Crystallographic screening of soluble epoxide hydrolase

Last year we highlighted a paper from Yasushi Amano and colleagues at Astellas in which they performed fragment-screening on soluble epoxide hydrolase (sEH), a potential target for inflammation and hypertension. A new paper from the same group in Bioorg. Med. Chem. builds on that work and provides some interesting comparisons.

In the first paper, the researchers performed an enzymatic screen with fragments at high concentrations, resulting in a hit rate of around 7.3%, of which 126 of the 307 hits resulted in crystal structures. However, despite this bounty of hits, only 2 new scaffolds were found that bind to the catalytic triad of the enzyme.

Given the success rate with crystallography, the new paper focused on crystallographic screening as the primary fragment-finding method. The researchers chose 800 fragments from their in-house collection with molecular weights between 151-250 Da. To identify new scaffolds, fragments containing amide or urea moieties – known catalytic-site binders – were excluded. The fragments were then pooled into cocktails of 10 and soaked into crystals of sEH, with each fragment at a final concentration of 1 mM. X-ray diffraction data of the soaked crystals resulted in 8 hits. To ensure that nothing was missed, cocktails of the remaining 9 fragments from pools with a hit were retested, but nothing new came up. Although the researchers do not comment on the lower hit rate compared with the original screen, this could be because they were looking specifically for new scaffolds.

Despite the 1% hit rate, the fragments identified were quite interesting, with IC₅₀ values ranging from 52 to 2200 µM. Most of the fragments formed hydrogen bonds to the catalytic triad, but the details differed from reported inhibitors. For example, several fragments contained secondary amines. Fragment 1 (cyan) in particular was well-positioned to reach into two sub-pockets on either side of the catalytic center, so 14 analogs were chosen for screening, resulting in molecules with significantly increased activity, such as compound 9 (magenta).

The crystal structure of compound 9 bound to sEH reveals that it binds in a similar manner as fragment 1. However, the added hydroxyl group is able to make new interactions that were unavailable to fragment 1, and the larger adamantyl group of compound 9 is able to make more hydrophobic interactions than the smaller phenyl ring.

This is a lovely illustration of the gains in both affinity and ligand efficiency that can be had by scaffold-hopping. It is also a nice example of using fragments to explore new chemical space. Finally, it is laudable that all the structural information is deposited in the protein data bank.

One Fragment to Rule them All

Recently, I have been riffing on the ontology of FBDD.  FBDD has become so popular that we are now seeing appropriation of the term in many papers that don't really mean it.  So, I came across this paper.  Now, don't be fooled by the title, this is about fragments, the abstract promises me so.  Let me skip the science, which to my eyes is actually quite boring, and get right to the heart of their fragment case.  

How is this paper fragments you ask?  Well, this is not about scaffold hopping or innovative uses of fragments to develop SAR.  This is not about interesting approaches to screening.  It is most certainly not about in silico approaches.  This is most certainly about fragment library design.  We often discuss here the sizes of fragment libraries and what they should look like.  One important concept we often tackle here is how big should the libraries be and what size should fragments be.  More importantly we often discuss how much of chemical space a fragment library should cover.  This paper takes an anti-Reymond approach to address that question. 

The Reymond approach tries to determine how big chemical space is, what it looks like, and what portion of it is available.  The Anti-Reymond approach identifies what is available and validates its inclusion in a fragment library.  Here is the last sentence of this paper:

"These findings...verify the value of the benzamide fragment in drug design."

Now, I was worried that benzamidine was not a valuable fragment.  This paper has removed all doubt in my mind.  Now that is settled, we can go on an validate the other 165, 999, 999,999 other possible fragments. 

Fragments vs P2X1

Four years ago we highlighted a paper in which researchers performed a fragment screen against ion channels. There have been other occasional reports, but for the most part this has been a quiet area. A new open-access paper in Neuropharmacology by Andrew Thompson and collaborators at Cambridge University, University of Bern, VU University Amsterdam, and Washington State University provides another case study.

The researchers were interested in the P2X1 purinergic receptor, which allows calcium ions to pass into cells when ATP binds. An antagonist could be a safe anti-clotting agent as well as a potential male contraceptive. However, the only reported inhibitors are freakish molecules like suramin.

The paper is heavily focused on assay development and validation, in this case using cells stably transfected with P2X1. These were loaded with a voltage-sensitive fluorescent dye: when the channel opens, fluorescence increases. (Control cells not expressing P2X1 do not behave this way.) By adding potential ligands first and then adding ATP, both agonists and antagonists could be identified.

The researchers screened 1443 fragments (from IOTA) at 300 µM each. Cell-based fragment screens are rare but not unprecedented. In this case, 46 hits were obtained, and these were retested at multiple concentrations; 39 hits showed dose responses. These were both agonists and antagonists, with EC₅₀ values ranging from low micromolar to above 1 millimolar.

For confirmation, the researchers used a fluorescently labeled analog of ATP that binds to the P2X1 on transfected cells but not to cells that don’t express P2X1; the increased fluorescence of the cells could be visualized using confocal microscopy. Most of the fragment hits reduced the fluorescent signal, suggesting that they block ATP binding.

A structural analysis suggested that the hits are quite diverse, though annoyingly only a single fragment structure is provided. Still, these do look like useful assays, and the paper provides another successful example of fragment screening in a complicated cellular system.

Fragments vs HIV Reverse Transcriptase - again

Some targets are so heavily studied that you would think there is nothing left to discover. HIV-1 Reverse Transcriptase (HIV-1 RT) is one of these, with 13 marketed drugs against it: half of all anti-HIV drugs. But as Gilda Tachedjian and collaborators at Burnet Institute, Monash University, the University of Pittsburgh, and the University of Melbourne show in a recent (and open-access) paper in Proc. Nat. Acad. USA, there are still new insights to be learned about this target.

The researchers started with an STD NMR screen of 630 Maybridge fragments, each at ~350 µM in pools of up to five. This gave 84 hits – a healthy 13% hit rate. However, when these were tested in a functional assay (RNA-dependent DNA polymerase activity, or RDDP) only 12 showed significant inhibition, of which 6 were better than 1 mM. Testing 14 related compounds led to 2 more hits, for a total of 8 fragments with IC₅₀s from ~70-750 µM. However, one showed signs of aggregation in dynamic light scattering and was not further pursued.

Since HIV-1 RT has been the object of such intensive research, the team looked at the similarity of their fragments to known binders, including those from previous fragment screening. Surprisingly, their hits turned out to be quite distinct.

Next, the researchers looked at the effect of their fragments on the DNA-dependent DNA polymerase activity of HIV-1 RT, and happily found results similar to the RDDP assay above. The 5 most potent fragments were also tested against three clinically important mutants of HIV-1 RT, and while two of them showed reduced activity, the other three were either as potent or even more so. Testing these against unrelated polymerases revealed that they are not merely promiscuous inhibitors.

Of course, functional activity at high concentrations can have all sorts of causes, so the researchers performed a battery of careful enzyme kinetics experiments to ascertain the mechanisms. One fragment turned out to be competitive with respect to deoxynucleotide triphosphate substrate, even though it looks nothing like a nucleotide. Another is competitive with the DNA substrate. In other words, both these fragments operate through different mechanisms of action from clinically approved HIV-1 RT inhibitors.

One of the most potent fragments is a p-hydroxyaniline, which the researchers recognized as a PAINS compound (it can form reactive quinones). However, freshly prepared samples of this fragment were just as active as samples that had been stored in DMSO for months. Also, an analog without the ability to form a quinone was still active, albeit less so.

The p-hydroxyaniline fragment also showed activity in a cell-based assay. Just as with biochemical assays, cell-based assays are also susceptible to false positives, but the kinetics of viral inhibition were consistent with inhibition of HIV-1 RT rather than other other mechanisms. Further work on the compound may be merited; these are exactly the kinds of investigations necessary to decide if an interesting PAINS molecule is worth pursuing.

Unfortunately there is no crystallographic or detailed NMR structural information as to how these molecules actually bind. Previous work has identified multiple fragment binding sites on HIV-1 RT, so further work should eventually reveal how these molecules interact with the protein.

In the end this paper shows that, even in the absence of structure, it is possible to learn a great deal about how fragments inhibit an enzyme. It is also a useful reminder that fragment-based approaches can identify new types of inhibitors even for a target that has been intensively – and successfully – studied for decades.

Natural Product Derived Fragments against MMP-13

I have been lucky to work on a lot of systems that very much interest me.  I, in particular, love metallo-proteins.  I worked on rubredoxin as a post-doc and when I moved into industry I worked on a slew of metalloproteins.  So, I love it now when I see papers on targets I used to work on.  This paper does exactly that while also letting me riff (later) on Natural-Product-Derived Fragments (NPDF). 

NPDF has a long history in FBDD having been discussed here, here, here, and so on.  Many vendors and some companies have NPDF libraries (whether they call them that or not).  However, these libraries have yet to be proven to be an efficient route for "discovering clinical drug candidates".  Lanz and Riedl set out to do this against MMP-13 (how many of your just said, yeah I worked on that target?).  All MMP-13 clinical candidates with strong ZBG (Zinc-binding groups) have failed.  They are aiming to develop a MMP-13 without a strong ZBG.  Of course, we have seen a LOT of work towards this goal: here, here, and here for example.  The authors propose that the use of NPDF prevents the problem of using fragments with "debatable biological properties".  This seems to the be the argument used by the NPDF people, since these fragments are found in nature they have desirable properties.  I have never bought this line of reasoning for a variety of reasons.  

To their end, the authors selected uracil as their starting NPDF for these reasons: good synthetic starting points, cis amide bonds, and its found in a variety of natural products (nucleic acids).  They docked it in the S1' non-zinc binding site and found a strongly conserved binding site. [For me, and I would imagine a whole lot of people, this fits in the "things you already knew" category.]  The uracil interacted with the NH an CO of Met232 via its cis amide bonds and "addresses" Lys228.  Several compounds were made from the uracil starting point (Figure 1):

Figure 1.  2: 5 uM vs. MMP-13, < 50% Inhib against 1,2,3,7,8,9,12, and 14 at 20 uM. 3: 10 nM vs. MMP-13, < 50% Inhib against 1,2,3,7,8,9,12, and 14 at 20 uM2: 5 nM vs. MMP-13, < 50% Inhib against 1,2,3,7,8,9,12, and 14 at 10 uM

So, in the end, they have created a potent and selective compound.  They did use a NPDF as a starting point.  Making these compounds is not something that bowls me over either for a Technical Difficulty score or Artistic Merit.   However, I would not go so far as to say that they have validated the NPDF approach.  I think to show that a generic approach works you need more than one (relatively well known) target with more than one (relatively well known) fragment. 

Benchmarking native mass spectrometry

Mass spectrometry (MS) is one of the less common tools to find fragments. In the conceptually simplest approach (native mass spectrometry), you incubate your protein with a putative ligand and ionize the mixture. Fragment binding is detected by an increased mass for the complex, and the strength of binding by the ratio of heavier bound complex peak to protein peak. However, the liquid to gas phase transition is a big step, and often the complex does not survive. Aside from more specialized applications of MS (such as here, here, and here) there aren’t many published examples. A recent paper from Federico Sirtori and colleagues at Nerviano and Università degli Studi di Milano in Eur. J. Pharm. Sci. describes fragment screening by native MS in detail.

The researchers used the reliable model protein Hsp90, which was also used in a previous MS study and in benchmarking other techniques. One of the many benefits of Hsp90 is a wealth of well-characterized inhibitors with a range of affinities, and these were used to calibrate the technique. This turned out to be critical: beyond sample preparation itself (beware non-volatile buffer components), all kinds of parameters can be adjusted including various voltages, temperatures, vacuum strength, and ion source. Get one of these wrong and your non-covalent complex either fails to ionize or blows apart.

In addition to using published data on known compounds, the researchers ran both fluorescence polarization (FP) and surface plasmon resonance (SPR) assays to independently determine dissociation constants. Initially the results from MS (a Q-TOF) were quite different, but after optimization the team was ultimately able to find conditions that gave qualitatively as well as quantitatively similar results for ligands with affinities ranging from picomolar to ~100 micromolar.

Thus encouraged, the team embarked on a fragment screening campaign. The Nerviano fragment library consists of 1914 molecules mostly following the rule of 3, though halogenated fragments up to 380 Da are allowed as are compounds with up to 6 hydrogen bond acceptors. The fragments were run in mixtures of 5, with protein at 2.5 µM and each compound at the low concentration of 10 µM. Sample injection and data processing were automated, and the entire screen took 2 days and 2 mg of protein.

Given the low concentration of fragments, the researchers lowered the bar for potential hits, yielding 282 compounds. These were retested individually, yielding 146 confirmed hits that gave signals of 5.2-29.7% bound protein. This is a high hit-rate, particularly given that these binding levels suggest affinities in the 20-179 µM range. Indeed, only 5 fragments could be competed by a high-affinity binder, suggesting either that the others bind outside the active site or are non-specific (false positives). Regarding false negatives, Nerviano reported the results of an NMR fragment screen against Hsp90 last year, and 12 of 14 hits identified there could also be detected by MS. The other two were likely below the detection limit of the MS assay.

Unfortunately, the researchers do not discuss thermodynamics. In theory enthalpic interactions dominate over entropic interactions in the gas phase, but it is unclear whether any of the observed binders were strongly entropy-driven.

In the end, it appears that fragment screening by native MS is workable, but the sensitivity is probably lower than other techniques. Of course, increasing the ligand concentration would increase the sensitivity to weaker binders, but at the cost of more non-specific binding – which is already considerable. Also, Hsp90 is about the friendliest protein one can imagine. I would be reluctant to try this with a more challenging target that lacks good tool ligands. But if you want to give it a go, this paper provides a wealth of information for getting started. And if you have experience with native MS, please share it in the comments.

Fragment Ontology

We here at Practical Fragments look for papers in the literature about fragments.  Typically, it is a Web of Science search, or I see something come in an alert that has "fragment" in the title.  Well, not everything with fragment in the title is not really about fragments as we typically think of them. So, I recently came across this paper titled : "Genetically Encoded Fragment-Based Discovery of Glycopeptide Ligands for Carbohydrate-Binding Proteins".  I decided to give the paper a good perusal, largely because one of the authors is from where I did my post-doc.

The authors are interested in making competitive inhibitors of carbohydrate recognition domains for the treatment of a variety of diseases.  The challenge with lectin inhibitors is that the native carbohydrate has relatively low affinity and are synthetically complex.  As you would think, you can use the carbohydrate for binding specificity and then add something more "drug-like" to increase affinity through other interactions.  This approach has been successful but require complex multistep syntheses.  In this paper, they decided to search for peptides which can synergize with carbohydrates rather than serving solely as a linker or standalone recognition element.  To do this, and increase throughput they used a genetically encoded library, phage display.  In short, they created a glycopeptide library of 10^8  molecules through derivatization of a peptide library with carbohydrate.  This approach allows the addition of different carbohydrates (targeting different lectins) with the same peptide library.  

Figure 1.  Library Screening Approach for Genetically Encoded Glycopeptide Libraries.

In this approach, the first library (Man-X7) is screened against the target and anti-target.  The second library (methyl-X7) and the third library (Ser-X7) are screened only against the target.  After the first round of panning, they identified a weak consensus of Man-[WYF]Y[SDEA].  These peptides were made and able to compete with ConA for ligand in SPR, the mannose was shown to be essential to activity, the specific peptide sequence was required for synergistic binding.  Further work showed that the final four residues of the peptide contributed minimally to binding, so they lopped them off.  

They then performed two more rounds of panning with Man-WY[D/E]-X7.  All of the hits from these rounds had single digit micromolar affinity and the glycan-proximal ligands are responsible for most of the affinity.  How did they know if this is actuallly binding to where they want it to?

Figure 2.  Man-WYD co-crystalllized with ConA. 

Figure 2. shows the crystal structure of Man-WYD.  The mannose moiety binds where it is expected.  However, the peptide is not binding in the remainder of the trisachharide binding site, but instead in a somewhat deeper cavity near Y12.  Additionally, a latent hydrophobic site is opened up through induced fit (asterisk), filled by the Y residue of the glycopeptide.  

This approach led to the discovery of a novel class of compounds which would not have been discoverable by "standard" approaches.  But, is this fragments?  In my eyes, fragments takes simple compounds and screen them against the target.  It then optimizes the actives as quickly as possible and does iterations.  A key component to FBDD is SBDD and identification of how the actives/hits bind.  To me, this approach adheres to all the tenets of FBDD.  We have seen super huge screening molecules before, so that should not be an issue. As I have said, FBDD is about small little things being screened effectively.  I think this paper shows it is more about how you think about your system. 

Fragments vs MCL-1 revisited: on to low nanomolar potency

The protein MCL-1 binds to other proteins to protect cancer cells from apoptosis. Protein-protein interactions have historically been considered difficult, but as we’ve noted previously (here, here, here, and here, for example) fragments have been successfully deployed against this target. A recent paper in J. Med. Chem. provides the latest update from Stephen Fesik and co-workers at Vanderbilt University.

We last highlighted this program in early 2013, when the Fesik lab disclosed a series of mid-nanomolar inhibitors, such as compound 1, derived from fragment merging. In the new paper, they report compound 2 as another fragment identified in the original NMR screen.

NMR-based structural information of this molecule bound to ¹⁵N, ¹³C double labeled MCL-1 revealed a similar binding mode as the previous series, and merging the molecules led to the low nanomolar compound 34, with impressive ligand efficiency. This compound was also >1700-fold selective for MCL-1 over the related protein BCL-x_L and >250-fold selective over BCL-2.

Although compound 34 did show activity in cell lysates, the authors note that it is unlikely to be potent enough to show unambiguous activity in cellular assays. Indeed, researchers at AbbVie and Genentech have recently reported MCL-1 inhibitors that show picomolar activity in biochemical assays but only high nanomolar to low micromolar activity in cells.

Still, this is another nice illustration of the power of fragments – combined with a healthy dose of medicinal chemistry – to tackle a difficult target. Notably, the researchers didn’t have to turn to super-sized fragments. Moreover, the best molecule shown is well within Lipinski space, and there are plenty of avenues for further optimization. It will be fun to watch this story progress.