-22T07:14:00.000-08:00

Practical Fragments has highlighted at least a couple papers (here and here) where fragments were identified by crystallography but where functional activity was not reported. Indeed, most experienced fragment hunters will be able to point to cases where they observed well-defined electron density but were unable to measure inhibition. Although this is often a source of frustration, researchers from Johnson and Johnson decided to avoid measuring activity altogether until after a couple cycles of crystallography-guided library design, as they describe in a paper published this month in J. Med. Chem.

The researchers were interested in the protein ketohexokinase, an ATP-dependent enzyme that is a potential target for metabolic diseases. They assembled a primary fragment screening library of 900 compounds with the following characteristics:

• 6-15 non-hydrogen atoms
• < 3 hydrogen bond acceptors
• < 3 hydrogen bond donors
• < 2 rings
• No unspecified chiral centers
• No unpleasant functionalities (peroxides, acyl halides, etc.)
• Prioritization given to molecules found in known pharmaceutical compounds (similar to the Fragments of Life)

This is a fairly standard set of criteria for assembling a fragment library. The researchers broke with convention by pooling fragments into groups of 5, with the members of a given fragment pool as structurally similar as possible. Normally when researchers pool libraries for crystallography-based fragment screening the idea is that each member of a given pool will be structurally unique to facilitate identification. In this case, though, the researchers were interested in observing general features of how fragments bind to the target protein.

Crystals of hexokinase were soaked with the pools, and 60 of these pools yielded electron density in the active site – a very high hit rate of 30%. A number of generalizations could be made about what molecular features were preferred in different parts of the binding site, and this information was used to build a secondary library of about 350 compounds based on 6 scaffolds; the idea was to merge or grow fragments found in the primary screen. These compounds were similarly pooled and screened crystallographically but not functionally, yielding hits from 4 of the scaffolds. The structures of these hits were then used to generate a third library of several hundred compounds around at least 4 separate scaffolds. These compounds were then tested individually to see if they could inhibit ketohexokinase, and were also characterized crystallographically. Gratifyingly, a number of these were active at submicromolar potency, including compound 6.

In addition to showing decent potency against ketohexokinase, compound 6 exhibited respectable drug-like properties as well, including lack of activity against the CYP450 enzymes, high oral bioavailability, and good selectivity against receptors, ion channels, and protein kinases, though other ribokinases were not tested.

This is an interesting and potentially useful approach, but it would be fun to see how it compares with a more “traditional” strategy, where individual fragments are advanced. It should be relatively straightforward to assay fragments from the first and second library for affinity; was fragment 3 (precursor to compound 6) one of the most potent or ligand efficient? Or was the information from fragments with no detectable activity instrumental in delivering the best compounds?

Fragment-based job listings

2010-12-17T09:24:00.000-08:00

The fragment-based community is very diverse, with practitioners coming from biochemistry, biophysics, chemistry, computational chemistry, and many other disciplines. Communicating job openings to such a fragmented community can be difficult, but we think Practical Fragments can provide a common place for employers who want to build up fragment expertise of any flavor. If you have an opening you are trying to fill, please add it as a comment to this post. These comments will then be listed in the “Job Openings” link under the “Links of Utility” heading on the right side of the page, so they will always be easy to find.

(Note: this is for positions in fragment-based drug discovery only. There is also a LinkedIn group that lists jobs with a broader but overlapping focus.)

Hsp90 and fragment linking

2010-12-10T07:24:00.000-08:00

There has been no shortage of fragment-based approaches directed toward the anti-cancer target Hsp90, most of which have relied on growing fragments (see here for some impressive recent examples). Researchers from Abbott published a report providing a couple examples of linking fragments against this target a few years back, but in those cases the ligand efficiencies of the linked molecules were dramatically lower than those of the initial fragments. In a recent paper in ChemMedChem, researchers from Evotec describe an example that maintains the ligand efficiency.

The research group had previously conducted a fragment screen against Hsp90, resulting in a number of hits. In the new paper, fragment hits 1 and 2 (see figure) were both found to have fairly low affinities, but were characterized crystallographically. Interestingly, fragment 2 could adopt at least two very different conformations, depending on whether it was co-crystallized in the presence of fragment 1. In the ternary structure, the two fragments come within about 3 Å of each other, and molecular modeling suggested that four atoms should be able to link them.

Gratifyingly, when such a compound was made and tested, it inhibited the enzyme several hundred-fold more tightly than either of the initial fragments. The crystal structure revealed that the compound binds similarly to the ternary structure of Hsp90 and fragments 1 and 2.

The authors note that “the binding free energy of the linked fragment 3c was found to be exactly the sum of those of the original two fragments.” Of course, this is still a long way from an ideal linking situation: as noted earlier this year a good linker should lead to super-additivity (an improvement of ligand efficiency), not just additivity (maintenance of ligand efficiency). Nonetheless, this example is still better than many attempts at linking, which often are less than additive.

Fragment-based conferences in 2011

2010-12-02T07:31:00.001-08:00

As 2010 winds to a close, it’s time to start planning for 2011. As in previous years, fragment events seem to cluster in the first half of the year, so start planning now!

February 21-22: SMi’s 10th Annual Advances & Progress in Drug Design Conference will be held in London, and has a number of fragment-based talks. There is also a separate half-day post-conference workshop on the topic on February 23.

February 23-25: CHI’s Molecular Medicine Tri-Conference will again be held in my beautiful city of San Francisco, with a program on medicinal chemistry that includes a fragment section. Notes on this past year’s meeting can be found here.

March 7-8: Fragments 2011, the Third RSC-BMCS Fragment-based Drug Discovery meeting, will be held in Stevenage, UK. This is a biennial event; the last was in Alderley Park in 2009 (you can read about it here and here). Registration is now open, as is a call for posters through January 31.

April 12-13: Cambridge Healthtech Institute’s Sixth Annual Fragment-Based Drug Discovery will be held in San Diego, with at least one pre-conference short course on the topic on April 11. You can read impressions of this past year’s meeting here.

Know of anything else? Organizing a fragment event? Let us know and we’ll get the word out.

More techniques: NovAliX and Graffinity combine MS and SPR

2010-11-29T07:00:00.000-08:00

We’ve written previously about Graffinity, which uses surface plasmon resonance (SPR) to find fragments, and NovAliX, which initially focused on mass spectrometry. The two companies have been collaborating since last year, and this has apparently been a fruitful partnership: this month NovAlix acquired a majority ownership stake in Graffinity (click here for press release). Earlier this year NovAlix also purchased an NMR-focused company, and they have already added crystallography expertise. Finding fragments effectively requires using a range of orthogonal technologies, and this latest move gives NovAlix a full suite of biophysical techniques.

Fragments vs PDK1

2010-11-12T07:22:00.000-08:00

Kinases have been a particularly productive target class for fragment-based drug discovery (and drug discovery in general), with nearly half of reported FBDD-derived clinical candidates targeting kinases. The latest dispatch from this field can be found in the November issue of ACS Medicinal Chemistry Letters.

In this paper, Jeffrey Axten and colleagues at GlaxoSmithKline describe their use of fragment screening to identify inhibitors of PDK1, a popular anti-cancer target. They started by assembling a library of fragments biased towards the purine-binding site of kinases, and tested 1065 of these in a biochemical screen at 400 micromolar concentration. Of these, 193 inhibited activity at least 60% and were further characterized; 89 had IC50 values better than 400 micromolar. A set of 36 of these, chosen on the basis of ligand efficiency and chemical tractability, were chosen for follow-up.

Saturation transfer difference (STD) NMR was used to confirm which fragments bound to PDK, which cut the number of hits in half. X-ray crystallography experiments were started before NMR and performed on 7 fragments; only the fragments that were confirmed by NMR gave interpretable data. One of these was the aminoindazole compound 8 (see figure).

A substructure search was conducted to find more elaborated molecules within the corporate screening collection, leading to compound 19, which has sub-micromolar potency. This compound also showed some signs of selectivity for PDK1 over other kinases. Although the paper stops here, Jeffrey Axten gave a nice presentation at FBLD 2010 in which he discussed subsequent medicinal chemistry that ultimately led to novel, high picomolar inhibitors of PDK1.

There are at least two lessons from this story. First, the significant attrition from the biochemical screen again emphasizes the need for orthogonal methods of fragment validation. Second, even though the fragment identified has been around the block with respect to kinases (as of last year, the aminoindazole substructure had appeared in over 70 kinase patents), skillful medicinal chemistry can still get you to novel compounds.

Pin1 revisited

2010-11-07T17:57:00.002-08:00

Earlier this year we highlighted a paper from Vernalis that described the use of NMR methods to discover inhibitors of the anti-cancer target Pin 1. In a recent issue of Bioorg. Med. Chem. Lett. the same team now reports a second series of compounds that inhibit this protein, also discovered and advanced through FBLD. The two papers together provide some interesting lessons.

Rather than using NMR, the researchers identified the second series of compounds with an inhibition assay. After screening 900 fragments at 2 mM, they obtained 40 hits, including 3 compounds previously discovered by NMR. Disturbingly though, follow-up NMR experiments confirmed binding for only 2 of the 37 new hits, suggesting that the remaining compounds may act through pathological mechanisms (see also here). Still, two hits are better than none, and the binding mode of one of the fragments (compound 3 in figure) was determined by X-ray crystallography. Several analogs of this were purchased and tested, and compound 5 was found to have an improved potency and ligand efficiency.

At this point chemistry entered the picture. The researchers synthesized several analogs of compound 5, guided by crystallography and modeling. This led to compound 10e and eventually to compound 20, with sub-micromolar biochemical activity and measurable cell activity.

Ultimately though, as in the previous Pin1 series, even this modest cellular potency was gained at the cost of unacceptable increases in size and hydrophobicity. This brings up an interesting question: at what point do you declare a target undruggable? The authors note that “the nature of the Pin1 active site makes it difficult to optimise hits into drug-like molecules.”

Fragment-based approaches can sometimes deliver inhibitors to challenging targets where HTS has failed. However, if the inhibitors can’t be transformed into drugs, is finding them actually a good thing? Researchers are getting better at improving potency at the same time as ligand efficiency for some targets, but ultimately getting to clinical candidates for harder targets may come down to how many resources you are willing to throw at a project: molecules such as ABT-263, though far from rule-of-5 compliant, are doing well in the clinic, but only after the investment of dozens if not hundreds of people-years.

Ligand efficiency hot spots

2010-11-03T20:31:00.000-07:00

Hot spots are regions of a protein with a particular predilection for binding to small molecules – thermodynamic sinkholes, so to speak. Discovering one of these can get you to potent molecules very quickly. In an effort to better understand hot spots, Iwan de Esch and colleagues at VU University in Amsterdam and collaborators at Beactica have deconstructed a potent ligand for nicotinic acetylcholine binding protein (AChBP), a model protein for ligand-gated ion channels, which are implicated in a variety of neurological diseases. They report their results in a recent issue of J. Med. Chem.

The researchers started with the previously reported quinuclidine compound 6 (see figure) and fragmented this into 20 analogs. They tested these in a surface plasmon resonance (SPR) assay as well as in a more conventional radioligand binding assay; the agreement between these very different assay formats was excellent, further validating the utility of SPR as a useful tool for discovering fragments.

Not surprisingly, some of the fragments have higher ligand efficiencies than the larger, more potent molecule, suggesting that there is a hot-spot that recognizes the core fragment 25 (which is structurally related to nicotine). This concept of “group efficiency” has been described previously, and can be useful for optimizing fragments. For example, compound 22, without a basic nitrogen atom, has the lowest ligand efficiency in the bunch; presumably, simply adding the nitrogen would give a sizable boost in potency.

However, one needs to be cautious. The researchers use computer docking to develop models of how each of these fragments bind, but as we have seen before, isolated fragments do not always recapitulate the binding modes of fully elaborated molecules. Still, particularly in the absence of structure (as is the case with many ion channels), exercises such as this could provide useful ideas for what to do with fragment hits.