25 May 2015

Charting new chemical space for kinase inhibitors

Since the advent of imatinib, kinase inhibitors have become a thing in drug discovery, with more than two dozen already approved. Indeed, kinases are the targets of more than a third of reported fragment-derived compounds to reach the clinic. Given that all 500+ human kinases bind ATP, you would think that the chemical space would be pretty well picked over by now. As Hongtao Zhao and Amedeo Caflisch at the University of Zurich show in a recent Bioorg. Med. Chem. Lett. paper, this is not the case.

The researchers started by extracting all 26,668 kinase inhibitors with MW < 600 Da and IC50 or Ki < 10 µM from the ChEMBL database; three quarters of these were better than 1 µM. These have been tested in aggregate against 367 kinases, of which 88 have more than 100 reported inhibitors!

The molecules were then deconstructed into 10,302 ring-containing fragments, such as benzene (7.1% of kinase inhibitors), 2-methylaminopyrimidine (3.5%) and N-methylmorpholine (2.3%), as well as more obscure structures. In fact, more than half (53%) of these fragments were not found within 7.5 million commercial compounds in the ZINC database. In other words, many fragments that form a part of known kinase inhibitors are not represented among commercial compounds, despite many vendors offering “kinase inhibitor libraries”.

What about the reverse question, analyzing commercial molecules for new kinase inhibitors? The researchers focused on possible “hinge-binding” fragments – those that have at least one hydrogen bond donor and one acceptor in close proximity to one another so as to be able to interact with a conserved region of kinases. Not surprisingly, more than half of the fragments (5681) found by deconstructing the kinase inhibitors fit this description. More interestingly, 196,904 potential hinge binders resulted from deconstructing the ZINC compounds, of which only 1% had been reported as kinase inhibitors.

Digging into the data more deeply, the researchers classified hinge binders as monocyclic, bicyclic, and multicyclic. This analysis revealed that the overlap between kinase inhibitors and commercial compounds was particularly low for multicyclic fragments. This intuitively makes sense: medicinal chemists often turn to ring construction to fix all manner of problems, both pharmaceutical and IP-related, so the under-representation in commercial compounds is likely because medicinal chemists introduce rings into simpler starting molecules. Also, from a molecular complexity standpoint, multicyclic ring systems may be less likely to bind to a wide variety of proteins than simpler monocyclic fragments.

More than five years ago Practical Fragments highlighted a paper from Abbott describing their efforts to generate novel hinge binders. As this and related analyses show, there is still plenty of chemical space left to explore and exploit.

21 May 2015

Just Because its called "Fragment-Based"...

When my parents were young and just starting out (the late 60s) they needed a vacuum cleaner.  So a vacuum cleaner salesman came to the house eager to make the sale.  This was the era of the Space Race, plastics, and so on.  So, it was cool to be associated with this.  The eager young vacuum cleaner salesman showed my parents the fine, sleek design of the vacuum cleaner (it was a ELECTROLUX).  It was long and sleek, looking like a rocketship (or a dachshund).  It came with a lot of nozzle attachments.  One in particular was shaped to be very narrow, and get in between the couch and wall for example.   He was particularly proud of this piece: the AEROspace tool.  He even wrote it down as such.  You must have a "AEROspace" tool for your vacuum.  It was an example of great marketing, associate yourself with something very popular to make something mundane appear special.     

So, this paper comes along from Moffatt Cancer Center and USF targeting ACK1 (aka TNK2).  This paper purports to have a "innovative fragment approach" (mix and match).  I love novel approaches to libraries.  So, let's dive in. There is a good deal of work that has been done with ACK1 by Amgen, OSI/Astellas, and others.  Dasatinib and Bosutinib also show activity against ACK1 also.  Based upon all of this previous work and the knowledge of the pyrimidine core they decided to approach the target as laid out in Figure 1.
Figure 1.  Library Design Approach
So, this paper doesn't interest me, although they do come up with some potent compounds, from a what they discovered aspect, rather from a more philosophical aspect. What does it mean to do fragments?  This harkens back to the Safran Zunft challenge.  To me, FBDD is about using simple, small molecules.  Pyrimidine series 9 does not fit any definition of a fragment (Cpd 8 would, but it was never tested AFAIK).  What they did was identify a variety of fragments which would be inputs for creating a small library of lead-like compounds.  However, for this to be "Fragment-based" I would think that they would tested each individual component and prioritized chemistry based upon that.  Or maybe they could have made R3=H.  They don't report Ligand Efficiencies (cue Pete Kenny).  This is simply not "Fragment-based" anything.  Nor, do I think this approach is novel.  Nor do they explain how this is novel.  
So, I think we have entered the time when anything that uses a fragment in the design process is fragment based.  Based on this line of thinking, Nicolaou's total synthesis of Taxol is "Fragment-based". Beware those talking the talk, but not walking the walk.

18 May 2015

Predicting protein ligandability and conservation of fragment binding modes

Say you have a protein target, and you want to know whether you will be able to find small molecules that bind to it. A fragment screen can give you a good idea as to the likelihood of success: if you find lots of different fragments with high affinities (say, better than < 0.1 mM), your protein is likely to be highly “ligandable.” On the other hand, if you get very few fragments, and most of them are weak (> 1mM), be prepared for a slog.

Of course, it would be even better if you didn’t have to do a physical screen at all, and two recent papers show how a computational approach may be sufficient. The first, by Dima Kozakov, Sandor Vajda, and their collaborators at Boston University and Acpharis is a detailed how-to guide in Nature Protocols. The second, in Proc. Nat. Acad. Sci. USA by Dima Kozakov, Adrian Whitty, and Sandor Vajda and their collaborators at Boston University, Northeastern University, and Acpharis, addresses some interesting questions about fragment binding.

The main program is called FTMap (also highlighted here); it and several related programs are accessible through a free web server. It is remarkably easy to use: just provide a protein data bank (PDB) ID or upload your own structure and away it goes.

The program works by docking a set of 16 virtual probes (such as ethanol, acetonitrile, acetamide – the largest molecule is benzaldehyde) against a protein and looking for “hot spots” where many fragments cluster. Previously the researchers demonstrated that known ligand-binding sites in proteins tend to be computational hot spots, where at least 16 probes bind. (Note that due to their small size, multiple probes of the same type – acetone, for example – can bind within the same hot spot simultaneously.) In other words,

The strongest hot spot tends to bind many different fragment structures, acting as a general “attractor.”

On the other hand, a hot spot with fewer probe molecules is unlikely to have enough inherent binding affinity to bind to ligands with low micromolar or better affinity.

A related program is called FTSite, which focuses on more thoroughly characterizing the best binding sites. Other programs allow for protein side chain flexibility, docking custom probes, or docking against ensembles of protein models such as generated by NMR structural methods.

The PNAS paper goes further to ask about ligand deconstruction. Specifically, why is it that when a larger ligand is dissected into component fragments, sometimes the fragments recapitulate the binding modes seen in the larger molecule, and sometimes they do not? The answer:

Because a substantial fraction of the binding free energy is due to protein-ligand interactions within the main hot spot, a fragment that overlaps well with this hot spot and retains the interacting functional groups will retain its binding mode when the rest of the ligand is removed.

The researchers support this assertion by examining eight literature examples in which structural information was available for fragments and larger ligands (some of which we’ve covered here, here, and here). In cases where the isolated fragments overlapped with 80% of atoms in probe molecules within a given hot spot, the fragment binding mode remained conserved. Also, these fragments tended to have high ligand efficiency values.

This is neat stuff, and it will be fun to see how general it is. I’m especially happy to see that all of the software is free and open access. Even though I’m hardly a computational chemist, I tried playing around with it and found it remarkably fast and easy to use. So if you have a protein with no known ligands, FTMap can find hot spots, and if they’re particularly promising, this should embolden experimental work.

13 May 2015

When Fragments don't deliver...

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

Tuberculosis is a scourge caused by a mighty nasty bug.  People have been using fragments to try to combat it for a long time: 2009 and 2014: targeting pantothenate synthesis and biotin synthesis. AstraZeneca join the party (just as Entasis spins out) with this paper.  In it, they describe their NMR fragment screen combined with a HTS biochemical screen targeting thymidine synthesis.  All the TK inhibitors are TMP or thymidine analogs.  The HTS of 120,000 compounds lead to multiple 1-30 uM active site binding (confirmed by HSQC NMR) inhibitors.  Compound 1
Cpd 1.  3.6 uM, 0.46 LE, 3.54 LLE.  
Figure 2.
was chosen as the basis for the hit to lead campaign.  Modeling suggested that the pyridone core is a thymidine mimic (Figure 2). This novel core allowed to reach sub micromolar potency within 10 compounds of the original hit.  The pyrimidine core was also potent, but not as much as the pyridone.  Pyranones were inactive, as was any other group but the cyano at the 2 position. Crystallography was a key to verifying the binding mode of the compounds.  One point of this is that verified means within 1 A of the predicted pose.  SAR led to the fused pyridinone, a 2 nM inhibitor, which nonetheless had no cellular activity.  The propose that this is due to the ionic nature of the compound, but ureas, amides, and sulfonamides did not afford the desired activity. 
Figure 3.  Fused Pyridinone showing X-ray Contacts

So, as is becoming a very common theme in fragments, they decided to use fragments to try to discover an alternate scaffold.  Using TROSY (HSQC for big proteins), they screen 1200 fragments in pools of 6.  Those fragment hits, termed FRITs which is a first for me (I think I like it.), with a LE greater than 0.25 were followed up by X-ray crystallography.
Figure 4.  Napthyridinone FRIT.  590 uM, LE=0.3. 
Figure 4. shows the best FRIT and its crystal contacts.  Combining this with the knowledge from the cyanopyridinone series, a virtual library was created and docked.  Hidden in their description, it appears that the library was passed by real chemists to prioritize the cpds.  Kudos.  With very limited SAR, they achieved significant potency (Figure 5), but still without cellular potency. 
Figure 5. 200 nM, LE=0.34.  

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

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

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

11 May 2015

Fragments vs Factor VIIa

The blood coagulation cascade involves several serine proteases, many with an appetite for arginine-containing peptides. The polar, basic guanidine moiety of arginine tends to wreak havoc on the pharmacokinetic properties of small molecules, sparking an intensive search for replacements. A few months ago we described how researchers were able to use fragment screening to find an alternative moiety for one member of the blood coagulation cascade. In a recent paper in J. Med. Chem., Daniel Cheney and colleagues at Bristol-Myers Squibb report their work on another, factor VIIa.

The researchers started by filtering commercially available small molecules to look for those with ≤ 17 non-hydrogen atoms, ≤ 3 rotatable bonds, and without anything nasty. This computational work left them with 18,000 fragments. These were then clustered based on similarity, and 200 compounds were chosen by chemists as having the potential to bind in the deep S1 pocket, where the guanidine normally binds.

At the same time, the 18,000 fragments were computationally docked (using Glide) against several different crystal structures of factor VIIa; this “ensemble docking” was used to account for the protein flexibility observed in various structures. This led to a further 250 fragments being chosen.

The 450 fragments were then assessed in biochemical and STD NMR-based assays, and 41 were soaked into crystals of factor VIIa, resulting in 27 structures with fragments bound in the S1 pocket. Happily, 12 of these fragments were – unlike guanidine – neutral. All of them were quite weak (even by fragment standards), with Ki values ranging from 8-19 mM, though searching for related fragments led to some with slightly improved affinities. However, when examining the binding mode of fragment 7, the researchers realized they could use it to replace a more basic moiety in their existing lead series (17), yielding compound 18. Although this reduced the potency, it dramatically improved the permeability. Also, the researchers stated that they were able to subsequently improve the potency, with details to come in a subsequent paper.


This is another nice example of using fragments to fix part of a larger molecule, though it is not necessarily easy. The researchers note that other attempts to append new fragments onto their existing scaffold were unsuccessful, likely due to geometric incompatibilities. This paper is also an illustration of how long it can take to get things published. One of the authors gave a nice presentation on some of this work at an ACS meeting in 2012, and there’s a line in the paper referring to a publication that came out “shortly after completion of this work” – in 2006! Still, late or not, it is nice to see the story in print, with a promise of more to come.

06 May 2015

More Notes from DDC 2015

Dan and I both gave our thoughts on the conference last week.  But there was more than just the talks.  There were roundtables.  I chaired one on using kinetics and thermodynamics to drive medchem for the PPI track.  It was a lively discussion.  It was agreed that dyed in the wool enzymologists are priceless.  Kinetics is useless if clearance is the driving force, so this becomes a PK/PD issue.  But does it always have to be?  Paul Belcher from GE shared the On/off rate map (Figure 1) that shows what realm of binding you are in depending on your reates.  Paul also mentioned that Tony Gianetti, formerly of Genentech, used HSA and SPR to assess a more realistic picture of how compounds interact in plasma.  In terms of earlier phase uses, one of the round table attendees mentioned that she had seen talks of people using kinetic data to drive medchem.  She couldn't recollect who, so if any of our astute readers have references please share.  We also discussed using kinetic data to rank compounds with similar IC50.  A question was raised whether or not kinetics can be a good surrogate for receptor occupancy? 

Figure 1.  On/off Rate Map: A = affinity limited efficacy, B= on rate limited efficacy, C= rapid off rate limited, D= slow off protected efficacy
So, what about thermodynamics?  By and large, this was viewed as retrospective only.  Paul from GE did share that they have an app note of using SPR to generate thermodynamic data (I can't figure out how to link it, so if you want it contact me (or Paul) and we can send it). 

The main thrust was that neither kinetics nor thermodynamics are used to make prospective medchem decisions, rather they are used to justify in retrospection. Specifically for PPIs, the consensus was that the focus should be on on rate because you have to the compound in there when you can (i.e. when the complex is "open" enough). 

Derek Cole of Takeda led one of the FBDD round tables: Practical Aspects of Fragment Screening. Here is a picture, courtesy of Bjorn Walse of Saromics.  
His notes are replicated below:
Round table became figure 8 with two tables, with 2-3 deep seats and 40 -50 participants. FBDD expertise from novice to experts, including Teddy Zartler, Dan Erlanson, Gregg Siegal, and Andrew Petros. Large attendance highlights the number of newcomers to FBDD, confirmed by Dan Erlanson during opening when 2/3 of attendees indicated this was their first CHI FBDD meeting. Very lively debate/discussion covering 4 primary targets.

1. Designing and building and storing libraries. Discussed size of library i.e. 1000 or 40K. Agreed that a good library of 1000 should yield lots of high quality hits. Best to keep HA low, 10 - 16 (majority in 12 - 14 range). Discussed 3D vs. flat fragments. Flat give higher hit rate and should be major part of library. 3D likely give lower hit rate but may yield very exciting hits. Discussed complexity and the need for fragments to have enough complexity, but not two pharmacophores. (ref. Astex work). IF just starting out, best to buy a vendor library, e.g. Maybridge or others, which are fully characterized.

2. Screening techniques. NMR and SPR most common. Both very good. Tm - fast, inexpensive and can correlate with x-ray. What to do if no biochemical activity. Might be fine if below sensitivity of biochemical assay, i.e. very small fragment, however if larger fragment, need to understand why not being detected.

3. Potential pitfalls. Make sure library is soluble above assay conditions, i.e. > 1 mM in aqueous buffer (1 - 2% DMSO). Check for aggregation. Run SPR clean screen.

4. Fragment hit follow up. Think of fragments as seeds to identify protein compatible pharmacophore. SAR by catalog of similar fragments or fragments which present a similar pharmacophore is of great value. May find fragments which are much more potent, efficient, or which crystallize (if original was unsuccessful). Good to design diverse library, but similarity in fragments is different than similarity in large molecules, small 1-atom changes can have profound effect on binding mode, potency, etc.
 
If I missed any other highlights, please add them in the comments, or email me and I can add it in.  

04 May 2015

Sloppy science

As regular readers may have discerned, I’m favorably disposed to most of the papers I highlight. They may have flaws or inconsistencies, but, with rare exceptions, I generally just ignore particularly problematic publications. Last year Teddy introduced the term PAINS-shaming to draw attention to – how shall we phrase it? – less salubrious specimens. Building on this alliterative theme, today’s post is about sloppy science. A fundamental tenant of sound science is to consider alternate explanations for results. Ignore this at your peril.

An example was published in J. Cancer Prev. The researchers were interested in a mutant of isocitrate dehydrogenase 1 (IDH1), a hot cancer metabolism target. They screened 500 fragments in a functional spectrophotometric assay, with each fragment present at the very low concentration of 5-10 µM. One of these inhibited the mutant protein by 80% – pretty impressive for a fragment. Until you look at the structure: 2-(3-trifluoromethylphenyl)isothioazol-3(2H)-one (shown below).

Fifty years ago, researchers showed that this chemical class (isothiazolinones, also called isothiazolones) could react with thiols, like this:

Isothiazolinones have been categorized as PAINS, though they do not show up in the original computational filters. However, Pete Kenny has (repeatedly) stated that having a dubious structure should not automatically disqualify a compound from further investigation, so what else do we know about isothiazolinones?

Well, there’s this paper, which concludes a discussion of isothiazolinones by stating:
We could not develop these into useful compounds and ultimately the structure–activity relationship (SAR) was uninterpretable. Most insidiously, there were encouraging aspects of sharp SAR as there always are with these PAINS, but this is eventually overwhelmed by flat and nonsensical SAR. Unpredictable nonspecific cytotoxicity was manifest. We found our compounds to be rapidly reactive with thiols under assay conditions.
Of course, one could argue that this is anecdotal. But then there’s this paper, with the unambigious title “Isothiazolones; thiol-reactive inhibitors of cysteine protease cathepsin B and histone acetyltransferase PCA”. The first line of the abstract states:
Isothiazolones and 5-chloroisothiazolones react chemoselectively with thiols by cleavage of the weak nitrogen-sulfur bond to form disulfides.
The researchers go on to demonstrate this using both small molecules and proteins, and some of the compounds they investigate are structurally quite similar to the hit here.

So in all likelihood the fragment described in the most recent paper reacts with one or more cysteine residues in IDH1, of which there are several. It is notable that the researchers conducted their assay in the absence of added thiol reducing agents, so modification of the cysteines would effectively be irreversible under their assay conditions.

What we have here is the re-identification of a known thiol-reactive molecule without any acknowledgement or apparent awareness that the molecule is reactive. I have no problem with covalent inhibitors, but I do have a problem with a generically reactive molecule being touted “for a future lead development”, as the researchers state in the abstract. It took me just minutes to track down the references above, and the fact that neither the researchers nor the reviewers did so is inexcusable.

Granted, this paper is not published in a high profile journal, and the easiest response would be to ignore it. It is certainly not the only one of its kind. Doing so, however, implicitly endorses sloppy science. This paper will undoubtedly pad the resumes of the authors. Highlighting its problems will hopefully make others wary of wasting time with this new "selective inhibitor."

29 April 2015

Tenth Annual Fragment-based Drug Discovery Meeting...Teddy's Thoughts

Dan posted his thoughts here.  Like Dan, CHI put me to work: I chaired the first session in PPIs, co-taught (with Dan) our award winning FBDD course to 22 attendees (a new high which I think shows that interest in FBDD is still growing), moderated a breakfast roundtable on kinetics and thermodynamics,  judged posters.  All of this during weather which made the natives shiver, and me feel like spring is really here (64F and cloudy).  

First off, there was live tweeting of talks by me and a few others: @iceobar, @moleculesmith, and others.  Beware that the Dubai Diamond Conference was also going on that week.  

In the PPI track, just as last year, fragments were a key component to various projects.  Mark McCoy, Merck (and he taught me more about NMR than just about anyone, whether he will admit it or not) gave a great talk on HDM2-p53.  I took away a few things from his talk which I really liked.  Merck (legacy S-P) really relies on NMR structural information: HSQC-based screening, NMR-based Ki,  and NMR-driven docking.  I was particularly intrigued with the NMR-driven docking because they were able to generate 80+ models with a 75% success rate that was confirmed by X-ray (once that was enabled).  They were forced down this path because they went 2 years without a X-ray structure. 

Joe Patel of AZ talked on SOS-RAS.  What I liked was that AZ uses a modified Voldemort Rule (which Harren Jhoti incorrectly attributes to me; I am the Boswell to Rod Hubbard's Johnson): HAC less than/equal20, cLogP less than5, less than3 rings, less than5 rot bonds, less than 3 HBD, and less than 5 HBA.  Their initial X-ray screening ended up at a wall, so they went to a covalent approach. 

Troy Messick of the Wistar gave a nice talk on using fragments and SBDD to drug an "undruggable" target.  I think this is exactly this is exactly the kind of success that has led FBDD to be ubiquitous these days.  I have to admit I have and am working with the Wistar on the NMR component of their screening, so I may be biased. 

I won't go into the various talks from the FBDD track,  However, echoing Dan this is really a great conference.  My main take home themes is that FBDD is really mainstream.  It's no longer the red headed stepchild to other hit generation processes (apologies to my ginger friends).  Biophysics is also seeing a huge growth, having grown up with FBDD, but really finding a lot more uptake outside of that space.  Next week I will post summaries of roundtables and some useful information. 

27 April 2015

Tenth Annual Fragment-based Drug Discovery Meeting

Last week marked the tenth anniversary of CHI’s three-day Drug Discovery Chemistry conference in San Diego. The conference consists of six tracks, with three happening simultaneously. The FBDD track is the only one which dates all the way back to the beginning in 2006. In fact, this is the oldest recurring fragment conference, predating both the Royal Society Fragments meetings as well as the independent FBLD meetings.

It’s worth reflecting on how far fragments have come since 2006. Back then, as Rod Hubbard (Vernalis and University of York) noted, most of the talks were prospective and methodological. Even as late as 2010 there were talks describing how dedicated fragment groups needed to be shielded from the larger organization. Now fragments are mainstream: a large fraction of the talks in the protein-protein interaction track involved fragments, as did both plenary keynote addresses to the entire conference.

Harren Jhoti’s keynote focused on lessons learned at Astex over the past 15 years. There has been some debate in the literature over ligand efficiency (LE), and one slide that struck me was a summary of 782 dissociation constants (measured by ITC) against 20 projects. The vast majority of these compounds had LE > 0.3 kcal/mol/atom. Given that Astex has put multiple fragment-derived drugs into the clinic and was acquired by Otsuka in one of the largest M&A events of 2013, the metric appears to have some utility.

Still, it’s important not to be dogmatic, particularly for difficult targets. Harren described a program for XIAP/cIAP where they started with an extremely weak fragment with LE < 0.2, but its binding mode was sufficiently interesting that they were willing to work on it. This program also revealed the importance of biophysical measurements, as functional activity was uninterpretable and even misleading until higher affinity compounds were discovered.

One theme throughout the conference was the observation that fragments bind at multiple sites on proteins. Harren noted that Astex researchers have found fragments bound (crystallographically) to 54 sites on 25 targets – an average of 2.2 sites per target. Some targets are even more site-rich: Joe Patel (AstraZeneca) performed a crystallographic screen on a complex of Ras and SOS and found four binding sites, including one previously discussed here. In this effort, 1200 fragments were screened in pools of 4, and in one case two fragments from the same pool each bound only when they were both present at the same time – each fragment alone showed no binding by NMR or crystallography.

Troy Messick (Wistar) described his work against the EBNA1 protein from Epstein-Barr virus. An HTS screen of 600,000 compounds came up with at best marginal hits, but soaking 100 different Maybridge fragments into protein crystals led to 20 structures, with fragments bound to four different sites. Some of these fragments were then merged to give cell-active compounds with good oral bioavailability.

Rather than exploring different ligands binding at different sites, Ravi Kurumbail (Pfizer) described an interesting case of the same ligand binding at different sites. A screen against the kinase ITK identified a (large) fragment that could bind both in the adenine binding pocket as well as a nearby pocket, as determined crystallographically. Determining the affinities of the same fragment for the two sites necessitated some clever SPR and enzymology, but did lead to a highly selective series.

In terms of targets, BCL-family proteins were certainly well-represented, featuring heavily in talks by Chudi Ndubaku (Genentech, selective Bcl-xL inhibitors), Mike Serrano-Wu (Broad Institute, MCL-1 inhibitors), Zaneta Nikolovska-Coleska (University of Michigan, MCL-1), Roman Manetsch (Northeastern, Bcl-xL and MCL-1), and Andrew Petros (AbbVie, BCL-2 and MCL-1). Of course, it was AbbVie (neé Abbott) that pioneered BCL inhibitors as well as FBLD in general, and I was happy to hear that there is a renaissance occurring there, with fragment approaches being applied to all targets, even those undergoing HTS.

Finally, there were some interesting practical lessons on library design. Peter Kutchukian described how the Merck fragment library was rebuilt to incorporate more attractive molecules that chemists would be excited to pursue. There is an ongoing debate as to whether a fragment library should be maximally diverse or contain related compounds to provide some SAR directly out of the screen, and in the case of the Merck library the decision was to target roughly five analogs in the primary library, with a secondary set of available fragments for follow-up studies.

The utility of having related fragments in a library was illustrated in a talk by Mark Hixon (Takeda) about their COMT program. A HTS screen had failed, and even a screen of 11,000 fragments came up with only 3 hits (with an additional close analog found by catalog screening). Remarkably, all of these are extremely closely related, but other analogs in the library didn’t show up; had they not had multiple representatives of this chemotype in their library they would have come up empty-handed.

In the interest of space I’ll close here. Teddy will post his thoughts later this week, and please share your own. CHI has announced that next year’s meeting will be held in San Diego the week of April 19. And there are still several great events on the calendar for this year!

20 April 2015

Tethering versus RNA

Last week we highlighted one of the less common fragment-finding methods, and today we turn to another. Tethering uses reversible disulfide exchange chemistry to trap thiol-containing fragments near binding sites. Back when we developed the technology at Sunesis we used cysteine residues in proteins. We occasionally discussed applying it to nucleic acids, but at the time it was hard to make a good business case. Now that microRNAs (miRNAs) have become hot, there is more interest in going after nucleic acid targets, and in a recent paper in Molecules Kiet Tran and Peter Beal (UC Davis) and Michelle Arkin (UC San Francisco) have done just that.

The researchers were interested in an RNA sequence that is cleaved in cells to generate miR-21, a potential cancer target. The idea is to find small molecules that bind to pre-miR-21 and prevent its processing to the mature miRNA. To perform Tethering, the researchers first introduced a thiol group into adenosine and incorporated this into RNA. They made two separate versions of pre-miR-21, with the modified adenosine at a different site in each, and also made a control RNA with a completely different sequence.

Next, they incubated the modified RNAs with 30 different disulfide-containing small molecules under partially reducing conditions and used mass spectrometry to identify those that covalently bound. As expected most showed minimal binding, but there were a couple hits. One of these, a 2-phenylquinoline, bound to both modified versions of the pre-mR-21 as well the control RNA, suggesting non-specific binding. In fact, 2-phenylquinoline is a known intercalator, so while its identification is not surprising, it does validate the ability of Tethering to identify binders. The other hit, however, appeared to be specific for one of the two pre-mR-21 sequences.

Of course, there is still a long way to go; it is unclear how much affinity the hit has for the RNA, or how specific it would prove if tested against a large panel of decoy RNAs. A key challenge for Tethering – as with many fragment-finding methods – is figuring out what to do with a hit. This is all the more true with RNA, about which we’ve written several times over the years. Still, one nice feature of Tethering is that it allows one to target a specific site of interest. Also, the covalent (disulfide) bond helps with both crystallography and modeling. It will be fun to watch this story develop.

13 April 2015

Substrate activity screening for irreversible PAD3 inhibitors

Of all the ways to find fragments, one of the more unusual is substrate activity screening, or SAS, which we first discussed here. The idea is to make and screen libraries of potential enzyme substrates and transform the best ones into inhibitors. In a new paper in J. Am. Chem. Soc., Jon Ellman and coworkers at Yale University describe how they used SAS to discover irreversible inhibitors of protein arginine deiminase 3 (PAD3), a potential target for neurodegenerative diseases.

The four human PADs (conveniently named PAD1-4) transform arginine residues in proteins to citrulline residues, with subtypes distributed differently across different tissues. The researchers started by making a library of more than 200 fragment-sized guanidines (the unique side-chain moiety in arginine) as potential substrates. These were then screened in a colorimetric assay. Several compounds were found to be processed by the enzyme, though all were very weak substrates (Km > 10 mM).

Next, the best substrates from three different chemical series were optimized for activity. For example, substrate 4a was grown to substrate 15a.


Finally, the substrates were converted to irreversible inhibitors by replacing the guanidine with a known chloroacetamide warhead. This coopts the natural mechanism of the enzyme, which relies on covalent bond formation between an active-site cysteine residue and the substrate. Within a given series, the better the substrate, the better the resulting inhibitor (for example, inhibitor 15b is more potent than inhibitor 4b). However, these correlations did not hold across series.

The best compounds were also tested for selectivity, and some of them were at least 10-fold selective for PAD3 over the other three PADs.

Last year we highlighted a paper that described several difficulties encountered (and overcome) using SAS to find inhibitors of the protease urokinase. (The comments to that post are well worth reading as they include contributions from the corresponding author of the paper as well as a former Ellman postdoc who is using SAS.) However, according to the current paper, SAS was relatively straightforward for PAD3 – another confirmation that different targets require different approaches.

08 April 2015

Fragment-based methods in drug discovery

FBLD generates a plethora of reviews, as evidenced by Practical Fragments’ annual round-ups (see for example 2014, 2013, and 2012). However, for the past three years there have been no new books. The drought has now ended, starting with the publication of Methods in Molecular Biology Volume 1289, edited by Anthony E. Klon of Pennsylvania Drug Discovery Institute. Computational chemistry is probably one of the most rapidly changing disciplines within FBLD, and thus it is appropriate that this is the primary focus.

The book is part of the Springer Protocols series, which offers highly specific step-by-step instructions. Many of the chapters have a common organization: Introduction, Materials, Methods, and Notes. While this can work well for established molecular biology techniques such as cloning, it can be trickier to apply to computational approaches. Some of the chapters are quite brief and assume extensive specialized knowledge, while others are extremely detailed. Of course, it is impossible to satisfy everyone; hopefully the following summary will help you find what is most useful for you.

Part I (Preparation) consists of five short chapters. The first is by Rachelle Bienstock, editor of the most recent (and also computationally intensive) book. As we’ve noted, water plays a pivotal role in protein-ligand interactions, and Rachelle concisely but thoroughly summarizes available computational methods. Chapter 2, by Yu Zhou and Niu Huang at the National Institute of Biological Sciences in Beijing, outlines how to use DOCK to assess binding site druggability. In chapter 3, Raed Khashan (King Faisal University, Saudi Arabia) describes a free software tool called FragVLib for generating virtual fragment libraries to compare different ligand binding pockets. Chapter 4, by Jennifer Ludington (formerly of Locus Pharmaceuticals), discusses practical issues in preparing a virtual fragment library, such as conformer and partial charge assignment. Finally, in chapter 5 Peter Kutchukian discusses how he and his Merck colleagues enlisted medicinal chemists to help fill the gaps in their fragment collection.

The second section is titled Simulation. In chapter 6, Kevin Teuscher and Haitao Ji (University of Utah) summarize “fragment hopping,” including an extensive table of available software tools. Chapter 7, by Olgun Guvench (University of New England), Alexander MacKerrel (University of Maryland), and coworkers describes SILCS: site identification by ligand competitive saturation. This program, developed by SilcsBio LLC, soaks proteins in virtual solutions containing very tiny fragments (think propane and methanol) to look for binding sites. Molecular dynamics simulations include methods to prevent aggregation of the ligands or denaturation of the protein.

Chapter 8, by Álvaro Cortés-Cabrera, Federico Gago (Universidad de Alcalá, Madrid) and Antonio Morreale (Repsol Technology Center, Madrid), describes how ligand efficiency indices can be used to guide fragment growing. Of course, metric skeptics will still ask, “sure it works in practice, but does it work in theory?” And in chapter 9, Jui-Chih Wang and Jung-Hsin Lin (Academia Sinica, Taipei) introduce a new scoring function for fragment-docking, including several pages of detailed instructions for implementing it in AutoDock. As we’ve noted, calculating binding affinities for fragments can be difficult, and the new function seems to be accurate to about ±2.1 kcal/mol for a series of compounds tested

Part III, Design, begins with another chapter by Rachelle Bienstock in which she outlines the process of fragment-based ligand design, highlighting various software tools available at each stage. This includes library design, growing, linking, and downstream considerations such as ADME. Chapter 11, by Zenon Konteatis of Agios, is a brief primer of the process, including an example for the kinase TGF-beta. The last chapter in this section, by Jennifer Ludington, focuses on binding site analysis to assess whether a protein site is druggable (or at least ligandable). She focuses on the procedure used at Locus Pharmaceuticals, which involved soaking a virtual protein in a solution containing fragments and then lowering the chemical potential of the system until only the tightest fragments remain bound. Clusters of probe fragments indicate possible hot spots.

Finally, Part IV consists of Case Studies, starting with a chapter on kinase inhibitors by Jon Erickson (Lilly). More than a third of FBLD-derived clinical candidates target kinases, so it is always good to have an updated overview, though there is at least one structural error.

The last two chapters are both by Frank Guarnieri, founder of Locus Pharmaceuticals and currently at Virginia Commonwealth University School of Medicine. These are highly opinionated (with lots of first-person singular pronouns) and fun to read. They both describe the simulated annealing of chemical potential (SACP) approach that formed the basis of Locus (and is also discussed by Jennifer Ludington above). Chapter 14 describes a small molecule erythropoietin (EPO) mimetic program. The protein EPO binds to and activates a dimeric receptor, and a small molecule functional mimetic would indeed be an exciting breakthrough. Unfortunately, the primary data presented are not compelling, and I remain unpersuaded, though perhaps readers are aware of more convincing evidence.

Chapter 15 describes the Locus program to develop a highly selective orally available p38 inhibitor. The discussion offers a rare window into life at a small biotech, including disagreements over strategies and interpretation of data. It now appears that p38 is probably not a good target for inflammation, which had unfortunate repercussions:

The business decision at Locus to put so many resources into this program along with other questionable business decisions resulted in the company going bankrupt after about 10 years in existence.

Some of the most important lessons are negative, and it’s nice to see these appear in print. Success stories are inspirational, but this chapter is a healthy reminder of the very many things that must succeed for fragment-based approaches to yield new drugs.

06 April 2015

When a Lead is a Lead

As we keep on saying, epigenetics is big.  So, today we present another paper on an old friend, BRD4.  This paper is a follow up from previous work where they used docking and X-ray to find the thiazolidinone fragment hit that was elaborated as shown below (Figure 1), but with potency in the single digit micromolar in vitro and double digit in cellulo
Figure 1.  Previous work from these authors.
In this work, they continue developing this scaffold investigating the reversed sulfonamide(Figure 2)
Figure 2.  Reversed Sulfonamide
which had significantly improved activity.  Cyclo-aliphatic rings showed increases in potency, but with larger rings also decreasing ligand efficiency.  Aromatic rings decreased potency and larger groups (rings with linkers) were not tolerated at all.  

The crystal structure of the cyclopentyl derivative was solved and was seen to have a different binding mode from the original fragment.  In this case, the WPF shelf is NOT the major binding site for the compound.  In the end, they ended up with
Figure 3.  End Result of this study.  
This is compound is potent (albeit not super potent), ligand efficient, with cell-based activity,  selectivity, and good PK properties.   What I really like is that final sentence of the conclusion:
a promising BRD4inhibitor and a useful lead for further anticancer drug development.

01 April 2015

Shapely fragments

Tired of all those planar aromatics in your compound collection? Three-dimensional fragments are all the rage these days, and chemical suppliers are happy to oblige. After the stunning success of their FUNK library, SerpentesOleum has come out with a new offering, Tesseract Products (TP). All of the TP fragments are guaranteed to be nice, plump, and squeezably soft. For example:


Even more exciting, the company has hired a crack team of physicists to produce a line of 4-dimensional fragments with principal moments of inertia greater than 1. Don't delay, order your TP today, and wipe away the 2-D blues!

30 March 2015

Politburo Approved

Viral, tropical diseases are really cool because they have great names. e.g. Dengue or Breakbone Fever or Chikungunya ("that which breaks up").  The great thing about many viral diseases is that they are dependent upon proteases for many things. (And yes, I know how that sounds.)  Proteases have nice, well defined active sites that you can fill quite well and shut them down. In this paper, the authors use fragment-peptide merging to inhibit Dengue protease.  

This is really an extension of previous work.  The original work used capped peptides with a warhead with very good potency (down to 43 nM).  They then investigated retro, retro-inverse, semiretro-inverse, and nonretro di- and tri-peptides.  This lead them to use a tri-peptide (Arg-Lys-Nle) in two generations: first an arylcyanoacrylamide and then to N-substituted 5-arylidenethiazolidinone (thiazolidinediones and rhodanines).  These second generation hybrids had increased membrane permeability, in vitro binding, in cellulo antiviral activity.  Based on docking, they decided to investigate Nle sitting in P1', in contrast to previous site preferences and then merge it with fragments from an optimized capping moiety. 
1.  Starting Point Hybrid Peptide
The investigation of Nle replacements led to the phenylglycine molecule, with 4x greater affinity:
9.  Phenyl-glycine hybrid
They, then chose three hybrids (including 9) and put two different caps on them:
Rhodanine Cap
Acrylamide cap

Compared to the benzoyl cap, the acrylamide was 2x better while the rhodanine was 5x better.  But, wait, doesn't the Politburo condemn all uses of rhodanines?  Of course not.  In this case, the rhodanine was selected through rigorous analysis: and they have selectivity (this assay is fluorogenic).  They are perfectly aware of the general distaste people have for rhodanines and address the concerns. All of this together, leads to the final compound (below).
This is a really nice piece of starting with a tool (covalent peptides) and working to generate drug like molecules with favorable properties. 

25 March 2015

We read these papers so you don't have to

Glycogen Phosphorylase is one of those systems that you hear about all the time; it was the first allosteric enzyme discovered.  It's been discussed here and here previously on this blog.  It is one of those ubiquitous enzymes and has been the subjet of a lot of research looking for allosteric modulators.  The majority of allosteric inhibitors are heterocyclic compounds with a well known history.  This paper wants to add to that history. 
The authors start with what appears to be a dreadful understanding of what fragment-based hit generation is.
"Lead-like discovery refers to the screening of low molecular weight libraries with detection of weak affinities in the high micromolar to millimolar range".
Maybe its just me, but we've been over this before.  Lead-like molecules, as Kubinyi showed, are large and decorated; fragments are not.  So, they got the low molecular weight thing right, but the name of the method wrong. Maybe an error in the proofing...
Starting on previous work, the chose a 21 member heterocycle library (Figure 1.) to investigate a morpholine-based peptide mimetic.
Figure 1.  Fragment Library
Activity was determined by an enzymatic assay with a maximal compound concentration of 222mM.  They also used 22mM, 56 mM, 111mM leading to Table 1 and some crazy SAR (N-Boc-ing 8 yielded 9 with >200x potency).  
Table 1. 
The key compound is 7, with 25 microM IC50;  while 6 (minus the methyl ester) is 1000x less potent.  Strange things are afoot at the Circle K.  They then docked 7 (and a few other "second tier" compounds).  They see "moderate" binding for all compounds; yet, one of these compounds is more than 50x more potent than the others.  We've been down this road before...

23 March 2015

Rad fragments revisited

Two years ago we highlighted a paper in which Cambridge University researchers identified fragments that bind to the protein RAD51, which in turn binds to the protein BRCA2 to protect tumor cells from radiation and chemotherapeutics. In a new paper in ChemMedChem, Marko Hyvönen and colleagues describe how they have grown these fragments into low micromolar binders.

One of the best fragments identified in the previous work was L-tryptophan methyl ester (compound 1), so the researchers naturally tried substituting the methyl group. A phenethyl ester (compound 5c) gave a satisfying 10-fold boost in potency, but this turned out to be the best they could get: shorter or longer linkers were both less active, and modifications around the phenyl ring gave marginal improvements at best. Also, changing the ester to an amide decreased affinity. They were, however, able to improve potency another order of magnitude by acylating the nitrogen (compound 6a).


At the same time, the researchers made a more radical change to the initial fragment by keeping the indole and replacing the rest with a sulfonamide (compound 7a). This also boosted potency. Further optimization of the sulfonamide substituent improved the affinity to low micromolar (compound 7m) and increased ligand efficiency as well.

The original fragments had been characterized crystallographically bound to the protein, but the researchers were unable to obtain structures of the more potent molecules, though they did sometimes see tantalizing hints of electron density. Competition studies with known peptide inhibitors also suggested that the molecules do bind in the same site as the initial fragments.

The thermodynamics of binding were characterized using isothermal titration calorimetry (ITC). Although the initial fragments owed their affinity largely to enthalpic interactions, the more potent molecules were more entropically driven. This, the researchers suggest, could partially account for the failure of crystallography despite extensive efforts: the lipophlic molecules can bind in a variety of conformations.

Some have argued that enthalpic binders should be prioritized, but this study illustrates one of several problems: even if you start with an enthalpic binder, there’s no guarantee it will stay that way during optimization.

This is a nice paper, but I do wonder how much affinity there is to be had at this site on RAD51. Given the micromolar affinity of the natural peptides, nanomolar small-molecule inhibitors may not be possible. Then again, like other difficult PPIs such as MCL-1, perhaps the right molecule just hasn’t been made. How long – and how hard – should you try?

18 March 2015

Mass Spec Screening in Solution

Mass spectrometry is a technique that most people are familiar with, as a QC tool.  It also has been demonstrated as a screening/validation tool.  Native mass spectrometry (nMS) has been discussed here, Weak Affinity Chromatography (WAC) here, and Hydrogen-deuterium exchange (HDX) here.  All of these methods have advantages and disadvantages.  A "new" method is the ligand-observed MS screening (LO-MS).  [I put new in quotes because I know of at least one company that has been using this method for screening for years via a CRO.]

The concept of LO-MS is straight forward (Figure 1) and very similar to WAC.  A mixture of fragments, in this case 384, are mixed with target (NS5B), incubated, and the ultrafiltrated (50kDa cutoff).  This step eliminates the need for the immobilization step in WAC, ensuring the native conformation.  The fragments were at 25 uM, while the target was at 50 uM. 
Figure 1.  Fragments MW 165 and 130 are binders.  MW162 and 150 are not. 
Retained fragments are then dissociated with 90% methanol and those showing intensity higher than the protein-minus control are considered binders (S/N  greater than 10).  In their library, 5% of the compounds were not amenable to mass spec detection, but they included them to increase the complexity of the mixture.  In the end, they ended up with 20 binders in 20 minutes!  They repeated the screen with smaller mixtures (50 and 84 fragments) where they found 12 binders (a subset of the original 20).  As a follow up, they ran the binders by SPR, validating 10 of the binders (50%).  5 out of these 10 gave useable crystals (observable electron density for the fragment) (50%).  They also show how the data can be used to generate Kds (like WAC).

This method raises some issues with me, but first let me say, it sure seems to work, and fast to boot.  From people I know who have used this to screen, they have been very happy.  Here is what bothers me: self-competition in the tube a discussed here and here, this is a non-equilibrium method (variable protein concentration during the ultrafiltration), and it is an indirect method.  For me, I prefer methods that directly detect ligand-target interactions, like NMR, SPR, and nMS.

16 March 2015

Fragments vs p97

The protein p97 is important in regulating protein homeostasis, and thus a potential anti-cancer target. But this is no low-hanging fruit: the protein has three domains and assembles into a hexamer. Two domains, D1 and D2, are ATPases. The third (N) domain binds to other proteins in the cell. All the domains are dynamic and interdependent. Oh, and crystallography is tough. Previous efforts have identified inhibitors of the D2 domain, but not the others. Not to be put off by difficult challenges, a group of researchers at the University of California San Francisco (UCSF) led by Michelle Arkin and Mark Kelly have performed fragment screening against the D1 and N domains, and report their adventures in J. Biomol. Screen.

Within UCSF, the Small Molecule Discovery Center (SMDC) has assembled a fragment library of 2485 commercial compounds from Life, Maybridge, and Asinex. These have an average molecular weight of 207 Da and 15 heavy atoms, with ClogP ~1.5. The researchers used both biophysical and virtual screening.

For the physical screening, the researchers started with surface plasmon resonance (SPR), with each fragment at 0.25 mM. This resulted in 228 primary hits – a fairly high hit rate. Full dose response studies revealed that 160 of theses fragments showed pathological behavior such as concentration-dependent aggregation or superstoichiometric binding. A further 30 showed weak or no binding, 13 were irreversible, and 5 bound nonspecifically to the reference surface, leaving only 20 validated hits which were then repurchased.

The 228 primary hits were also assessed by STD NMR, each at 0.5 mM when possible (some fragments were not sufficiently soluble). Of these, 84 gave a strong STD signal, and 14 of these were also among the 20 SPR-validated hits.

The 20 repurchased fragments were further tested by both SPR and STD NMR, and 13 of them reconfirmed by both methods. The paper includes a table listing all 20 compounds, and one observation that struck me was the fact that all but one of the hits – which had dissociation constants ranging from 0.14 to 1.7 mM – are larger than the library average. Such results could argue for including larger fragments in libraries, though this goes against both molecular complexity theory as well as extensive experience at groups such as Astex.

Next, the researchers sought to discover information on the binding sites. Three fragments could be competed by ADP, suggesting that they bind in the nucleotide-binding site of D1. To narrow things down further, the researchers turned to 13C-1H-methyl-TROSY NMR, in which specific side chain methyl groups of Ile, Leu, Met, Val, and Ala were labeled, and chemical shifts were examined in the presence and absence of fragments. Two of the proposed nucleotide-binding site fragments showed similar shifts as AMP or ADP, further supporting a common binding mode (the third was too weak to test). This was not an easy experiment: the hexamer has a mass of 324 kDa, well above where most people do protein-detected NMR.

Independent of all the biophysical screens, virtual screens were conducted using Glide XP, which suggested that the nucleotide binding site would be the hottest hot spot. Happily, all three fragments that appear to bind to this site scored highly in the in silico work, with two of these within the top 100 fragments. However, the binding sites for the other ten confirmed fragments remain obscure.

This paper serves as a useful guide for how fragment screening is performed on a tough target in a top-tier research group. Although difficult, it is not impossible to advance fragments in the absence of structure. While it remains to be seen whether that will be the case for any of these fragments, the researchers have provided a wealth of data for those who wish to try.

11 March 2015

The Sequel is Never as Good as the Original

We are living in a target-driven environment in Pharma, for both good and bad.  The low-hanging fruit have been plucked and the high-hangers are tough.  But, fragments have proven to be highly utile in liganding these targets.  One drawback with target-based screening is the problem with cellular activity, while it may be easy to generate good activity against the isolated target, in the end you need activity in the cell/animal.  Back in the good ole days, people just skipped the target and went straight into cells: compounds are put on bacterial plates and the microbes die if the compound is anti-microbial.  This is the simplest example of phenotypic screening, the phenotype here being "dead cells". [For a discussion of the history of phenotypic screening, go here.]  Fragments could be the worst case scenario for phenotypic screening as fragment-target interactions are very weak, and very commonly do not exert a biological effect. 

In this paper from Rob Leurs and colleagues, including Iota, the describe a fragment-based phenotypic screen process.  This work is a follow on to previous work from this group discussed here, which I quite liked  So, they have a target (PDEB1) but immediately follow their screening with the phenotypic part.  For the phenotypic screen, they used several different parasitic PDE and MRC5 cell-line as a counter-screen. I won't bore you with any of the experimental details. The compounds are recapitulating known molecules, like benadryl.  Now, I really wanted to like this paper, at least from a process approach.  It appears to my eyes, that all the compounds are pretty much equipotent and cytotoxic.  This is a really disappointing paper in that it doesn't really do anything.  They had shown previously that you could get non-cytotoxic compounds with good inhibition of PDEB1.  They didn't repeat that here.  There is no X-ray, they did before.  The compounds are wholly uninteresting and stretch the imagination to be seen as compounds "with a lot of potential to grow into antiparasitic compounds".

09 March 2015

Are PrATs privileged or pathological?

Pan assay interference compounds – PAINS – have received quite a bit of attention at Practical Fragments. In addition to being a fun topic, the hope is that publicizing them will allow researchers to recognize them before wasting precious resources.

But not all PAINS are created equal. Some, like toxoflavin, simply do not belong in screening libraries due to their tendency to generate reactive oxygen species. I would put alkylidene rhodanines in the same category due to their ability to act as Michael acceptors, their tendency to undergo photochemistry, and their hydrolytic instability. The nice thing about these sorts of molecules is that their clear mechanistic liabilities justify excluding them.

But things are not always so simple, and in a recent paper in J. Med. Chem. Martin Scanlon and co-workers at Monash University, along with J. Willem Nissink at AstraZeneca, describe their experiences with a more ambiguous member of the PAINS tribe: 2-aminothiazoles. (See here for In the Pipeline’s discussion of this paper.)

That 2-aminothiazoles (2-ATs) should be PAINS is not obvious: at least 18 approved drugs contain the substructure. Thus, it was not unreasonable to include 2-ATs in the 1137-fragment library assembled at Monash. But after screening 14 targets by STD-NMR and finding a 2-AT hit in every campaign, the researchers started to become suspicious. They gathered a set of 28 different 2-ATs and screened these against six structurally diverse proteins using surface plasmon resonance (SPR). Many of the 2-ATs bound to 5 of the proteins, and a couple bound to all six. The researchers used 2D-NMR (HSQC-NMR) to further characterize binding and found that the 2-ATs bind to multiple sites on the proteins rather than the desired one-to-one binding mode.

A common source of artifacts is the presence of reactive impurities, so the researchers resynthesized some of the 2-ATs and showed they behave the same, ruling out this mechanism. Solubility was also not a problem. Finally, the ligand-based NMR experiments revealed that the 2-ATs really did appear to be binding to the proteins, ruling out interference from unreacted starting materials or decomposition products.

One structure-activity relationship did emerge: acylation of the amino group dramatically reduced promiscuity of the 2-ATs. However, in the case of 2-ATs with a free amino group, there was little meaningful SAR. Thus, the researchers propose calling these molecules PrATs, or promiscuous 2-aminothiaozles.

Further analysis of high-throughput screening data from the Walter and Eliza Hall Institute and AstraZeneca revealed that 2-ATs were also over-represented among hits. What’s spooky about this result is that most of the screens were done at 10 micromolar – far lower than typical fragment screens.

The researchers freely admit that they have no mechanism for why PrATs bind to so many proteins. I suspect there is something fundamental to be learned about intermolecular interactions here, though how to extract these lessons is beyond me. One gets the impression that the authors themselves have been burned by pursuing PrATs, as they conclude:
On the basis of our findings reported here and our unsuccessful attempts to optimize these fragments against different targets, we have removed 2-ATs from the fragment library.
This paper serves as a thorough, cautionary analysis. As evidenced by multiple approved drugs, PrATs can be advanceable, and we certainly won’t be PAINS-shaming papers that report them as screening hits. If you can advance one to a potent lead, then bless your heart. But be warned that this is likely to be even more difficult than normal.