28 January 2015

Get to Know Your Compounds

One of the first fragment screens I was ever involved with had RNA as the target (this is back when people did anti-bacterial research).  Because of that, I always try to write about targets, not proteins when referring to generic things we wish to find ligands for.  Nucleic acids have secondary and tertiary structure, just like proteins, and thus have ligandable pockets.  We have covered RNA as a target previously.  Well, we get to add another paper to the list.

In this paper from researchers at Goethe-Universität Frankfurt am Main present their results on HIV Tat-TAR.  This target was discussed over three years ago.  I am not particularly impressed with the compounds or the work (even though it included RNA NMR).  I was more impressed with comment made in the paper which hint at the kind of compound understanding we often cite as lacking from academic papers.

First, let's get to the guts of the paper.  They have been trying to identify ligands to this target for years, yielding nanomolar affinities but limited specificity.  Moving to fragments when all else fails, they decided to utilize very simple fragments: benzenes and amines, amidines, or guanidines able to be protonated at physiological pH.  Their fragments were screened in a fluorescent Tat-TAR-peptide assay.   Figure 1 shows the compounds tested.
Figure 1.  Compounds tested.  IC50s shown in parentheses. 
Cpds 1-6 were inactive, but cpd 7 looked promising...at first glance.  As the authors state:
"However, the IC50 value of this compound improves steadily when aqueous solutions are kept under air.  This effect was also found with other compounds, for example tetraaminoquinazoline 23.  The electron rich heterocycles in particular have the tendency to produce false positive results, presumably by forming positively charged oligomers."
I presume that they ran the assay and a few days later went back to re-test the compounds and saw anomolous results.  What really strikes me is that with a 7 mM IC50 upon retesting they saw a number sufficiently different (and that they trusted) to flag it.  They also note that such compounds must be carefully recrystallized and fresh powders ONLY used.   

The rest of the story is not nearly as interesting.  They performed 1H NMR titrations and 2D NOESY to confirm that these compounds are binding to the RNA.  They do some SAR and re-discover cpd 22, a known Tat-TAR inhibitor, that has already been patented.
So, what do we learn here? Understanding your fragments and their potential liabilities in your assay is crucial. 

26 January 2015

Fragments vs PKCθ, selectively

There are more than 500 protein kinases in the human genome, many of which have been tackled with fragments – sometimes all the way to the clinic. Within the universe of kinases, the dozen different isoforms of protein kinase C (PKC) provide an interesting challenge. For example, PKCθ is important in T cell signaling and thus has potential for treating autoimmune and inflammatory disease, but one needs to steer clear of isoforms important for heart function, such as PKCα. In two recent papers in J. Med. Chem., Dawn George and collaborators at AbbVie, WuXi, and Inventiva describe their efforts towards this goal.

The first paper starts as many fragment stories do: a high-throughput screen had come up largely empty. The AbbVie (née Abbott) team had previously constructed a collection of fragment-sized kinase hinge binders, and after screening ~250 of these at 300 µM in a fluorescence (TR-FRET) assay they selected compound 1 because of its structural novelty and ligand efficiency.

Modeling suggested multiple possible binding modes. Crystallography for PKCθ is difficult, but the researchers were able to obtain a structure of the compound bound to a different kinase, FAK. This suggested introducing a positively charged moiety to target an aspartic acid residue in PKCθ, leading to the more potent compound 15a. Additional optimization led ultimately to compound 41, which had moderate potency in cell-based assays, good pharmacokinetics, and 74-fold selectivity against PKCα. The compound also showed activity in a mouse arthritis model, but only at high doses, and was toxic at a slightly higher dose.

That’s where the second paper picks up. The researchers thought that by improving the pharmacokinetics they could lower the dose of the compound required, thereby reducing the potential for off-target effects. By now they had been able to obtain co-crystal structures of some of the more potent compounds bound to PKCθ, which confirmed the proposed binding mode and also gave additional ideas as to how to proceed. Extensive medicinal chemistry ultimately led to compound 17l, with low nanomolar biochemical and cell-based activity as well as good pharmacokinetics.

Unfortunately, this compound did not give stellar efficacy results in the mouse arthritis model. Also, this compound and several others appeared to be toxic to mice, with effects ranging from lethargy to seizures to death. The compounds were screened against panels of kinases and other receptors to try to find the source of these effects, but all to no avail; the compounds were fairly selective. This one-two punch of limited efficacy and unpredictable toxicity led to the termination of the PKCθ program.

These two papers reveal yet again that fragment-based lead discovery is often just the beginning of an arduous medicinal chemistry journey that can lead a long way from Valinor. The final destination here proved to be a dead end, but at least a useful one: it shows that PKCθ is certainly not a straightforward target for arthritis, or perhaps any indication. Kudos to the researchers for publishing this story so other scientists will not have to take the same journey. And at the very least, this compound is a useful probe for dissecting the biology of PKCθ.

21 January 2015

Not Every Clam will Hurt You

I grew up on a wonderful little island called Jamestown (although technically it is Conanicut island and the town is Jamestown).  It was a great place to grow up, especially because in the summer we lived walking distance to the beach.  One of the very cool things about the beach is that it has an awesome sand bar that pokes up at low tide.  That was the most fun part of the beach to me.  One of the things we did was stand on the sand bar and dig our feet into it.  You scrunch your toes into the sand until you hit something hard.  Then you excavate with your toes around it.  If you got a foot or so down (this took some patience) and got lucky you would find a quahog.  Thems is good eating.  Many an hour was spent doing this and bringing home dinner.  Sometimes, you found something hard and started more excavation around it...and WHAM!  Not a quahog, but a razor clam instead! There goes your day as blood starts gushing out of your foot stuck in a foot of mud.  You can come up with a different approach to find the clam, but you still get hurt by razor clams.  Eventually, you give up digging for clams with your feet because you hit one too many razor clams and you get your clams from Zeek's Creek Bait Shop.

We here at Practical Fragments have a great job, we get to pontificate on fragment papers.  As most people know, its Good Cop (Dan)/Bad Cop (Me) by and large.  It works for us and the blog gets read by more than our mothers.  But this is an opinion blog, and as everyone knows (G-rated version): Opinions are like belly buttons, everyone has one.  We welcome contrary opinions, sometimes even try to provoke them.  Dan and I do very little coordinating for this blog beyond the "I will have something for Monday".  So, when we both find something that bothers us, well that's worth discussion.  One topic in particular Dan and I have found is PAINS (Pan Assay INterference Compounds).

PAINS are gaining traction as things to avoid in screening collections; there's even a Facebook page.  The literature is pretty clear as to what these are and why they are bad.  In my eyes, I am fine just removing them all from my screening deck and being done with them.  In fragment space, there is MORE than enough other compounds that I don't worry about missing whatever chemical space they live in.  However, as I have often said, a fragment is like pornography, the viewer knows it when they see it.  As you may know, I am not one for hard and fast rules.  If you want to keep PAINS-like compounds in your collection, fine by me.  BUT, you must be aware that they are PAINS.  You must know that they must be kept to a higher standard of evidence, you must do more controls, etc. And of course, if you are making tools then it doesn't matter if it is a PAIN (Dan and I disagree here.) 

So, Practical Fragments gadfly Pete Kenny has a post up at his (recently renamed blog) about PAINS.  In it, he takes Practical Fragments to the woodshed over PAINS, even though his main point is about how we make decisions on data.  He starts his commentary by pointing to this post and calling it a "vapid rant".  As noted in the comments to my post Pete immediately took exception to it believing the burden of proof should be on the blogger to demonstrate the guilt of the compound(s) in question.  He also cites this post as one that should be wary of calling something crap or pollution.  He then goes in to the ontogeny of PAINS and raises some points:
  • PAINS study is irreproducible because structures and targets are not revealed
  • Only 6 HTS campaigns were analyzed when 40+ were available
  • All screens used Alpha-Screen, so this may not be very "PAN"
He then goes deep into the actual structure of rhodanines and how some are good, or less bad.  I think Pete has lost the forest for the trees, or shrubs.  Its not that there are probably some rhodanines that are NOT bad actors; but we know many are, and these require a higher level of confirmation than other compound classes.  Not every clam you dig for is going to slice your foot open, but when enough do, but after enough do, you change your approach.

19 January 2015

Fragments vs HSP90: Nerviano’s turn

HSP90, an oncology target, is one of those proteins that seems tailor-made for fragments: it has an active site with a predilection for small molecules, it’s easy to work with, and it crystallizes readily. Indeed, at least two fragment-derived molecules targeting this protein have advanced to Phase 2 clinical trials. In a recent Bioorg. Med. Chem. paper, Elena Casale, Francesco Casuscelli, and colleagues at Nerviano describe their efforts against this target.

The researchers started by identifying a fluorinated probe molecule that they could use in a Fluorine chemical shift Anisotropy and eXchange for Screening (FAXS) assay. This is an NMR-based competition method, in which fragments are screened to find those that displace a known ligand, in this case one that binds in the active site. A total of 1200 fragments were screened in pools of 10, each at the relatively low concentration of 50 micromolar. Nonetheless, 23 hits were found, four of which were characterized crystallographically bound to the protein.

Fragment 3 was among the more interesting, both because of its high ligand efficiency as well as its structural novelty. SAR-by-catalog failed to find anything better from 20 compounds tested, and initial fragment growing also proved disappointing. However, a closer inspection of the crystal structure (cyan) revealed the possibility of linking the fragment to the well-known HSP90 fragment resorcinol. This led to compound 8b, which binds about 5-fold more tightly. Crystallography revealed that the molecule (magenta) also binds as expected.

However, the team wisely chose to test synthetic intermediate 7h (in which the hydroxyl groups were still methylated) and this turned out to be even more active than the designed compound. Since the hydroxyls of the resorcinol are essential for binding in other lead series, the team solved the crystal structure of compound 7h (green) and was surprised to find that it binds in a completely different manner than compound 8b; the ligand essentially flips over.
This discovery led to a change in direction for medicinal chemistry, leading ultimately to the low nanomolar compound 12a. Unfortunately this molecule had only modest cell-based activity and was metabolically unstable.

This is a solid, nuts-and-bolts sort of story. Although it does not conclude with a clinical candidate, it does provide a useful window into how fragment-based methods are applied in industry. It is also a reminder to screen all your intermediates and to remember that even subtle changes to a molecule may have dramatic effects on its binding mode. Those surprising shifts can point the way to promising chemical space.

14 January 2015

A Great New Tool....for what?

As has been noted here, frequently, is that in silico design of fragments is very hard, fraught with problems, and often leads to crap.  As was pointed out elsewhere recently, computational tools are getting more powerful, but still don't have chemical intuition leading to suspect structures.  I am assuming that computational scientists have heard the critiques because we are seeing better and better work, with more experimental verification.  Now, what about better structures?  In this paper from Kaken Pharmaceutical and Toyohashi University of Technology, the propose a way to do this.  

In silico tools can be divided into two classes, structure-based and ligand-based design (TOPAS and Flux are two examples of the latter).  These methods are based upon biological evolution: reproduction, mutation, cross-over, and selection.  Mutation and cross-over are vital for creating new chemical structures.  Mutation can be atom or fragment-based.  In a previous study by these authors, the atom-based method was used for the mutation, in which an atom is modified into another atom to explore the chemical space. The method often resulted in a lot of unfavorable structures that contained invalid hetero−hetero

atom bonds such as O−O and N−F. The fragment mutation approach avoids this problem, especially when the fragments are from known molecules (this assumes they were synthesized and thus could be again). This is one key to their approach: chemical feasibility is considered.

Figure 1.
The method (Figure 1) uses a known molecule to "navigate a chemical space to be explored." [I love this phrase, but immediately I think of this.]  The reference molecule is also used to generate the seed fragments (Figure 2), which can be rings, linkers, or side chains.  
Figure 2
 With a good set of seeds, connection rules, and so forth, the key is the mutation and cross-over events.  A parent molecule is randomly selected and then one of three operations occurs: 1. add a fragment, 2. remove a fragment, or 3. change a fragment.  For "Add Fragment", if the base fragment is ring, then a new linker, side chain, or ring is chosen.  If the base fragment is linker or side chain, then a ring is added. "Remove fragment" removes a terminal fragment.  "Replace fragment" is a fragment for fragment swap (Figure 3). The cross-over function is also shown in Figure 3. 
Figure 3
Then they used this protocol to design ligands against GPCR (AA2A and 5HT1A). 
Figure 4.
Figure 4 shows some of the results against AA2A.  They were able to generate a molecule that is very similar to a known active and because of the generation of the fragments these are all presume to be chemically feasible.  
So, my first complaint here is where's the experimental verification?  OK, this is not a medchem journal, but still...  I am not nearly as savvy as some of our regular readers, but I am completely missing the forest for the trees here.  This paper first struck me as pretty neat, but then the "neat-o" factor fell away and I was left asking "what is it for?"  To me, this would seem to be a patent-busting tool.  We need to generate a structure that is very similar to billion dollar compound A, but it cannot contain fragments X, Y, and Z.  Is this better than locking your favorite medchemists in a room with a few pads of paper?  I am not being flippant here.  If I am missing something, please let me know in the comments.

12 January 2015

Choosing fragments and assays

One of the advantages of running lots of fragment screens is that it generates lots of data that you can mine for general trends and insights. Astex and Vernalis have both done this; in a paper just published online in J. Biomol. Screen. Peter Kutchukian and (former) colleagues at Novartis provide their own meta-analysis of 35 fragment screening campaigns.

The Novartis fragment library consists of 1400 fragments with molecular weights ranging from 102 to 306 Da and logP values from -2.19 to 3.9. This library has been screened against dozens of targets using a variety of different methods. The researchers looked at the hit rates and used Bayesian methods to try to answer three broad questions.

What makes a fragment amenable for fragment-based screening?
Many people have found that some fragments hit many targets while others hit none, and the results here are no different. Over a set of 20 targets, only 37% of fragments came up as a hit, as opposed to the 54% that would be expected if the odds of hitting a target were the same for all fragments (and using the hit rates actually observed). Correspondingly, some fragments hit more targets than expected. Indeed, 1.4% hit six or more, which is orders of magnitude more than would be expected by chance. Given justifiable concerns about artifacts, one might be tempted to dismiss these hits, but the researchers found that these frequent hitters turn out to be more likely to generate crystal structures than other active fragments. In other words, these are privileged fragments (think 7-azaindole).

Do these privileged fragments have anything in common? Previous work from Astex and Vernalis has suggested that fragment hits tend to be slightly more lipophilic than non-hits, and this trend is all the more apparent here. In fact, fragments that hit more than five targets had a median logP of 2.47 versus 1.45 for fragments that hit just a single target. Promiscuous fragments also tended to be slightly larger than other fragments, in contradiction to the molecular complexity hypothesis. They also tended to have more aromatic bonds, fewer rotatable bonds, and higher solubility.

How do hits from different fragment screening technologies and target classes compare with each other?
Do different target classes find different sets of hits? An analysis of substructures identified in hits against various target classes suggests the answer is yes. Certain substructures are preferred by kinases, for example, while other substructures are preferred by serine proteases. This suggests that building fragment libraries specific to a target class may be productive, though certainly not essential.

Regarding screening technologies, the researchers examined both biophysical (for example NMR, SPR, and DSF) as well as biochemical (such as fluorescence) assays. In general, the hit rates were similar for different technologies, with two exceptions. In SPR, a number of fragments nonspecifically interacted with the surface of the chip, giving a higher number of false positives. On the other hand, DSF gave an anomalously low hit rate, and on closer inspection the researchers found that about 1% of the fragment library appeared to denature proteins.

Interestingly, there was less overlap of hits between biophysical methods and biochemical methods than among biophysical methods or among biochemical methods. In other words, hits from an NMR (biophysical) screen were less likely to be found in a fluorescence (biochemical) screen than in an SPR (biophysical) screen. This is similar to the results of a previous study, though not stated explicitly there.

What is the best way to pair FBS assay technologies?
Given this finding, the researchers suggest that, to find the greatest number of hits, it is best to pair a biochemical method with a biophysical method. Of course, this assumes that the goal is to find as many hits as possible, but these may come at the expense of false positives. Still, if you’re going after a tough target, you want to find every possible hit you can. And if you are more interested in weeding out false positives than finding every viable hit, choosing fragments that hit in both a biochemical and a biophysical assay is probably a good starting point.

This is a fascinating paper and contains far more data than can be practically summarized here. It will be fun to see whether similar analyses, from different organizations, come to similar conclusions. 

07 January 2015

Spinach affects the Water

People often ask what a fragment is.  I like to paraphrase Justice Potter and say that it is like pornography; it is in the eye of the beholder.  I am not one for hard and fast rules as to what a fragment should be.  But, I also have a definite opinion what a fragment is NOT.  To me, what a fragment should be is easily described: relatively unadorned molecules.  I have a whole set of rules as to what the substituents should look like (coined the Zartler Optical Filter or ZOF by a cheeky comp chem friend).  In this paper, a group from Merck Serono decide to probe exactly what role the spinach on fragments play.  

Specifically, they deconstructed a TIE2 inhibitor (Figure 1) into its core hinge binding motif (Figure 2). 
Figure 1.  Crystal Structure of the Intact Inhibitor
This hinge binding motif has the advantage in that "decoration" can be introduced at the 4 or 8 position (Figure 2) as well as giving three donor/acceptor moieties. 
Figure 2. 4-Amino-8H-pyrido[2,3-d] pyrimidin-5-one (compound 1)
as core hinge binding motif.
They determined crystal structures for this molecule and four related fragments (Figure 3)
Figure 3.  Fragments for this study.
and then went to town on them with in silico methods to study the roles of water.  In one of those "gotta love it" moments, they classified the waters as "happy" or "unhappy", depending on whether they have positive or negative free energy, respectively.

So, what do we learn?  First, changes in the decoration leads to different binding modes.  In this case, they conclude that replacement of different water molecules leads to differences in binding modes.  Well, not surprising.  But, I think this is part of a trend, studying water and how fragments affect them, and vice versa.  In fact, the authors suggest using WaterMap could help to rationalize the roles of waters.  So, are we entering a brave new world of experimental verification of in silico predictions?

05 January 2015

Fragments in the clinic: 2015 edition

It’s been two years since Practical Fragments updated its list of fragment-derived compounds in the clinic, and since then there have been some nice developments. The table below starts from the previous list and also includes everything new we've managed to find. As before, this includes compounds whether or not they are still in development (indeed, some of the companies no longer even exist). Drugs reported as still active in clinicaltrials.gov, company websites, or other sources are in bold, and those that have been discussed on Practical Fragments are hyperlinked to the most relevant post.

Drug Company Target

Vemurafenib (PLX4032) Plexxikon B-Raf(V600E) inhibitor
Phase 3

ABT-199 Abbott Selective Bcl-2 inhibitor
LEE011 Novartis/Astex CDK4 inhibitor
MK-8931 Merck BACE1 inhibitor
Phase 2

AT13387 Astex HSP90 inhibitor
AT7519 Astex CDK1,2,4,5 inhibitor
AT9283  Astex Aurora, Janus kinase 2 inhibitor
AUY922 Vernalis/Novartis HSP90 inhibitor
AZD3293 AstraZeneca/Astex/Lilly BACE1 inhibitor
AZD5363 AstraZeneca/Astex/CR-UK AKT inhibitor
Indeglitazar Plexxikon pan-PPAR agonist
Linifanib (ABT-869) Abbott VEGF & PDGFR inhibitor
LY2886721 Lilly BACE1 inhibitor
LY517717 Lilly/Protherics FXa inhibitor
Navitoclax (ABT-263) Abbott Bcl-2/Bcl-xL inhibitor
PLX3397 Plexxikon FMS, KIT, and FLT-3-ITD inhibitor
Phase 1

ABT-518AbbottMMP-2 & 9 inhibitor
ABT-737AbbottBcl-2/Bcl-xL inhibitor
AT13148AstexAKT, p70S6K inhibitor
AZD3839AstraZenecaBACE1 inhibitor
AZD5099AstraZenecaBacterial topoisomerase II inhibitor
DG-051deCODELTA4H inhibitor
IC-776Lilly/ICOSLFA-1 inhibitor
JNJ-42756493J&J/AstexFGFr inhibitor
LP-261LocusTubulin binder
LY2811376LillyBACE1 inhibitor
PLX5568Plexxikonkinase inhibitor
(RG-7129)RocheBACE1 inhibitor
SGX-393SGXBcr-Abl inhibitor
SGX-523SGXMet inhibitor
SNS-314SunesisAurora inhibitor
UndisclosedVernalis/ServierBcl-2 inhibitor

The current list contains more than 30 clinical-stage drugs but is certainly incomplete, particularly in Phase I. If you know of any others (and can mention them) please leave a comment.

02 January 2015

Fragment events in 2015

Happy 2015! Lots of exciting events coming up this year - hope to see you at one!

Newly Added! The American Chemical Society is organizing a series of FREE Thursday webinars on Drug Design and Delivery. They all look fun; readers of this blog may be particularly interested in Designing Better Drug Candidates (January 29, by Paul Leeson), Fragment-Based Drug Design Strategies (March 19, by yours truly), PAINS (May 28, by Jonathan Baell), and X-ray Crystallography in Drug Discovery (July 30, by Jon Mason and Miles Congreve).

February 17-18: SELECTBIO is holding its Discovery Chemistry Congress in Berlin, Germany, with a number of talks on fragment-based lead discovery.

March 22-24: The Royal Society of Chemistry will be holding Fragments 2015 in Cambridge, UK, the fifth in the illustrious series organized by RSC-BMCS. You can read impressions of Fragments 2013 and Fragments 2009.

April 21-23: CHI’s Tenth Annual Fragment-Based Drug Discovery will be held in San Diego. You can read impressions of last year's meeting here and here, the 2013 meeting here and here, the 2012 meeting here, the 2011 meeting here, and 2010 here. This will be the ten-year anniversary, and it looks like a great lineup of speakers. Also, Teddy and I will be teaching our short course on FBDD over dinner on April 22.

June 9-12: NovAliX will hold its second conference on Biophysics in Drug Discovery in Strasbourg, France, and is currently accepting abstracts. Though not exclusively devoted to FBLD, there is lots of overlap; see herehere, and here for discussions of the 2013 event.

August 11-13: The OMICS Group is holding a conference entitled Drug Discovery & Designing in Frankfurt, Germany, with FBDD listed as a conference highlight. I confess I've never heard of this group, so if anyone has attended one of their events please leave a comment.

December 15-20: Finally, I'm helping to organize the first ever Pacifichem Symposium devoted to fragments in Honolulu, Hawaii. The Pacifichem conferences are held every 5 years and are designed to bring together scientists from Pacific Rim countries including Australia, Canada, China, Japan, Korea, New Zealand, and the US. There is lots of activity in these countries, and since travel to mainland US and Europe is onerous this should be a great opportunity to meet many new folks - in Hawaii no less! Abstract submissions are now open, and we're giving preference to people and organizations that have not presented before.

Know of anything else? Add it to the comments or let us know!

29 December 2014

Review of 2014 reviews

The year is spinning to an end, and as we did in 2013 and 2012, Practical Fragments is looking back on notable events as well as reviews we didn’t cover previously.

2014 was full of conferences, starting with the CHI meeting in San Diego (here and here), moving to the Zing conference in the Dominican Republic, on to the Fall ACS meeting in beautiful San Francisco, and ending with FBLD 2014 in Basel.

In terms of reviews relevant to the fragment community, John Christopher and colleagues at Heptares published an extensive analysis of “Structure-based and fragment-based GPCR drug discovery” in ChemMedChem early in 2014. The last few years have seen an efflorescence of new structural information on G protein-coupled receptors, and this paper provides a thorough compilation of crystal structures and small molecule ligands. The review also discusses methods that have been used to discover fragments that bind to GPCRs, including TINS, SPR, CEfrag, radioligand binding, and fluorescence assays, and ends with case studies on A2A antagonists and β1AR ligands.

In contrast to GPCRs, kinases represent a well-established target class for fragment-based drug discovery, as exemplified by the first approved drug, vemurafenib. Structural biology has played a major role in this success; more than 200 of the 518 human kinases have had their X-ray crystal structures determined, and more than 3000 protein kinase structures have been deposited in the protein data bank. Astex has put several kinase inhibitors into the clinic, and in Methods in Enzymology Paul Mortenson and colleagues from the company discuss the state of the art. This is a clear and concise review of fragment-based drug discovery in general and as specifically applied to kinases. It serves as an excellent introduction to the topic.

Any chemist who has worked on kinases will be familiar with azaindoles, and in Molecules, Sylvain Routier and colleagues at Université d’Orléans discuss “the azaindole framework in the design of kinase inhibitors.” This provides a thorough compilation of azaindole inhibitors against ALK, Aurora, Cdc7, CHK1, C-Met, DYRK1A, FAK, IKK2, JAK2, KIT/FMS, PAK1, p38α, PIM1, B-Raf, ROCK, m-TOR, and TrkA, replete with synthetic methods. The paper also includes a nice analysis of binding modes. Of the 58 crystal structures of azaindoles bound to kinases in the protein data bank, the majority (48) are with 7-azaindole rather than the three other positional isomers. This isomer (found in vemurafenib) is also over-represented in the patent literature and among commercial compounds.

Another target that has yielded to FBLD is BACE1, a hot but still controversial target for Alzheimer’s disease, and in Bioorg. Med. Chem. Lett. Daniel Oehlrich and colleagues at Janssen review “the evolution of amidine-based brain penetrant BACE1 inhibitors”. This is very much a medicinal chemist’s review, with over 100 chemical structures, including a nice summary of the various chemotypes used by different companies. The authors do an excellent job synthesizing a tremendous amount of data, much of it reported only in the patent literature, and engage in some intriguing chemical sleuthing to guess at the identity of clinical candidates whose structures have not been publicly disclosed, such as MK-8931.

Jia Zhou and collaborators at the University of Texas Galveston and Fuzhou University discuss “Evolutions in fragment-based drug design: the deconstruction-reconstruction approach” in Drug Discovery Today. After briefly describing fragment-finding methods and library design, the review focuses on deconstruction of known ligands to generate “privileged” fragments that are then reassembled into new molecules. Although this approach can be productive, if one doesn’t exclude PAINS the result can be garbage-in, garbage-out.

Finally, in Methods in Enzymology, Katherine Warner (National Heart, Lung and Blood Institute) and Adrian Ferré-D’Amaré (University of Cambridge) review the crystallographic analysis of fragments binding to the TPP riboswitch. This is a concise how-to guide, and the methodology could be applicable to other RNA targets.

And with that, Practical Fragments says farewell to 2014. Thanks for reading, and may the New Year bring wonderful new discoveries!

22 December 2014

Progress in Biophysics and Molecular Biology special issue

The latest issue of Prog. Biophys. Mol. Biol. includes five articles on fragment-related topics. We already discussed one from Astex; brief summaries of the rest follow.

Eddy Arnold (who has an editorial introducing the articles) and colleagues from Rutgers University discuss the advantages of screening fragments crystallographically. Regular readers of this blog will likely be familiar with some of the material, but there is lots of practical advice on fragment cocktail design (that is, choosing which fragments to mix together), optimization of soaking, high-throughput crystallography, and related topics. There is also a nice example of an “unknown known,” where the apparent activity of a compound turned out to be due to contaminating metal.

David Dias (University of Cambridge) and Alessio Ciulli (University of Dundee) have a piece on using NMR in structure-based lead discovery, with a heavy focus on large multi-protein complexes. They succinctly review both ligand-based and protein-based NMR methods and then discuss how these techniques can help determine ligand conformations and binding sites. Next, they discuss how to tackle high molecular weight protein assemblies or protein-protein complexes, often by using clever isotopic labeling strategies. The figures throughout are particularly effective at showing what kinds of information can be obtained from the various techniques.

Andrew Hopkins (University of Dundee) and colleagues are up next with “Fragment screening by SPR and advanced application to GPCRs”. Surface plasmon resonance, of course, is a mainstay of fragment screening, and this is a timely how-to guide by some of the experts in the field. As the title suggests, a major focus is on GPCRs, a class of membrane proteins only recently targeted by fragments. There are some good practical tips on protein immobilization, screening, and weeding out false positives. My sense is that screening GPCRs by SPR remains challenging; most of the fragment libraries screened tend to be small (no more than a few hundred compounds), and sensitivity seems to be an issue, with most of the hits being quite potent by the standards of FBLD (low micromolar or better).

Finally, Theresa Tiefenbrunn and C. David Stout (Scripps) lead us “Towards novel therapeutics for HIV through fragment-based screening and drug design.” Practical Fragments has highlighted fragment efforts against several targets for this virus, including HIV protease, HIV reverse transcriptase, HIV integrase, and TAR RNA; this paper discusses these and more. This is a thorough compilation of copious data and focuses heavily on fragment screening. Crystallography plays a starring role, but SPR and NMR are also prominent. In short, it shows practical applications of the prior papers, and so makes a nice conclusion to this series.

15 December 2014

Fragments vs CDC25B phosphatase – from behind

Protein phosphatases, which remove phosphate groups from proteins, fall into the category of low-hanging but firmly attached fruit: many make great targets, but getting lead-like inhibitors is tough. Indeed, the enzymes seem to be particularly susceptible to PAINS (see for example here and here). A major challenge is the phosphate-binding site, which has a predilection for highly negatively charged (and non-druglike) moieties. In a paper just published in ACS Chem. Biol., Tomasz Cierpicki and his group at the University of Michigan neatly sidestep this issue.

The researchers were interested in the dual-specificity protein phosphatase CDC25B, which is important in cell cycle regulation and thus a potential anti-cancer target. They started with a 1H–15N HSC NMR screen of 1500 fragments in pools of 20, with each fragment present at 0.25 mM. This yielded a single hit: 2-fluoro-4-hydroxybenzonitrile.

Because the researchers were using protein-observed NMR and had previously assigned the backbone resonances, they were able to use chemical shift perturbations to identify the binding site. Surprisingly, this turned out to be not the active site at all, but rather a region about 15 Å away. They were able to confirm this site using X-ray crystallography, which further revealed that the fragment binds in a small pocket near where the substrate protein CDK2 binds.

The researchers noticed a nearby sulfate ion (from the crystallization buffer) and, after first doing a brief SAR by catalog survey, they tried to link this to their hit. Although this certainly didn’t improve physicochemical properties, it did result in tighter binding, and crystallography confirmed that the new molecule bound as designed. This molecule also inhibited the phosphatase, albeit modestly (IC50 1-2 mM). The result suggests that blocking this protein-protein interaction is effective at blocking activity.

It remains to be seen how much affinity there is to be had at this site. Still, I do have a soft spot for phosphatase inhibitors that bind outside the active site. At the very least this paper provides a new direction for an old – and very difficult – class of targets.

10 December 2014

How much information can NMR provide?

A frequent assumption in fragment-based lead discovery is that similar fragments have similar binding modes, which are conserved as the fragments are elaborated. However, this isn’t always the case, a fact that can complicate optimization. Ideally multiple crystal structures help guide the chemistry, but in the real world crystal structures can be difficult to obtain.

One of the seminal papers in FBLD used NMR rather than crystallography to guide design, a strategy still used today. But how effective is NMR at assessing the binding modes of related fragments? This is the question that Isabelle Krimm and colleagues at the Université de Lyon sought to answer in a paper published a few months ago in PLOS ONE.

The researchers were interested in the inflammatory enzyme peroxiredoxin 5 (PRDX5), and they examined its interactions with five catechols: the parent unsubstituted molecule and four derivatives with substituents ranging from methyl to phenyl. Although catechols are PAINS, the researchers took pains to carefully examine the NMR spectra to look for signs of misbehavior.

Two NMR techniques were used, saturation transfer difference (STD) NMR and chemical shift perturbation (CSP). STD is nice because it is a ligand-detected method: you don’t need to go to all the work of assigning the chemical shifts of the protein. One piece of information from an STD experiment is whether a hydrogen atom is exposed to solvent or buried close to the protein, and in this case three of the catechols showed one particular hydrogen atom was exposed to solvent. The unsubstituted catechol provided only a single NMR peak and thus no information, and the fifth catechol was also not very informative, though it did seem to bind. Repeating this “epitope mapping” of all the catechols with human serum albumin instead of PRDX5 gave different results, suggesting a different binding mode.

Of course, there is only so much information you can get from ligand-detected NMR, so the researchers turned to protein-detected NMR and examined the CSPs of proton-nitrogen cross peaks using 15N-HSQC experiments. They also calculated CSPs for various potential binding modes and compared these with the experimentally observed CSPs to generate models. These suggested a common binding mode for the same three catechols that STD revealed as having a single solvent-exposed hydrogen atom each. Combining all this information led to specific binding models for these three fragments.

But how good are the models? Happily, the researchers were able to obtain crystal structures of four of the catechols bound to PRDX5, and these agree quite well with the NMR-derived structures. Unfortunately, the fifth catechol couldn’t be characterized bound to the protein crystallographically; NMR also suggested that this bound differently than the others.

So in the end, NMR was able to successfully predict that three ligands had similar binding modes, while another likely doesn’t. The process does seem to require a fair bit of effort. Nonetheless, in cases where crystallography is difficult or impossible, it may be the best way to get essential structural information, and this paper provides a good road map.

08 December 2014

PAINS Shaming, part deux

So, as regular readers know, we have declared war on PAINS on the blog.  As part of that effort, I (we?, not sure if Dan wants to be associated directly with it) introduced PAINS Shaming. Well, thanks to Angelo Pugliese and Duncan McArthur at the Beatson we have the latest paper to shame. 
The nice thing is that they come right out and call it like it is: a Rhodanine.  To reiterate, from the comment by Baell and Walters:
Rhodanines exemplify the extent of the problem. A literature search reveals 2,132 rhodanines reported as having biological activity in 410 papers, from some 290 organizations of which only 24 are commercial companies. The academic publications generally paint rhodanines as promising for therapeutic development. In a rare example of good practice, one of these publications (by the drug company Bristol-Myers Squibb) warns researchers that these types of compound undergo light-induced reactions that irreversibly modify proteins. It is hard to imagine how such a mechanism could be optimized to produce a drug or tool. Yet this paper is almost never cited by publications that assume that rhodanines are behaving in a drug-like manner.
And as predicted, this paper does not cite Voss et al.  They cite dose-depedent responses for their compounds.  Does it matter?  Not to me.  To their credit, they call these molecules tools, but also tout them for future therapeutic development.  A PAIN can be a useful tool or even lead to non-PAIN containing compounds, but it requires a higher level of proof.  I don't see that here. 

So, here is your PAINS Shaming (Holiday themed): 

03 December 2014

Huge Library + Tiny Hit Rate = Novel Chemotype

As Dan recently pointed out that I pointed out, epigenetics is big.  Bromodomains get a lot of play on this blog.  One bromodomain that is not mentioned a lot in the literature is ATAD2 (because everyone is actually working on it?).  It is promising because of the diverse cellular activities it is involved in.  However, its bromodomain is quite dissimilar from to "druggable" bromodomains.  [Just an aside, can't we get away from druggable already?] Only 3 of seven residues lining the KAc pocket that interact with peptide are similar (compared to Brd4) (Figure 1)
Figure 1.  View of residues within the KAc binding site of BRD4 that interact with diacetylated residues.  Residues from the peptide are shown in teal.
So, in this paper from the Fesik lab at Vanderbilt, the use fragments to discover chemical matter against this tough target.  They utilized 15N-HSQC, like the previous post on bromodomains, because it can detect millimolar binders and (with resonance assignments) determine where on the protein it is binding.  They screened 13800 fragments (NOT a typo!) as mixtures of 12, or 1150 individual experiments.  Using the SO-FAST pulse sequence allows each experiment to be acquired in 7 minutes (6 days of acquisition).  This required more than 2 grams of labeled material.  Hits were then deconvoluted as singletons, resulting in 65 actives with Kds from 350uM to more than 2 mM (determined by HSQC titration).  12 had affinities of less than 1 mM.  This hit rate of 0.1% is low, especially for a fragment based screen, even against a PPI.  While it may ligandable, a hit rate this low still indicates this will be a very tough nut to crack. 

The assignments of ATAD2 are NOT known, but they observed a consistent cluster of resonances being perturbed (Figure 2).
Figure 2.  A. Fragment 1, B, Fragment 5, C Fragment 12.  Green Circles represent resonances which may report on ligand binding.
They discovered several novel chemotypes, never seen against bromodomains, albeit with a very low hit rate, that could be put in three clusters (Figure 3).  Cluster 1 represents known bromodomain inhibitors, while cluster 2 and cluster 3 are unique to ATAD2.  Interestingly, the Kds only differ by 2-fold, but are still more potent than other recently published ATAD2 compounds.
Figure 3.
One representative from each cluster was crystallized (1, 5, and 12).  All three fragments occupy the same pocket and make a critical contact to the conserved N1064.  They also compare their fragments to work from the SGC that scooped them. 
Figure 4. A. Fragment 1, B, Fragment 5, C Fragment 12.
In the end, this is an unsatisfying paper.  There is speculation as to how these fragments can be progressed and made more potent.  But, this entire paper is about the novel chemotypes for ATAD2.  There is no chemistry in a journal that has Chemistry in its title.  I expect more from this journal and this group.  To summarize, if you throw enough fragments at a target you can find a few that bind. 

01 December 2014

Fragments finger a PHD finger

As Teddy recently observed, epigenetics is big, and fragments have played an important role against several targets. One class of proteins that has received less attention is the group of PHD fingers, which recognize methylated lysine residues. The pygo-BCL9 complex contains a PHD finger that binds to a specific methylated lysine residue on histones, and has been implicated in cancer. Marc Fiedler, Mariann Bienz and colleagues at the MRC Laboratory in the UK describe their efforts against this target in a new paper in ACS Chem. Biol.

The researchers started with a virtual screen of 225,000 commercially available compounds. They purchased 313 of the top hits and tested them for binding with protein-detected NMR (1H-15N-HSQC). This produced only three very weak hits – a hit rate of 0.001%. Three additional virtual screens produced a couple dozen more, but all of these were weak; the best had an affinity around 3.5 mM and a ligand efficiency around 0.12 kcal/mol/atom. Co-crystallography proved unsuccessful, probably in part due to the low solubility of the compounds.

Enter fragments. The researchers screened the Maybridgerule of three” 1000-compound library in pools of 5 compounds, each at 1 mM, under the same protein-detected NMR conditions they used previously. Numerous pools appeared to show binding but deconvolution proved unsuccessful for all but two. Strikingly, the two hits – both benzothiazoles – are almost identical, differing only in a single atom substituent (fluorine vs chlorine).

Although the best fragment hit was also weak (Kd = 3.1 mM), it had a much higher ligand efficiency (0.31 kcal/mol/atom). More importantly, it was sufficiently soluble (20 mM!) that it could be cocrystallized with the protein, resulting in a high resolution structure. This revealed that the fragment binds in a narrow cleft – a conclusion independently reached by examining the NMR chemical shift perturbations (CSPs) of protein amino acid residues in the presence of compound.

Testing various analogs did not identify anything significantly more potent, but changing the benzothiazole core to a benzimidazole changed the pattern of CSPs. Additional NMR studies and modeling suggested that these molecules bind not in the narrow cleft but rather in the pocket where methylated lysine binds, and competition studies with a short peptide supported this hypothesis.

This is a nice example of applying fragments against an important emerging target class. It is also a beautiful illustration of molecular complexity in action: as the authors note, the hit rate from fragment screening was around 200-fold higher than the virtual screen, and provided better hits to boot. As with most fragment screens there is still a long way to go to get to a potent compound, but it looks like this group is on the right path.

25 November 2014

Docking covalent fragments

Most drugs interact non-covalently with their target. The conventional wisdom was that covalent drugs – especially irreversible ones – would have dangerous side effects. Although this is still a concern, the success of drugs such as ibrutinib and dimethyl fumarate has caused a resurgence of interest. In a new paper in Nature Chemical Biology, Brian Shoichet, Jack Taunton, and colleagues at the University of California San Francisco describe how computational chemistry can be used to find new covalent inhibitors.

The researchers created a modified version of the program DOCK called – wait for it – DOCKovalent. Happily, they have made this available for free to anyone. To start, you upload your crystal structure and choose which amino acid residue you are interested in targeting. You can then pick from 9 different libraries of various electrophiles, each covering a different class of covalent “warhead”: epoxides, aldehydes, etc. There are about 650,000 molecules in total, roughly half of which easily qualify as fragments, with the rest being lead-like (still < 350 Da). Each molecule is either commercially available or readily synthesized in one or two steps.

The program then virtually links each molecule with the selected protein residue (typically cysteine or serine) and calculates scores based on predicted van der Waals and electrostatic interactions as well as desolvation. Multiple conformations of each ligand are sampled (with fragments there are not that many) as are different rotamers of the nucleophile. Users then manually inspect and test the top hits.

The researchers first benchmarked the program against four proteins with known covalent inhibitors, where it performed well. In the case of the bacterial protein AmpC β-lactamase (which we previously discussed here), the program retrospectively predicted the correct structure of 15 out of 23 known boronic acid ligands. In one case where the prediction differed from the reported co-crystal structure, the researchers re-determined the co-crystal structure at high resolution and found that DOCKovalent was actually correct.

Thus confident, the researchers docked 23,000 commercial boronic acids against AmpC and selected 6 on the basis of score and structural novelty. Of these, 5 had inhibition constants of 3.55 µM or better, with the best being 40 nM. A crystal structure of this compound bound to the protein led them to purchase 7 additional compounds, one of which had Ki = 10 nM and a ligand efficiency of 0.73 kcal/mol/atom. Most of the molecules were also selective against 4 other proteases and were able to reverse antibiotic resistance in AmpC-expressing bacteria.

Of course, by design all of these molecules have a boronic acid warhead; will any such molecule inhibit this enzyme? To find out, the researchers tested 5 low-scoring molecules and found that 4 of them showed, as hoped, less than 10% inhibition at 10 µM. However, a fifth molecule showed reasonable inhibition, with Ki = 3.2 µM. To understand this false-negative, the team solved the crystal structure of the molecule bound to AmpC. Interestingly, the molecule bound in a conformation different than had been predicted – one that also required conformational changes in the protein, which are not allowed in DOCKovalent.

The researchers took a similar approach to seek novel inhibitors of the kinases RSK2 and MSK1 using reversible cyanoacrylamide-containing molecules (previously highlighted here). Here too the researchers were able to identify selective nanomolar cell-active inhibitors.

This looks like a very nice approach. Of course, it does require a crystal structure (or at least a good model). Also, as mentioned above, the fact that the protein is kept rigid means the program will be unable to detect ligands that bind to cryptic pockets, so there is still plenty of opportunity for empirical surprises. Still, the fact that DOCKovalent is freely available will hopefully encourage people to give it a try on their favorite protein.

17 November 2014

Deconstruction, superadditivity, and selectivity

One of the more exciting phenomena in fragment-based approaches is synergy (or superadditivity), in which the binding energy of linked fragments is greater than the sum of the binding energies of the individual fragments. Extreme cases are relatively rare, and the underlying thermodynamics can be counterintuitive, so it is always fun to see new examples. Cosimo Altomare and collaborators at the University of Bari and Consiglio Nazionale delle Ricerche (Italy) describe one in a recent paper in J. Med. Chem.

The proteases factor Xa (fXa) and thrombin (fIIa) are two heavily-studied anticoagulant targets. The paper characterizes a previously described molecule (compound 3) that is selective for fXa but still potent against fIIa, leading to good anticoagulant activity in human plasma as well as profibrinolytic activity. The researchers took a fragment deconstruction approach to better understand the binding to both targets.

As seen previously for fXa, the chlorothiophene moiety (red) is essential for binding, and removing it (compound 14) obliterates any detectable activity on both enzymes. However, while removing the glucose moiety (green) to give compound 1 reduced affinity for fXa by less than ten-fold, it reduced affinity for fIIa by more than two orders of magnitude. In contrast, removing the piperidine moiety (blue) to give compound 6a reduced affinity to both enzymes by several orders of magnitude.

However, these results are context-dependent. Removing both the piperidine moiety and the glucose moiety gives compound 4a, which has similar activity against fIIa as compounds 1 and 6a, where only a single moiety has been removed. In fact, compound 4a (without the glucose) is actually slightly more potent than compound 6a (with the glucose) against fIIa. But, as mentioned above, adding the glucose to compound 1 gives an impressive 110-fold boost in affinity for fIIa. In comparison, a famous early example of cooperativity in an NMR by SAR study gave only a 14-fold boost.

The researchers solved the crystal structure of compound 3 bound to fIIa, which reveals several hydrogen bond interactions between the glucose moiety and amino acid residues that have been previously implicated in allosteric activation of the protein. Perhaps compound 3 is exploiting this allosteric mechanism to bind more tightly.

This is a careful, thorough study and serves as a useful reminder that cooperativity can be huge, but it is still difficult to explain, much less predict.

12 November 2014

Pleasant Surprise

Epigenetics is bigWicked big.  How big?  This big.  Papers come from everywhere.  In this paper, an academic group from Minnesota, goes after SIRT2 with fragments.  SIRT2 is a type III HDAC that resides primarily in the cytoplasm that uses NAD+ as a co-factor (Figure 1).
Figure 1.  Biochemical Reaction of SIRT2

Sirtuins (there are seven) have a long history aready in pharma.  SIRT2 has been fingered as a potential treatment for Parkinson's Disease (PD) and other pathologies, including bacterial infection.  There are a nice range of available inhibitors for SIRT2.
Figure 2.  Known Sirtuin2 Inhibitors
Suramin, a drug originally made in 1916.  I think it was made by pouring hot sulfuric acid over naptha tar (but my chemistry may be off).  Of course, when I saw this I got my dander up and got ready both barrels.  [It also made me chuckle, because many moons ago I co-authored a paper on suramin against RANK-RANKL.  In that paper suramin blocked a PPI.]  In this paper suramin is highly selective for SIRT1 over SIRT2 and 3.  So, as my wife says, your mind is like a parachute, it only works when open.  So, let see what they did.

One of the known inhibitors is

First, they evaluated a SIRT5-suramin crystal structure, where suramin mainly occupies the peptide binding site and a sulfonate protrudes into the nicontinamide binding site.  With this, they came up with the following generic plan (Figure 3). In this case, the circled napthalene is close to the  nicotinamide binding site.  They proposed to merge/link nicotinamide compounds to the appropriate suramin-like moiety. 
Figure 3.  Merging Strategy for SIRT2 Inhibitors
So, my quibble, and its not a big one, but their molecules are big (20 heavy atoms or more).  Oh well, a fragment is in the eye of the beholder.  Dan would call this FADD maybe.  Well, how did they do, you ask?  Well, they were able to generate sub-micromolar compounds (64 being the best) (50 nM![edited]), with selectivity against SIRT1 and 3.  The MOA was competitive vs. substrate and noncompetitive vs. NAD+ (although they could not rule out uncompetitive).  It had low cytotoxicity.  YAY.  Yet, it only had moderate anti-cancer activtity.  Well, those two outcomes could still allow it to be a good PD compound.  But their data indicated that it would have a low probability for crossing the BBB. 
So, in the end, I was pleasantly surprised.  This ended up being nice work with a good breadth of work.  I don't know if this makes it into the "lead-like" space or will remain in the "tool" space, but I like to see this kind of work, especially from academic groups.