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.

Benchmark Your Process

So, not everybody agrees with me on what a fragment is.  As has been pointed out years ago, FBDD can be a FADD.  In this paper, from earlier this year, a group from AZ discusses how FBDD was implemented within the infectious disease group. Of course, because of the journal, it emphasizes how computational data is used, but you skim over that and still enjoy the paper :-). They break their process into several steps.

Hot Spots: This is a subject of much work, particularly from the in silico side.  In short, a small number of target residues provide the majority of energy for interaction with ligands.  Identifying these, especially for non-active site targets (read PPI), is highly enabling, for both FBDD and SBDD. To this end, the authors discuss various in silico approches to screening fragments.  They admit they are not as robust as would be desired (putting it kindly).  As I am wont to say, your computation is only as good as your experimental follow up.  The authors indicate that the results of virtual screens must be experimentally tested.  YAY!  They also state that NMR is the preferred method; 1D NMR in particular being the AZ preferred method.  [This is something (NMR as the first choice for screening) that I think has become true only recently.  Its something I have been saying for more than a decade, but I guarantee my cheerleading is not why.] They do note that of the two main ligand-based experiments, STD is far less sensitive than WaterLOGSY.  There is no citation, so I would like to put it out there, is this the general consensus of the community?  Has anyone presented data to this effect?  Specifically, they screen fragments 5-10 per pool with WaterLOGSY and relaxation-edited techniques.  2D screening is only done for small proteins (this is in Infection) and where a gram or more of protein is available.

Biophysics:  They have SPR, ITC, EPIC, MS, and X-ray.  They mention that SPR and MS require high protein concentrations to detect weak binders and thus are prone to artifacts.  They single out the EPIC instrument as being the highest throughput.  [As an aside, I have heard a lot of complaints about the EPIC and wonder if this machine is still the frontline machine at AZ.]  60% of targets they tried to immobilize were successful.  They also use "Inverse" SPR, putting the compounds down; the same technology NovAliX has in their Chemical Microarray SPR.  In their experience, 25% of these "Target Definition Compounds" still bind to their targets. 

They utilize a fragment-based crystallography proof of principle (fxPOP).  Substrate-like fragments (kinda like this?) are screened in the HTS, hits [not defined] are then soaked into the crystal system, and at least one structure of a fragment is solved.  This fragment is then used for in silico screening, pharmacophore models, and the like.  So, this would seem to indicate that crystals are required before FBDD starts.  They cite the Astex Pyramid where fragments of diverse shape are screened and the approach used at JnJ where they screen similar shaped fragments and use the electron density to design a second library to screen.

As I have always said, there are non-X-ray methods to obtain structural information.  AZ notes that SOS-NMR, INPHARMA, and iLOE are three ways.  These are three of the most resource intensive methods: SOS-NMR requires labeled protein (and not of the 15N kind), INPHARMA requires NOEs between weakly competitive ligands (and a boatload of computation), while iLOE requires NOEs of simultaneously binding ligands.  I think there are far better methods, read as requiring fewer resources, to give structural information more quickly (albeit at lower resolution).

The Library:  The describe in detail how they generated their fragment libraries.  They have a 20,000 fragment HCS library.  The only hard filter is to restrict HA less than 18.  I fully support that.  They also generated a 1200 fragment NMR library biased towards infection targets.

The Process:   The authors list three ways to tie these methods together:

1. Chemical Biology: Exploration of binding sites/development of pharmacophores.  I would add that this is also for target validation.  As shown by Hajduk et al. and Edfeldt et al., fragment binding is highly correlated to advancement of the project. 
2. Complementary to HTS.  At the conference I am at today, one speaker (from Pfizer) said that HTS was for selectivity, FBDD was for efficiency (or Lord, here comes Pete with that one).  I really like that approach.
3. Lastly, stand alone hit generation.  

I think this paper is a nice reference for those looking to see how one company put their FBDD process in place. Not every company will do it the same, nor should they.  But there is a FBDD process for every company.

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.   

Fragments in the clinic: AZD5363

As illustrated earlier this year, kinases have been a fertile field for fragments. In a recent issue of J. Med. Chem., Jason Kettle and colleagues at AstraZeneca describe the discovery of AZD5363, a protein kinase B (PKB) inhibitor currently in multiple phase I clinical trials for solid tumors.

The story actually starts a decade ago, with a collaboration between Astex and the Institute of Cancer Research. The two organizations were interested in PKB (also known as Akt1), which has a central role in the PI3K signaling cascade. Virtual, biochemical, and crystallographic screens identified small fragments such as substituted pyrazoles and 7-azaindole (which astute readers will recognize as the starting point for vemurafenib) that bind to the so-called hinge region of PKB. Structure-guided fragment-growing ultimately led to compound 2.

This compound, while potent against PKB, was unselective against the related protein kinase A (PKA), so further crystallographically-enabled medicinal chemistry led to CCT128930, with 30-fold selectivity against PKA. This compound had limited oral bioavailability, so further optimization led to compound 3.

In 2005, Astex partnered this program with AstraZeneca, which is presumably where the current paper picks up. Although compound 3 had good pharmacokinetics and was selective against PKA, it inhibited the kinase ROCK2, which regulates blood pressure; it was also a modest hERG inhibitor. Extensive SAR explorations around the hinge-binding element, the amine, and the aromatic group were not productive, but substitution off the benzylic position was tolerated. Adding a basic substituent dramatically reduced hERG binding, but at the cost of oral bioavailability. However, adding a variety of neutral, polar substituents led ultimately to AZD5363, which has no detectable hERG inhibition, good selectivity against ROCK2, and improved solubility and cell activity.

This paper nicely illustrates some of the challenges in drug discovery: high-affinity molecules were obtained relatively quickly, but these still required a huge amount of effort to achieve selectivity, oral bioavailability, and other properties. Indeed, only three heavy atoms differentiate compound 3 from AZD5363, but it took a heroic effort to get there.

Finally, it is worth noting that this research was done at Alderley Park, which attendees of Fragments 2009 will remember fondly. Sadly, AstraZeneca has announced that they will be closing this site. There are many very talented scientists there, and Practical Fragments wishes all of them the best of luck.

Ligandability

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

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

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

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

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