16 April 2014

What we do in life, echoes in eternity (or the life of the patent)

Next week is the Drug Discovery Chemistry conference where Dan and I will be co-teaching our award-winning FBDD short course (or at least our mom's think it is great). We look forward to seeing any/all of you next week.  Blogging may be light next week, but we promise to give an update of the going-ons at the conference soon after.  

Kinases are fun, and those of us who have worked in them have probably all worked on the same ones.  I always loved the MAP family.  Why would I have a favorite kinase family?  Because of the cascading MAP kinases, like the one in this paper, Mitogen-activated protein kinase kinase kinase kinase 4 (that's a lot of kinase!).  But, unlike a lot of other kinases, there is no good tool compound.  So, using SPR, they decided to generate one. This paper is not particular interesting in terms of what they did, but rather it raises interesting questions. While the approach they describe is not novel, it is nice to see the data supporting them. 

They screened their 2500 fragment library against immobilized protein at 100 uM (single point).  225 hits were found with Kd ranging from 10 to 2000 uM (LE =0.24 to 0.59) for a 9% hit rate.This paper is about progressing this oxazole fragment 1

Based upon its structure and the wealth of kinase structure knowledge extant, they surmised it would be ATP-competitive and a hinge binder.  Based upon a binding model, the attempted to prosecute this fragment by "close-in" analogs and looking for groups that would extend farther into the hydrophobic pocket, but with MW less than 350 Da and clogP less than 3.5.  Exploring bi-aryl space resulted in 8:  
This compound had an activity of 143 nM and it was at this point that they decided to switch to the biochemical assay as their primary assay.  In the end, using X-ray focusing on LLE, they ended up deliveringa low molecular weight compound with favorable in vivo PK.  It also demonstrated a pathway functional response. 

This raises an excellent point, something I get asked frequently.  When do you switch from a biophysical assay to a biochemical one?  This maybe arguing semantics, but I think as more and more companies enter this arena these are exactly the things we need to discuss.  I think the switch happens when you feel comfortable, there is no hard and fast rule.  There is a difference in the SPR Kd and biochemical IC50 by more than 10x.  It is very important to note that they relied heavily on LE (-RTlnKd/HA) and LLE (pKd-cLogP), or pIC50 for biochemical assays.  But, it also raises the issue of correlation between SPR Kd and IC50.  I raise these socratically, and as maybe as a topics for discussion next week (or in July and September).   

14 April 2014

Can selectivity of fragments be maintained?

In 2011 we highlighted an analysis of kinase inhibitors that demonstrated that non-selective fragments could produce selective leads, and vice versa. However, that study was based on hundreds of compounds not necessarily chosen from the same projects. Are the results the same within individual fragment-to-lead programs? This is the question that Ian Collins and colleagues at the Institute of Cancer Research address in a recent paper in MedChemComm.

The researchers examined three fragment-to-lead efforts: two targeted the kinase PKB and the other targeted the kinase CHK1. In all three cases they started with fragments and used structure-based design and fragment growing to obtain low nanomolar inhibitors. Importantly, they also obtained crystal structures of key compounds along the way, demonstrating that the initial fragment – a hinge-binding element – maintained its position and orientation throughout the process.

Each fragment, lead compound, and intermediate molecule was tested for selectivity in a panel of 91 kinases using a microfluidic mobility-shift peptide phosphorylation assay. The concentration of ATP in each assay was at the KM,ATP, and each compound was tested at 10-fold above its IC50 for the target kinase (so for example fragment 1 below was screened at 1000 μM, and fragment 5 was screened at 8 µM). For each compound a selectivity score was calculated based on the number of kinases inhibited at a certain threshold. For example, if S(30%) = 1, this would mean that all of the kinases were inhibited by at least 30% at the concentration tested, whereas if S(30%) = 0.03 this would mean that only 3 kinases (3/91= 0.03) were inhibited.

It's worth noting that selectivity is tough to define specifically. Although the selectivity score makes sense intuitively – each compound is tested at a concentration relevant to the intended target – I am concerned that it will make potent compounds appear more selective than they really are. Indeed, a plot of S(30%) versus -log[concentration tested] is fairly linear. (Compounds discussed below are labeled by number on the plot.)
Accepting this definition of selectivity, though, it appears that nonselective fragments, such as 7-azaindole (fragment 1) could be progressed to nonselective leads such as compound 4, which was an early milepost en route to AZD5363, currently in Phase 2 clinical trials.

Fragment 1 was also modified to slightly less promiscuous fragment 5. A slight tweak to this molecule produced selective fragment 6, which was then optimized to the selective compound 8 (closer to AZD5363). In the case of fragment 6, even though the structural change was minor (removal of a single methylene) this was enough to make a specific interaction with a residue in PKB not found in other kinases. The CHK1 story is similar in taking a nonselective fragment to a selective lead.

So what’s the conclusion? The authors suggest that:
Broad kinase selectivity screens of fragments could be predictive of the lead, provided strategies to conserve the profile are followed in the elaboration, avoiding introducing new interactions with target-specific residues. Conversely, the initial fragment selectivity patterns are unlikely to reflect those of developed leads if the fragment does not already encode the anticipated target-specific interactions.
In other words, it depends. This is not meant as a criticism: I think this conclusion is about as decisive as possible when generalizing about fragment-to-lead strategies. At the very least, the work suggests that effort spent optimizing a fragment before growing or linking could be worthwhile. And even a promiscuous fragment may be only one atom away from something quite specific.

09 April 2014

Covalent, destabilizing fragments against TB target BioA

Differential scanning fluorimetry (DSF) is a hit-finding technique in which a protein is incubated with a small molecule and heated until the protein reaches its “melting temperature” and unfolds. If a small molecule binds, in theory it should stabilize the protein towards thermal denaturation and thus raise the melting temperature, giving a positive thermal shift. However, most folks who have performed these types of experiments have also found (and usually ignored) molecules that lower the melting temperature of the protein. In a new paper in ChemBioChem, Barry Finzel and coworkers at the University of Minnesota follow up on one of these with very interesting results.

The researchers were interested in the enzyme 7,8-diaminopelargonic acid synthase (BioA) from Mycobacterium tuberculosis, the organism that causes its eponymous disease. This enzyme – which is not found in mammals – is involved in the synthesis of the essential cofactor biotin. DSF was used to screen 1000 compounds from the Maybridge Ro3 Diversity Fragment Library at 5 mM concentration, resulting in 21 hits which changed the denaturation temperature (Tm) by more than 2 °C. A dozen of these decreased the Tm, but although all of these were taken into crystallography trials, only compound 1 yielded a structure. STD NMR was also used to confirm that the compound binds to BioA in solution.

Next, the researchers used the classic “SAR-by-catalog” approach and purchased analogs of compound 1. Compound 2 turned out to be particularly interesting: it decreased the Tm by a whopping 18 °C! Weirder still, when soaked into crystals of BioA, they turned from yellow to red.

BioA is a transaminase: it takes a nitrogen from one molecule (called SAM) and transfers it to another molecule (called KAPA). En route to its final destination, the nitrogen is transferred to a co-factor, pyridoxal phosphate (PLP), which contains an aldehyde. Compound 2 contains a hydrazine, which is known to react with aldehydes, and in fact a co-crystal structure of compound 2 bound to BioA shows that this is exactly what happens. Interestingly, compound 2 binds in a somewhat different manner than compound 1 despite their similar chemical structures.


Compound 2 turns out to be a reversible inhibitor of BioA, and the researchers were able to demonstrate that it is a moderately potent and competitive inhibitor with respect to SAM and a less potent uncompetitive inhibitor with respect to KAPA. This is exactly what you would expect, since it competes with SAM for binding to PLP but does not compete with KAPA.

Now you may think that hydrazines aren’t exactly drug-like, but it turns out that a commonly used drug against tuberculosis is isoniazid, which contains an analogous acyl hydrazide. The researchers found that isoniazid also decreases the Tm of BioA, though less dramatically than compound 2. Though isoniazid works through an entirely different mechanism, the researchers were able to obtain a co-crystal structure of this binding to PLP in BioA (magenta; PLP is on the left, and protein is not shown), showing that it binds differently than either compound 1 (green) or 2 (cyan). Nonetheless, it did not show any inhibition of the enzyme, demonstrating that covalent binding alone is not sufficient for disrupting enzymatic activity.
This is a very nice paper, and it will be fascinating to try to understand how the fragments so effectively destabilize the protein despite binding tightly, and how this translates into inhibition. The researchers suggest that finding ligands that destabilize proteins could be generally useful for turning off proteins. Are there other well-characterized examples out there?

07 April 2014

It's A Start

As the readers of this blog know, I tend to be harsh on academic "Drug discovery" papers.  Sometimes, there is a really worthwhile academic paper, but by and large I find that they tend to publish things that are barely "drug discovery" and more the For Dummies...of what they think drug discovery is.  Which way will I swing on this paper from researchers Down Under?  

The bacterial Sliding Clamp, aka polymerase 3beta, is a key player in bacterial replication and is an "emerging" target. It interacts with other proteins via LM (Linear Motifs): 4-10 amino acid disordered regions.  This is typically a weak interaction (1-100 uM). These LM exist at termini, but sometimes in loops.  A consensus sequence for the LM that interacts with the Sliding Clamp has been identified: QLx1Lx2F/L (S/D preferred at x1; x2 may be absent).  Two classes of compounds have been identified previously but with >10 uM affinity and no -cidal activity. 

So, these authors went after this target using X-ray as the primary screen.  The Zenobia Fragment Library was used (352 molecules) to soak into crystal in pools of 4 fragments.  Four fragments (below) were found to bind to Subsite I on Chain A.  However, no changes in the main chain density were observed.

They also found several other fragments with weak density, and several that were deemed crystallographic artifacts.  None of these compounds showed significant activity below 1 mM in their competition assay.  So, the story then continues that they "sought to improve binding affinity by identifying fragments that could more completely occupy" the binding site.  

[An aside:  To me, this brings up an important point about the choice of fragment collection.  Fragments that are designed for X-ray soaking tend to be small (10-12 HAC).  Just from a theoretical standpoint, those fragment would have to have an affinity in the 250 uM range (LEAN 0.3).   This was covered in a poll and most most people are happy going < 10 HAC.  My question is how often is a very small fragment found as an active?]

To do this, they noted that the fluoro-phenyl group in 1 was previously reported, leading to investigations with compound 5. It was found to fully occupy the binding site.

They searched ZINC for compounds similar to 1-5.  Their initial purchases failed to find any compounds with activity < 1mM.  Eventually, they landed on the hypothesis that chlorocarbazoles were "promising", leading to compound 6.  At this point, I think Dan's head exploded, Scanners-style.  Yes, that is an epoxide.  The co-crystal structure showed that it was binding in the active, albeit with weak electron density.  Their SAR, wisely, did not include the N-alkyl epoxide. 
Both 7 and 8 show good LE and LLEAT.  Only the R enantiomer of 8 caused movement in the main chain.  It also was the most potent in the replication inhibition assay (64 uM).  It was also the most potent in terms of -cidal activity against both Gram positive and negative microbes. 

So, is this a good or bad paper?  I would say it is a start, but if I had been a reviewer I would have made them change the title "Discovery of Lead Compounds Targeting the Bacterial Sliding Clamp
Using a Fragment-Based Approach" to "Discovery of ACTIVE Compounds Targeting the Bacterial Sliding Clamp Using a Fragment-Based Approach".

01 April 2014

Funky fragments

Natural products have led to many approved drugs, and there is an increasing appreciation that Nature often knows best. Indeed, several published fragment libraries incorporate natural products or natural product-like molecules (see for example here, here, and here). With all this attention, it was inevitable that commercial fragment suppliers would spot this market need.

SerpentesOleum, Inc. has just launched a library they call FUNK: Fragments Uncovered in Natural Kompounds. This set consists of several hundred natural products and derived fragments carefully selected to maximize hit rates. For example:


The company has screened their library against targets such as PTP1B and falcipain-1 and obtained remarkably high hit rates in functional assays. In fact, SerpentesOleum is so confident that they’re offering a money-back guarantee if you don’t obtain at least one active against your target, no matter what it is. Looking at the structures of their compounds, I have no reason to doubt their claim.

26 March 2014

Who's Doing FBLD, 2014 Version

It's been a while since we updated this list.  The first list had 24 companies, the second 44.  From 2011 to now, what's changed?

I have divided the list into (primarily) providers of services and pharmaceutical companies. This does not mean that that providers don't do their own discovery, or work in a mixed-model.  I have annotated those companies which were not previously on the list.  Please note that this does not necessarily mean they were not doing FBDD previously, they just were not listed.If we missed someone, let us know and we will update the post.

Providers:
Ancorex  (New 2014)
Beactica
Biodesy  (New 2014)
Biofocus(Galapagos)  Acquired by Charles River Laboratories
Biosensor Tools
BioSolveIT
Chemical Computing Group   (New 2014)
Crelux
CrystaX Pharmaceuticals  Acquired by Oryzon Genomics
Domainex   (New 2014)
Emerald BioStructures
Exscientia   (New 2014)
Evotec
Graffinity  Acquired by NovAliX 
iNovacia  Acquired by Kancera
Infarmatik
Intellisyn (New 2014)
IOTA Pharmaceuticals
Kinetic Discovery
MEDIT
Molsoft (New 2014)
Nanotemper (New 2014)
NMR Research  (New 2014)
NovAliX
Pharma Diagnostics
Proteros 
Pyxis Discovery  (Are they still an ongoing concern?)
Red Glead  (New 2014)
Saromics (New 2014)
Schrodinger
Selcia
SensiQ  (New 2014)
Structure Based Design
Viva Biotech  (New 2014)
Zenobia Therapeutics
ZoBio

Companies
Abbvie             split from Abbott
Amgen             (New 2014)
Ansaris (previously Locus)
Ariad               (New 2014)
AstraZeneca
Astex              Acquired by Otsuka(2013)
BioLeap
Boehringer Ingelheim
Bristol Myers Squibb
Carmot Therapeutics
Constellation Pharma
Crown Biosciences 
Dart Neuroscience
Eli Lilly
Genentech (Roche)
Genzyme Acquired by Sanofi-Aventis
GlaxoSmithKline
Heptares
Johnson & Johnson 
Merck
Nerviano Medical Sciences
Novartis
Pfizer
Plexxikon    Acquired by Daiichi Sankyo (2011)
Polyphor
Roche
Sprint Bioscience
Takeda California
UCB   (New 2014)
Vernalis
Vertex

**UPDATE** 27Mar2014: added Domainex, UCB
**UPDATE2** 28May2014: added MolSoft, Ancorex

24 March 2014

Fragments vs MCL-1, again and again

Last year we highlighted a paper from Stephen Fesik’s group at Vanderbilt in which he used SAR by NMR and fragment merging to identify nanomolar inhibitors of the protein MCL-1, an anti-cancer target that had previously been thought to be impervious to small molecules. In a recent paper in Bioorg. Med. Chem. Lett., Andrew Petros, Chaohong Sun, and other former colleagues of Fesik at AbbVie describe two additional series of inhibitors.

The researchers started with an NMR screen using MCL-1 in which the methyl groups of isoleucine, leucine, valine, and methionine were 13C-labeled. Screening this against a library of 17,000 fragments in pools of 30(!) gave dozens of hits, some of which inhibited in a biochemical assay (for aficionados, they assessed binding to the BH3 domain of Noxa using fluorescence polarization as a readout).

Fragment 1 turned out to be fairly potent, though it is super-sized and violates the rule of three. The researchers were unable to get co-crystal structures of any of their fragments bound to MCL-1, but they were able to use NOE-based NMR experiments to develop a model of how fragment 1 might bind. This led them to synthesize a number of analogs such as compound 17, for which they were able to obtain a co-crystal structure with the protein, ultimately leading to the mid-nanomolar compound 24.


Fragment 2 was much less potent than the other fragment but had a considerably higher ligand efficiency. In this case simple modeling suggested growing away from the acidic portion of the molecule, leading to compound 36 (which was characterized crystallographically bound to MCL-1) and the more potent compound 44.

Overlaying the co-crystal structures of compounds 17 (blue) and 36 (red) reveals that they both bind in the same region, where Fesik’s compound 53 (green) also binds. All three molecules place a carboxylic acid in a similar position, but the two more potent molecules thrust a hydrophobic moiety deep into a pocket of the protein. It is tempting to speculate that compound 44, the more potent analog of compound 36, may also take advantage of this pocket.

Andrew Petros presented some of this work at FBLD 2012, so it is nice to see it in print. Though reasonably potent, it is worth keeping in mind that the molecules are also quite lipophilic. Perhaps it is significant that, like the Fesik paper, no cell-based data are presented. Collectively, though, these papers establish that MCL-1 is ligandable. Whether it will be druggable remains an important – and as yet unanswered – question.

19 March 2014

PAINS propagation

PAINS, or pan-assay interference compounds, comprise a subject that has cropped up several times here (and here, and here, and here). Although not exclusive to fragments, I wanted to point out a thorough and insightful analysis by Jonathan Baell over at HTSPAINS in which he traces the lineage of a dubious series through paper after paper all the way back to 2001. The assays, models, and mechanistic theories all change, and the molecules keep getting uglier as they devolve from chalcones to bis-benzylidenepiperidones. It’s an entertaining and educational look at sloppy science. He ends with an important point:

People still don’t realize how easy it is to get a biological readout. The more subversive a compound, the more likely this is.

Indeed, even with decent looking molecules it can be difficult to figure out exactly what is going on; with PAINS you may as well start explaining things in terms of phlogiston and humorism.

I can’t help thinking of the late Efraim Racker’s admonishment: “don’t waste clean thinking on dirty enzymes.” Even when they are chemically pure, PAINS molecules are mechanistically dirty. The amount of effort wasted on them boggles the imagination, so keep them out of your libraries!

17 March 2014

This is another way to do it.

The key to doing something right is to following the directions.  How closely you follow the directions, or don't follow, can be the difference between brilliance and just a good performance, e.g. cooking.  Sometimes, directions are meant as guidelines, like the Pirate Code or the Voldemort Rule.  Late last year, and blogged about here, I published a paper in Current Protocols on how to prosecute an STD screen.  A recent paper in PLOSOne, shows how someone else runs their screens, but with details on library construction, solubility testing, and more.  What makes this paper of interest is the level of detail that they provide.

Library Design: They assembled a diverse fragment library with the following rules: 110≤ molecular weight ≤350, clogP≤3, number of rotable bonds ≤3, number of hydrogen bond doners ≤3, number of hydrogen bond acceptors ≤3, total polar surface area ≤110, and logSw (aqueous solubility) ≥ −4.5. 
I am little confused by the figure and what the text says.  In the text, they seem to have relaxed the MW cutoff, but the figure shows that anything not Voldemort Rule compliant is tossed.  They also preferred that the compound has at least one aromatic peak (for easier NMR detection).  They purchased 1008 from Chembridge, solubilized at 200 mM in DMSO-d6 (ease of NMR detection, again) and then tested the solubility at 1 mM in water.  I would have added some salt here, 50 mM, but that is a quibble.  For purity, they claim a low level of impurity (< 15%)!!!  To me, this is a whole lot of impurity.  But, as has been noted here, purity levels vary from library to library.
Solubility Testing:  They then made sure to experimentally test every fragment for solubility.  I can agree more emphatically with this approach.  Bravo!  They go into great detail, which I will not attempt to replicate here, but thanks to open access, they have included the scripts in the supplemental.  Acceptable compounds had > 0.1 mM aqueous solubility.  For me, this is too low, but to each their own.  They ended up with 893 total fragments (89% passed).  The real data I would like to see is how many fail if the cutoff is set at 0.5 mM or higher.  
Pooling: They then describe their pooling strategy.  I like open access articles for a lot of reasons, and tend to overlook small editorial problems (typos, grammar, etc.), but in this case, let me rant.  The authors state in the text that a random mixing of compounds would lead to severe overlap, exemplified in 3a.  To me, it does no such thing. 

Their approach is very similar to the Monte Carlo-based one that has previously been discussed on this blog.  Their final pools contain 10 fragments at 20 mM (I assume in 100 % DMSO-d6). 
Screening: They also acquired the 1H spectrum, STD (-0.7 ppm, > 1 ppm from any methyl), and WaterLOGSY spectrum of every pool for future reference.  This is a very clever approach as the STD should give no signal while the WaterLOGSY should give inverted peaks for all compounds in the pool (when interacting with a target they will be "right-side up").  Again, the figure may show that (I think if you blow up the figure the WaterLOGSY spectra does have peaks) but it is very difficult to see. 
Three of the 90 pools (3.3%) showed peaks in the aromatic region, most likely due to aggregation (they observed precipitation).  I would like to know if those compounds showed STD peaks also had those methyl groups within 1 ppm of the saturation frequency.  I would also like to know if they removed those compounds from the library, or just dealt with it.  For a paper with a great level of detail, it falls flat in this respect.  
Screening is performed at 10uM Target: 500uM ligand and the following parameters: acquisition time of 1 s, 32 dummy scans, and relaxation delay of 0.1 s, followed by a 2 s Gauss pulse train with the irradiation frequency at −0.7 ppm or −50 ppm alternatively. The total acquisition time was 15 minutes with 256 scans.
Screen Analysis: One of the first things they noticed was that there were difference between the reference spectra (plain water) and the screening sample (protein buffer).  They decided they could not automate the entire process and instead just scripted the data processing and display.  Then they confirmed each putative active as a singleton. 
What they are putting together is a "One Size Fits All" process.  I give them credit for doing this, but I think that you cannot find a single NMR-based process for all targets.  In particular, I think they could have used more typical conditions for the reference spectra.  The paper then goes on and discusses their application to targets of interest.  For me, that is irrelevant.  This paper is an excellent companion to the Current Protocol paper, and due to open access, most likely to get far more citations.

12 March 2014

Off-rate screening (ORS)

Molecules that dissociate slowly from their target proteins are potentially useful because they can have a long-lasting effect even if they are rapidly cleared from circulation. However, it is next to impossible to predict whether a molecule will dissociate slowly or not. Moreover, the correlation with binding affinity is poor: weak binders generally don’t stay bound to their target for long, but even tight binders often rapidly dissociate. In the early stages of lead discovery most folk are focused on affinity, and it is usually only much later that kinetics enters in. In a new paper in J. Med. Chem., James Murray, Paul Brough, and colleagues at Vernalis introduce a technique that moves kinetics to the front of the line.

The technique, off-rate screening (ORS), relies on surface plasmon resonance (SPR), which is already commonly used to study binding kinetics. The trick here is using SPR to screen products in unpurified reaction mixtures. An initial fragment with known affinity is modified, and products screened for slower dissociation. Of course, the concentration of desired compound is likely to vary from mixture to mixture, but the great thing about looking at compound dissociation is that it is a zero order reaction: it does not depend on concentration. The researchers use mathematical simulations to show that even if the yield is only 5%, a product with a 10-fold slower dissociation rate constant could still be detected. Since off-rates can vary by orders of magnitude, this is not such a high bar.

Of course, simulations are one thing, but how does the technique actually work in practice? The researchers show examples on two targets, one using some of the early compounds for their HSP90 program, the other some of their PIN1 inhibitors. For PIN1, the researchers resynthesized some of the molecules in plastic tubes, which caused leaching of plastic into the reaction mixtures. Nonetheless, for both proteins the dissociation rate constants measured for unpurified reactions were very close to purified molecules, generally differing by less than 30%.

The researchers also tried subjecting compounds to eleven reaction conditions typically used in medicinal chemistry, evaporating the solvent, and testing the products; the idea was to see if the reagents or other components in the reaction mixture would interfere with the assay. Happily in all cases the dissociation rate constants differed by less than 20%, again pointing to the robustness of ORS.

Of course, as with any technique, there are limitations. Since the screening compounds are not purified from their starting materials, the desired products must dissociate sufficiently slowly from the protein to be distinguishable from other components in the reaction mixture; dissociation rate constants greater than about 1.2 s-1 appear to be challenging. Also, if the starting material itself has a slow dissociation rate from the protein, it may be difficult to differentiate this from a low yield of slowly dissociating product. The researchers note that both cases could be addressed by changing the temperature, either lowering it to slow the dissociation rate constant or raising it to increase it.

All in all this is a nice approach, and it will be interesting to see how widely it catches on.

05 March 2014

Flexible fragment linking vs the transcription factor EthR

Transcription factors have a well-earned reputation for being extremely difficult targets. Although the literature is littered with inhibitors of various transcription factors, most of these turn out to be of questionable validity, to put it politely. A recent paper in Biochem. J. by Sachin Surade, Tom Blundell, and collaborators at the University of Cambridge and the Ecole Polytechnique Fédérale de Lausanne-EPFL reports what looks to be the real deal.

The researchers were interested in a protein called EthR, a transcription factor from Mycobacterium tubercuolosis involved in antibiotic resistance. Unlike many other transcription factors, this one contains an allosteric binding pocket known to bind lipophilic molecules. Armed with this knowledge, the researchers performed a thermal shift assay using a library of 1250 fragments at 10 mM each, which resulted in 86 hits that stabilized the protein by at least 1 °C. These were then tested for their ability to disrupt the interaction between EthR and DNA using surface plasmon resonance (SPR), and 45 of them showed greater than 10% inhibition at 0.5 mM. Reassuringly, only 1 of 45 fragments that had shown no stabilization in the thermal shift assay showed more than 10% inhibition here, suggesting that the thermal shift assay had a low false negative rate.

Confirmed hits were characterized by full dose-response curves and soaked into crystals of EthR, resulting in several co-crystal structures. Compound 1 was particularly interesting because two copies of it bound to the central hydrophobic channel, which was only possible due to conformational changes in the protein. Also, although the likely natural ligand of EthR appears to make only hydrophobic contacts to the protein, the carbonyl of compound 1 makes hydrogen bonds. In one of the two bound molecules, the interaction is with an asparagine residue of EthR; in the other, it is with a water molecule.


Swapping the cyclopentyl ring to a phenyl to yield compound 5 gave a slight loss in potency but simplifies subsequent modifications, and crystallography revealed that it binds in the same manner as compound 1. More significantly, linking two molecules of compound 5 via a disulfide bond (compound 9) improved the affinity by more than two orders of magnitude.

Of course, disulfides can react with cysteine residues in a protein – a fact that can be rather useful for finding inhibitors. Thus, it was essential to demonstrate that compound 9 was really binding non-covalently to the protein rather than acting through an unrelated mechanism. Happily, the researchers were able to determine the co-crystal structure of compound 9 bound to EthR, confirming that it binds in the same manner as the two molecules of compound 5, including the two hydrogen bonds. (Unfortunately though, none of the crystal structures appear to be deposited in the protein data bank.)

Compounds 1 and 9 were both tested for their activity to enhance the effect of the antibiotic ethionamide in Mycobacterium tubercuolosis cultures, and both were active, though with similar potencies despite their very different affinities to the isolated protein; it seems likely that the disulfide bond would be reduced in the bacterium. It will be interesting to replace this with a more stable linkage (amides were also tried but did not improve affinity).

One interesting conclusion is that “flexible fragments in the library can lead to a more efficient exploration of chemical space.” This is exemplified by the fact that floppy fragment 1 binds in two somewhat different conformations to the two sites on the protein. Having some flexibility in the early stage of a project can be useful, and another reason not to be too rigid in assembling a fragment library.

03 March 2014

FABS-ulous Screening Against Membranes

The blog is running on a 2 hour delay today thanks to the winter storm (we actually got a nothing burger here from it).
If you follow this blog, and actually read what I say, you will know I have a 19F-fetish.  Thus, whenever another paper comes out, I gravitate towards it.  Claudio Dalvit is really one of the primary (if not THE) drivers of 19F NMR screening development.  He has been discussed on this blog often.  Most recently, back in October, when he published an example of n-FABS against a membrane target, FAAH.   Now, he is back with this paper: "Fluorine NMR-based Screening on Cell Membrane Extracts".  I was immediately transported back to my days at Lilly where in our group we came up with the great idea to try to screen (using STD) against crude membrane preps.  I don't remember much but my lab mate being unsuccessful in the end for any number of reasons.  Obviously, the development of a robust, biophysical technique which can be applied to intact cells, cell lysates, or membrane preps would be a significant addition to the entire biophysical toolbox.  Currently, only biochemical assays largely based upon fluorescence can do this.  n-FABS, as decribed previously, relies on the substrate of the target (which is labeled with at least one 19F atom) being converted by target action into product, and thus causing a chemical shift change in the 19F.  This is easily detected by NMR and voila, an assay is born. This work is an extension of the previous work on FAAH and very similar to this work by Brian Stockman.  The 19F chemical shift of substrate and product are easily differentiated and roughly quantitatable:
The proper controls showed that this activity is solely due to the TOI.  What makes this assay so appealing is shown in the next figure:
This figure shows the 1H spectrum of the reaction at 2hr (top) and 24hr (bottom).  There is virtually no difference in this spectrum, indicating that it is impossible to follow the substrate due to large signals from detergents and endogenous protonated signals.  For me this is the key to this.  We all know membrane proteins are hard to do, especially with fragments.  I have always wondered where 19F fits in the biophysical toolbox, especially in light of recent discussions where it presumed that 19F could out perform 1H.  In discussions, I have said that 19F runs circles around 1H when the ligands are highly aliphatic.  Well, this is the converse, and still just as true, when the sample matrix is ugly with "other stuff", in this case the stuff that keeps the target in solution.  One major drawback is that this approach is NOT a binding approach, and thus would be of limited utility against non-enzymatic membrane targets, such as a majority of membrane targets.  In the majority of membrane targets, SPR may be the most robust approach.

24 February 2014

Fragments vs bacterial DNA ligase: triumph of structure-based design

Fragment approaches have been used successfully against several anti-bacterial targets (see for example here, here, and here). In a recent issue of ACS Med. Chem. Lett., a team of researchers from Astex and GlaxoSmithKline report another potential weapon in the ongoing war against bugs.

The researchers were interested in bacterial DNA ligase (LigA), which is essential for DNA replication, is highly conserved among numerous types of bacteria, and is quite different from its human counterpart. They started by screening ~1500 fragments against S. aureus LigA using a combination of X-ray crystallography (soaking), ligand-observed NMR (WaterLOGSY), and thermal shift assays. Hits that made it through this gauntlet were then evaluated by isothermal titration calorimetry (ITC) and prioritized in part by ligand efficiency. One of the best molecules was compound 3.

The chlorine atom of compound 3 bound in a hydrophobic pocket of the enzyme. Wary of the potential reactivity of this motif, the researchers replaced it with a trifluoromethyl group; they also removed a nitrogen from the pyrazine ring to provide a vector for fragment growing. The resulting compound 10 had slightly improved potency.


Examining the structure of the initial fragment also revealed a water-mediated hydrogen bond, and by enlarging the triazole to a 6-azaindole 6-azaindazole (compound 12) the researchers were able to make this hydrogen bond directly while also more effectively filling the pocket, providing a satisfying 70-fold boost in affinity. However, close inspection of the crystal structure and computational modeling suggested that this molecule was binding in an energetically unfavorable conformation. Simply adding a nitrogen to the pyridine ring alleviated this problem, providing another 15-fold boost in potency (compound 13). This molecule also showed antibacterial activity against a number of Gram-positive pathogens.

This is a brief but elegant paper that demonstrates the power of crystallography and modeling to drive a fragment-derived medicinal chemistry effort. It will be fun to watch this story progress.

19 February 2014

Poll results: how do you store your fragment libraries?

The results are in, and it looks like there is wide diversity in how folks store their working fragment libraries:


Of the 79 votes, the largest number, roughly 42%, keep their compounds at -20 °C. The next largest category was room temperature (29%), with -80 °C (16%) and +4 °C (13%) rounding out the list.

There were also some good comments to the original post giving more details as to solvent, use of inert gas, etc. These parameters are more difficult to capture in a multiple-choice poll, so please keep those examples coming.

17 February 2014

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

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

HCV has recently had drugs approved for its treatment, but as with any virus, different modes of treatment are important.  The ATP-dependent helicase activity is found in the C-terminal 2/3 of the NS3 protein. Helicase activity is straight forward to measure and there has been some success in terms of non-viral specific inhibitors.  The inhibitors found to date have been found to act through undesireable mechanisms, but with a wealth of structural information there is no reason why helicase is inherently undruggable.  With this information in hand, they decided to target site 3+4 (green sticks are DNA from the structure), near the most conserved residue W501.  The ATP-binding site is 1+2 for reference. 
 Their first approach was to screen the 1,000,000+ corporate compound collection.  As you would expect for a paper blogged about here, they failed to find anything interesting (all the inhibitors worked by undesireable modes).  So, on to the FBDD campaign, to save the day once more.  The used a "shotgun" approach with their fragment screen:

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

They then clustered the best hits into 9 chemotypes:

 They used an "Analog by Catalog" approach and soaked or co-crytallized the best compounds into crystals.  S6, S7, and S9 were not found to bind to helicase in the crystallization trials and were deprioritized.  S5 was found at Site 3+4, but also others.  S1-4, and S8 were found to bind solely to site 3+4 (12 examples shown overlain). The key feature of this is the compounds are centralized in a wide groove over W501.  The topology of the binding site (wide groove and small lipophilic pocket) meant that optimizing for potency could be challenging.
From this, they decided S2-S4 were the most promising.  In the end, the focused on the S2 indole series as the most promising.  The S2 stereotype 1
was found from an STD-NMR screen of 3 fragment per sample (300 uM fragment and 3.5 uM helicase).  They then, much to my heart's delight, they reached into the NMR cabinet for line broadening and competition experiments confirming it binds in site 3+4.  X-ray confirmed the binding mode, but potency was not improved with chemistry.  So back into the NMR cabinet they went: a methyl resonance assay, 
 15N TROSY showing peaks shifting upon addition of a derivative of 1, and 19F NMR!  OMG, how awesome is this?  

In terms of the chemistry, removing the Br does not change the potency, but did change the orientation of the compound in the binding site.  Further elaboration led to this compound 19 (3 uM and 0.23 LE):
It contains a nitro group, think what you may.  In order to confirm the binding affinity of the compound without immobilizing protein, they used the methyl resonances to do the titrations.  The two separate peaks they followed gave values of 32 and 28 uM (+/- 8).  Given the broadness of these peaks, I think this is a pretty decent assay, although it is an order of magnitude different than the biochemical Kd.  However, subsequent structural studies revealed that there is significant structural dynamic differences between pH 6.5 and 7.5.  ITC gave the same number (33 uM and enthalpy driven); however, the ITC had to be run at high compound concentration and a different pH.  They then went off the deep end and decided to use CD (I can't link to a previous post of using CD because we have never had a post where someone used it).  With a horrible assay (don't even get me started on near-UV CD as a readout of tertiary structure), they got reasonably close to the Kds determined by ITC and methyl-NMR.  

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

12 February 2014

Fragments vs NAMPT, maximum ligand efficiencies, and off-target activities

The enzyme nicotinamide phosphoribosyltransferase (NAMPT) is essential for the synthesis of the important cofactor NAD and thus an intriguing target for blocking cancer cell metabolism. In two recent papers, researchers from Genentech, Forma Therapeutics, Pharmaron Beijing, and Crown Biosciences describe how they used fragment-based approaches to discover new inhibitors of this enzyme.

In the first (J. Med. Chem.) paper, Peter Dragovich (Genentech) and collaborators start with a screen of 5000 fragments using surface plasmon resonance (SPR) at the relatively low concentration of 100 µM. This yielded 283 hits which were retested at 150 µM and also competed with a known high-affinity inhibitor; noncompetitive fragments, which presumably bind outside the active site, were discarded. This winnowed interesting hits to 118 fragments, each of which was characterized in full dose-response curves. Only 6 were extremely weak (KD> 2 mM) or nonspecific, while 35 were quite potent (KD< 100 µM).

As an interesting aside, the substrate for NAMPT is nicotinamide, and this was characterized by SPR as having a remarkably high ligand efficiency (LE) approaching the “soft limit” Teddy recently discussed. The researchers suggest:

The LE exhibited by nicotinamide for NAMPT is the highest we have observed for a fragment lead and, given that NAMPT is highly optimized to efficiently bind this substrate, may approach an upper limit of this parameter for such molecules.

Keep in mind that Genentech has done lots of screens, so this is a significant statement. Indeed, I can think of only a few fragments (here and here) with comparable LE values.

But back to NAMPT. More than 30 co-crystal structures of fragments bound to the enzyme were solved, and several of these fragments were advanced. In doing so a variety of information was used, including data from molecules previously discovered in-house and elsewhere. Lots of nice SAR are presented, and if you’re into structure-based drug design I’d strongly encourage a close reading of the paper. Just to give you a flavor, compounds 12 and 13 (blue), despite their structural similarity, bound in very different orientations. A bit of engineering led to compound 15, and crystallography revealed that only a single enantiomer of a racemic mixture binds to the enzyme. Borrowing information from other NAMPT inhibitors led to the potent single enantiomer compound 17; the other enantiomer is 250-fold less active. Further modification yielded an orally active molecule with activity in a mouse xenograft model.


In the Bioorg. Med. Chem. Lett. paper, members of the same team describe two other series of molecules derived from fragments – and provide some important warnings about interpreting data.

One series (not shown here) was optimized to nanomolar potency in biochemical assays and antiproliferative cell assays. However, the team did a series of careful follow-up studies to show that these molecules are probably acting through off-target mechanisms. For example, the molecules do not reduce NAD levels as they should, and addition of the product of NAMPT did not rescue the cells, as it would were NAMPT the primary target.

For the other series, compound 7 (red above) was characterized crystallographically bound to NAMPT. Initial attempts to improve affinity were unsuccessful, but the co-crystal structure of another fragment suggested that replacing the pyrazole moiety with a simple phenyl group would be tolerated, leading to compound 25. Subsequent fragment growing ultimately led to Compound 51, with low nanomolar potency in both biochemical and cell-based assays. Importantly, this molecule did reduce NAD levels in cells, and the antiproliferative effects could be rescued by adding the product of NAMPT. Taken together, these data show that compound 51 is a nanomolar inhibitor of NAMPT both biochemically and in cells.

The importance of such rigorous characterization is driven home by a footnote, in which the researchers reveal that compound 51 was previously alleged to be an inhibitor of glucose transporter 1 (GLUT1). This was published in a high-profile journal, and several chemical suppliers now sell this compound (called STF-31). Although the current paper does not explicitly say so, it is possible the results in the earlier paper could be attributed to NAMPT inhibition rather than GLUT1 inhibition.

In the hope that views on STF-31 will evolve, I’ll close this Darwin Day post with a quote from The Descent of Man:

False facts are highly injurious to the progress of science, for they often long endure; but false views, if supported by some evidence, do little harm, as every one takes a salutary pleasure in proving their falseness; and when this is done, one path towards error is closed and the road to truth is often at the same time opened.

10 February 2014

Pushing the Limit

Dan's recent post discusses the limits of fragments binding to PPIs.  This paper from a while back came to my attention recently and I think it is important to bring up for discussion.  In it, they discuss the physical limits of binding.  They start with this:
Protein−ligand binding is a delicate balance between the loss of entropy resulting from complexation and the enthalpy gained by forming favorable contacts with the protein.
Entropy changes comes from linking two fragments, loss of internal flexibility, and reorganizing water in the binding site.  Current thinking (2 years ago) provides that in terms of favorable energy, van der Waals forces are the primary driver of affinity, while H-bonding and electrostatic interactions drive specificity.  Then they revisit this seminal paper from Kuntz et al but with the intent of exploring ALL biophysical properties rather than drug like ones.  For this study, Ligand Efficiency is DeltaG divided by the HAC. 

If van der Waals forces are the primary driver of affinity, there should be a correlation between affinity and size/contact area. 
There is not.  In terms of efficiencies, the median efficiency is -0.34 kcal/mol*atom.  Putting that in terms of buried surface area (BSA), they determined that the median efficiency is -23 cal/mol*A^2 (Angstrom squared).  To compare, if you look at only solvent accessible area, this value goes down to -7 cal/mol*A^2.  However, despite their inherently larger binding areas, macromolecules do not bind with greater inherent affinity than small molecules.  They argue that this is due to better "burying" of the small molecules.  As expected the most ligand efficient compounds are small, highly charged compunds buried in highly charged sites.  The limit is -1.75kcal/mol*atom, but a soft limit of -0.83 kcal/mol*atom is proposed.  

For maximal binding efficiency, they found that 90% of these interactions involve a charge-charge interaction or a metal ion.  In fact, the most efficient have several charge-charge interactions.  It is known the most efficient ligands are small, but not all small ligands are highly efficient.  So, what makes this difference?  As would be expected (at least I expected it), the longer the distance between charged groups the less efficient the interaction. 
For every 1A drop in average contact distance, the maximal efficiency goes down -0.41 kcal/mol*atom.  Wait!  What about desolvation you ask?  Isn't the entropic cost of desolvation in charged molecules very high?  In many of the highest efficiency complexes, there is water in the binding sites, so not all of the water is displaced, the authors state.  They also state that the charges in the binding pocket may not be fully solvated because the pockets around the charge are so small.  Yeah, I am not happy with that explanation either. 

So what makes maximally affinity?  Kuntz et al. said after 15 heavy atoms your affinity plateaus.  In fact, Kuntz showed that it is exceedingly rare to find an affinity >-15 kcal/mol, arguing that this is due to biological effects, namely clearance.  This paper argues that that cutoff is "seredipitously random or manmade".  Other people have argued that as ligands increase in size the maximal efficiency would drop because the number of interactions that need to be optimized increases and the only way to do this is through structural compromises and thus reduced affinity.  The authors of this paper begrudgingly admit this hyopthesis fits their data.

So, what implications does this mean for fragments? Does Kuntz's data mean that fragment libraries should be no bigger than 15 heavy atoms? Should we consider adding charged moieties or even metals?  They argue that this is a source of vast potential improvement for drug design. 

03 February 2014

How weak is too weak for PPIs?

Ben Perry brought up an interesting question in a comment to a recent post about fragments that bind at a protein-protein interface: “At what level of binding potency does one accept that there may not be any functional consequence?” I suspect the answer will vary in part based on the difficulty and importance of the target, and many protein-protein interactions (PPIs) rank high on both counts. In a recent (and open-access!) paper in ACS Med. Chem. Lett., Alessio Ciulli and collaborators at the University of Dundee, the University of Cambridge, and the University of Coimbra (Portugal) ask how far NMR can be pushed to find weak fragments.

The researchers started with a low micromolar inhibitor of the interaction between the von Hippel-Lindau protein and the alpha subunit of hypoxia-inducible factor 1 (pVHL:HIF-1α), an interaction important in cellular oxygen sensing. The team had previously deconstructed this molecule into component fragments, but they were unable to detect binding of the smallest fragments.

In the new study, the researchers again deconstructed the inhibitor into differently sized fragments and used three ligand-detected NMR techniques (STD, CPMG, and WaterLOGSY) to try to identify binders. As before, under standard conditions of 1 mM ligand and 10 µM protein, none of the smallest fragments were detected. However, by maintaining ligand concentration and increasing the protein concentration to 40 µM (to increase the fraction of bound ligand) or increasing concentrations of both protein (to 30 µM) and ligand (to 3 mM), the researchers were able to detect binding of fragments that adhere to the rule of three.

Of course, at these high concentrations, the potential for artifacts also increases, but the researchers were able to verify binding by isothermal titration calorimetry (ITC) and competition with a high-affinity peptide. They were also able to use STD data to show which regions of fragments bind to the protein, suggesting that the fragments bind similarly on their own as they do in the parent molecule. (Note that this is in contrast to a deconstruction study on a different PPI.) Even more impressively for a large (42 kDa) protein, the researchers were able to use 2-dimensional NMR (1H-15N HSQC) to confirm the binding sites.

Last year we highlighted a study that deconstructed an inhibitor of the p53/MDM2 interaction. In that case, the researchers were only able to find super-sized fragments, and they argued that for PPIs the rule of three should be relaxed. The current paper is a nice illustration that very small, weak fragments can in fact be detected for PPIs, though you may need to push your biophysical techniques to the limit.

But back to the original question of how weak is too weak. With Kd values from 2.7-4.9 mM, these are truly feeble fragments. Nonetheless, they could in theory have been viable starting points had they been found prospectively. That assumes, though, that these fragments would have been recognized as useful and properly prioritized. The ligand efficiencies (LE) of all the fragments, while not great, are not beyond the pale for PPIs. Previous research had suggested that much of the overall binding affinity in compound 1 comes from the hydroxyproline fragment (compound 6, which was originally derived from the natural substrate). Not discussed in the paper, but perhaps more significantly, the LLE (LipE) and LLEAT values are best for compound 6, which despite having the lowest affinity is the only compound that could be crystallographically characterized bound to the protein. In the Great Debate over metrics, this suggests that LLE and LLEAT may be more useful than simple LE for comparing very weak fragments.

29 January 2014

Kill Them Bugs!

Bugs are bad.  I hate bugs.  Bugs of all kinds.  In our part of the world we have a particularly noxious, invasive bug called the stink bug.  Ewwww.  And they are everywhere.  And in the winter they are particularly prevalent because they get in your attic, soffets, etc. and then creep into your house.  I would love to be part of a global effort to eradicate these horrible creatures.  I may lose my green bona fides advocating the genocide of an entire species, but so be it.  It is also not so practical, so really not germane to this blog.

However, targeting bacteria is practical, and important.  Antibiotic resistance is on the rise globally and only two antibiotics with novel modes of action have been approved in this century.  Dire consequences meet pressing need.  Many antibiotics with improved efficacy are due to higher to higher potency or resistance to degradation.  But, this avenue has a limited lifespan and novel targets are needed.  Into this breach steps Astra Zeneca, with this paper.  The topoisomerases DNA gyrase and Topisomerase IV Top IV) have already been shown clinically to be validated targets.  The A subunits contains the DNA cleavage domain while the B subunits contain the ATP binding and hydrolysis domain.  DNA gyrase inhibitors also typically inhibit TopIV.  Fluoroquinolones (the DNA complex) and aminocoumarins (the ATP site) target these enzymes. Aminocoumarins have not received much attention to due PK and safety issues. There are a wide variety of ATP-targeting compounds.

Cpds 1 and 2 have been shown by X-Ray to bind in the ATP site and extend outside that site to generate additional interactions with R144.  The team's design goal was a new scaffold that would merge these two compounds attributes.  They chose 2-pyridylureas which had not previously been explored.  Modeling showed that 5-substitution reaches towards R144 with a carboxylate and 4-substitution allows for exploration into more open space.  6-substitution abuts a hydrophobic region and should not be messed with.

Cpds 3-13 were synthesized (or were commercially available) to test these hypotheses with Cpd 6 clearly the best.  Then they explored the 4 and 5 substitutions 9see the actual paper for Tables 1-3).  The chemistry and isozyme exploration they performed was very detailed.  The two best compounds ended up being 31 and 35

Then the paper gets into the details (it's 24 pages long and the results/discussionare pp 5-13).  I highly recommend reading that part on your own.  I am really impressed by the work.  As they discuss, the Xtal structures support many of the design hypotheses.  This cannot be understated.  Fragment-based drug design (and in this case it really is DESIGN) was effective and robust.  In the end, their compounds were able to realize potent inhibition of 4 topoisomerases across three bacterial species. Importantly, bacterial growth was realized through inhibition of both the gyrase and Top IV which is the key criterion for continued optimization.  Efficacy in a mouse model was demonstrated with 35.