22 August 2016

Crystallographic screening of a nuclear receptor

Crystallography as a primary screen seems to be gaining traction. As the old cliché goes, a picture is worth a thousand words. And as Andrey Grishin recently commented on an earlier post, the increasing speed and capacity at synchrotrons lowers the barrier for data collection. A new paper in ChemMedChem by Yafeng Xue and colleagues at AstraZeneca provides yet more support for starting with crystallography.

The researchers were interested in the retinoic-acid related orphan receptor γt (RORγt), a potential target for autoimmune diseases. The protein is a nuclear hormone receptor, and like many members of this family, ligands tend to be lipophilic with poor physical properties. Also, work by other companies around this target had created a thicket of intellectual property claims. To find new and attractive chemical matter, the researchers turned to fragments.

The ligand binding domain of RORγt was crystallized and soaked against a library of 384 fragments chosen on the basis of maximum diversity and previous success in crystallography. Fragments were screened at 75 mM concentration in pools of four, with members chosen to have different shapes. This process did require “extensive optimization”, and even then about 15% of the datasets were not usable. But the effort paid off, resulting in 21 hits from 18 pools. Hits were then tested by SPR, revealing that the best had an affinity of just 0.2 mM (though with an impressive LE of 0.42 kcal mol-1 per heavy atom), while some were > 5 mM.

As expected, many of the fragments bound in the large and lipophilic ligand binding pocket, accessing various binding modes previously seen with other ligands. This is a nice confirmation that fragments are able to sample chemical space very efficiently, as shown five years ago for HSP90. Indeed, for one particularly productive pool, three of the fragments bound simultaneously at different subsites within the ligand binding pocket!

Of course, proteins are often highly dynamic in solution, and one concern with crystallographic screening is that the protein crystals may not allow much movement. In this case the researchers did observe several cases of induced fit, with one side chain residue shifting more than 3 Å to accommodate a fragment. This revealed a type of interaction that was not predicted using a computational approach: a victory – for now – for the power of empiricism.

As discussed earlier this year, secondary ligand binding sites appear to be common, and indeed five fragments bound outside the ligand binding pocket. Three of these bind at what seems to be a protein-protein interface for other receptors, which could lead to highly selective molecules.

It’s a long way from a 0.2 mM fragment to a useful lead series, but having a structure (or 21) dramatically improves the odds – as demonstrated here and here. The paper ends by suggesting that such a series has indeed been identified, and it will be fun to watch as the story unfolds.

15 August 2016

Dynamic combinatorial chemistry and fragment linking

Dynamic combinatorial chemistry (DCC) sounds incredibly cool. The idea is that libraries spontaneously form and reform. Add a protein and Le Châtelier's principle favors the formation of the best binders. In other words, not only does cream rise to the top, more cream is actually created.

The applications of DCC for fragment linking are obvious, and indeed early reports date back nearly twenty years to the dawn of practical FBDD. The latest results are described in a new paper in Angew. Chem. Int. Ed. by Anna Hirsch and collaborators mostly at the University of Groningen.

The researchers were interested in the aspartic protease endothiapepsin, which is a model protein for more disease-relevant targets. This is a dream protein: it is easy to make in large amounts, crystallizes readily, and is stable for weeks at room temperature. Readers will recall that this protein has also been the subject of multiple screening methods. Previous efforts using DCC had generated low micromolar inhibitors such as 1 and 2. These acylhydrazones form reversibly from hydrazides and aldehydes. Crystallography had also previously revealed that compound 1 binds in the so-called S1 and S2 subsites of endothiapesin while compound 2 binds in the S1 and S2’ subsites. In the current paper, the researchers enlisted DCC to try to combine the best of the binding elements.

To do this, the researchers chose isophthalaldehyde, which contains two aldehyde moieties, and nine hydrazides, which could give a total of 78 different bis-acylhydrazones. They incubated 50 µM of isophthalaldehyde with either four or five of the hydrazides (each at 100 µM), with or without 50 µM protein, and in the presence of 10 mM aniline to accelerate the exchange. Reactions were allowed to incubate at room temperature at pH 4.6 for 20 hours, after which the protein was denatured and the samples were analyzed by HPLC to see whether some products were enriched in the presence of protein.

Biologists may want to consider whether their favorite proteins would remain folded and functional under these conditions, and chemists may also balk at molecules containing an acylhydrazone moiety – let alone two. Leaving aside these concerns, though, what were the results?

As one would hope, some molecules were enriched over others when protein was present, though only by a modest two or three-fold. Two of the enriched molecules – both homodimers – were resynthesized and tested. Compound 13 was quite potent, and crystallography revealed that it binds in a similar fashion to compound 1, though electron density is missing for part of the molecule. Compound 16, on the other hand, is only marginally more potent than the starting molecules. Unfortunately the researchers do not discuss the activities of molecules that had not been enriched at all.

The paper ends by stating rather hopefully that DCC “holds great promise for accelerating drug development for this challenging class of proteases, and it could afford useful new lead compounds. This approach could be also extended to a large number of other protein targets.”

I’m not so sure.

This is an interesting study; the work was carefully done and thoroughly documented—but I’m less sanguine about whether DCC will actually ever be practical for lead generation. Indeed, the very fact that the experiments were done well yet are incapable of distinguishing a strong binder from a weaker one argues that the technique is inherently limited. I would love to see DCC work, but it seems to me that, even after two decades of effort, DCC has not been able to move beyond proof of concept studies. Does anyone have a good counterexample?

08 August 2016

Metallophilic fragments revisited

Way back in 2010 we highlighted work out of Seth Cohen’s lab at UC San Diego on “metallophilic fragments”, which are specifically designed to bind to metal ions. As long as one avoids PAINS, the approach could be useful for targeting metal-dependent enzymes. Indeed, multiple drugs derive much of their affinity by binding to metals; these include HDAC inhibitors (for cancer) and integrase inhibitors (for HIV). In a recent paper in J. Med. Chem., Cohen and colleagues describe work against an influenza target.

The researchers were interested in the so-called “PA subunit” of RNA-dependent RNA polymerase, which is both essential and highly conserved among influenza strains. The endonuclease in the PA subunit requires two metal ions, either Mn2+ or Mg2+, and in fact previous publications had demonstrated that metal chelators could inhibit the enzyme. In the current paper, the team screened about 300 fragments at 200 µM in an activity assay; those that inhibited >80% were retested to produce dose-response curves. Compound 1 came in as reasonably potent and impressively ligand-efficient, as is often the case with metal-binding fragments. Docking studies suggested that it could bind to both of the metal ions in the active site.
Initial SAR around compound 1 led to compound 10, with a significant improvement in potency that the researchers attribute to increased basicity and thus stronger interactions with the metals. Taking pieces from previously published molecules led to another increase in potency (compound 63). Separate fragment growing efforts off compound 1 led to sub-micromolar inhibitors such as compound 35. Combining both series led to compound 71, which is the best of the bunch with low nM activity, though it fell short of the hoped-for additivity of binding energies.

Compound 71 was also tested in cellular assays. Happily, it was able to protect cells from a lethal dose of influenza virus with an EC50 in the low micromolar range, about 100-fold below the cytotoxic dose observed in the same cell line. Of course, there is still a long way to go: no pharmacokinetic data are provided, and selectivity against other metalloproteins may be a challenge. Still, it will be interesting to watch future developments, both with this series and with the approach in general.

01 August 2016

Lead Generation: Methods, Strategies, and Case Studies

Lead generation refers to that point in drug discovery when initial screening hits against a target are wrought into compelling chemical matter. This chemical matter is often plagued with deficiencies in terms of potency, pharmacokinetics, or novelty, yet it provides a starting point for further optimization. This is the subject of a massive (800+ pages!) new two-volume work edited by Jörg Holenz (GlaxoSmithKline, formerly AstraZeneca) as part of Wiley’s Methods and Principles in Medicinal Chemistry series. Readers of this blog will not be surprised to find that fragments play a major role; indeed, the molecule on the cover of the book came out of FBLD. I won’t attempt to summarize all 25 chapters here, but will simply highlight those most relevant to FBLD.

Mike Hann (GlaxoSmithKline) sets the stage in chapter 1 by briefly describing the characteristics of successful leads. He emphasizes the importance of physicochemical properties and avoiding molecular obesity, and how judicious use of metrics can help navigate away from perilous chemical space. He also summarizes internal programs that again demonstrate that fragment-derived leads tend to be smaller and less lipophilic than those from other lead discovery techniques.

In chapter 3, Udo Bauer (AstraZeneca) and Alex Breeze (University of Leeds) discuss the concept of ligandability – the ability of a target to bind to a small molecule with high affinity. Fragments are ideally suited for assessing ligandability, and the researchers briefly describe fragment-based experimental and computational approaches to do so. They also include a nice 11-point summary of factors to consider when starting lead generation on a new target, ranging from the presence of small-molecule binding sites to the number of patent applications.

Chapter 6, by Ivan Efremov (Pfizer) and me, is entirely about fragment-based lead generation. I'm undoubtedly biased, but I think it provides a self-contained and fairly detailed guide to FBLD, including topics such as screening methods, hit validation, metrics, hit optimization, fragment growing vs fragment linking, and case studies on vemurafenib, BACE, MMP-2, LDHA, venetoclax, MCL-1, and GPCRs.

Helmut Buschmann and colleagues at RD&C Research, Development, and Consulting, focus in chapter 9 on optimizing side effects of known molecules to develop new drugs, but they also discuss some interesting older work reporting that 418 of 1386 drugs contain other drugs as internal fragments.

Chapter 12, by Dean Brown (AstraZeneca), is devoted to the hit-to-lead stage, and much of his advice is applicable to FBLD. Dean also includes a fantastic metaphor to illustrate the size of chemical space: "if a typical corporate screening collection were to fit on a postcard, the rest of the earth is the amount of available drug-like space." This assumes a million-compound library and a conservative estimate of 1023 drug-sized molecules, so if anything it is an understatement.

Molecular recognition is critical for both FBLD and lead generation in general, and this is the topic Thorsten Nowak (C4X Discovery Holdings) tackles in chapter 13. He covers key areas such as thermodynamics, emphasizing the importance of enthalpy while acknowledging the difficulty of prospectively using thermodynamic data. The role of water and halogen bonds are covered, along with some freakishly high ligand efficiency values. There are a couple errors: one paper is categorized as using dynamic combinatorial chemistry when in fact it actually used static libraries, and Tethering is confused with Chemotype Evolution, but overall there's lots of good stuff here.

Biophysical methods are covered in chapter 14, by Stefan Geschwindner (AstraZeneca). These include NMR, SPR, ITC, thermal shift assays, native mass spectrometry, microscale thermophoresis, and more.

Chapter 16, by Ken Page and colleagues at AstraZeneca, discusses "lead quality." This often entails various metrics, from simple ones such as ligand efficiency and LLE to more complicated attempts to predict clinical dosages. Although it is easy to poke fun at metrics, most thoughtful scientists find them useful for making sense of the reams of data generated in lead optimization campaigns.

Chapter 17, by Steven Wesolowski and Dean Brown (both AstraZeneca), is arguably the most entertaining. Entitled "The strategies and politics of successful design, make, test, and analyze (DMTA) cycles in lead generation," it is replete with pithy quotes and even an original (and highly geeky) cartoon. Along with multiple examples, the chapter formulates plenty of questions to consider during lead optimization, and ends with a particularly relevant quote by Billings Learned Hand: “Life is made up of a series of judgments on insufficient data, and if we waited to run down all our doubts, it would flow past us.”

In chapter 23, Sven Ruf and colleagues at Sanofi-Aventis Deutschland describe a success story generating leads against cathepsin A, a target for cardiovascular disease. HTS yielded three different chemical series with sub-micromolar activities, each with different liabilities. Crystallography revealed their binding modes, and this allowed the team to mix and match fragments across the different series to generate a molecule that ultimately went into the clinic. Although this may not be classic FBLD, it does seem to be a good case of using concepts from the field, or fragment-assisted drug discovery.

A similar, if less directed, approach is the subject of chapter 25, the last in the book. Pravin Iyer and Manoranjan Panda (both AstraZeneca) describe "fragmentation enumeration," in which known drugs or clinical candidates are fragmented into component fragments and recombined. On some level the fragments themselves are likely to be privileged; the researchers cite the famous quote by Sir James Black that "the most fruitful basis of the discovery of a new drug is to start with an old drug." Most of the work is computational, although one molecule derived from the approach has encouraging cellular activity against Mycobacterium tuberculosis.

There's far more to this book than could be listed even in this relatively long post, including multiple case studies, so for those of you who are interested in lead generation definitely check it out!

25 July 2016

Multiple bromodomains, multiple methods, and even more fragment hits

All this month Practical Fragments has been focused on bromodomains, highlighting chemical probes against BRD9, CBP and EP300, and family VIII bromodomains. Today’s post covers three earlier-stage programs on three different bromodomains.

In Acta Pharm. Sinica, Bing Xiong, Nai-xia Zhang, and colleagues at the Chinese Academy of Sciences discuss their work on BRD4, an anti-cancer target about which we’ve written previously. The researchers describe the construction of a fragment library designed for NMR screening; this is a good resource for people undertaking similar efforts. Interestingly, of 800 compounds purchased, only 539 were soluble to at least 100 µM in aqueous buffer. These were pooled into 56 groups of 8-10 compounds and screened at 200 µM (total fragments) using STD and T1ρ. This yielded 10 hits, of which three had measurable IC50 values from 110 to 440 µM. Five of the hits were characterized in more detail using two dimensional NMR (1H-15N HSQC), and three by X-ray crystallography. Some of these fragments are less-precedented as bromodomain ligands, and could be useful starting points for further work.

In contrast to BRD4, for which multiple ligands have been reported, the bromodomain on BRPF1 is less explored. In a recent paper in J. Med. Chem., Jian Zhu and Amedeo Caflisch (University of Zürich) provide 20 new co-crystal structures, all of which have been deposited in the protein data bank. The researchers performed a computational screen of 24,133 molecules using a program called SEED, which was able to crank through the entire set in just a day. Crystal soaking was attempted with thirteen of the top 30 hits, resulting in five structures, of which three bound in the manner predicted. Crystal structures of another 15 analogs and other bromodomain inhibitors were also determined. Some of the molecules are reasonably potent, with double-digit micromolar affinities and good ligand efficiencies.

Finally, while most bromodomains have a conserved asparagine residue that makes hydrogen bonds to the substrate (or inhibitor), 13 of the 61 known human bromodomains do not, and these tend to be more difficult targets. The second bromodomain of the pleckstrin homology domain-interacting protein (PHIP(2)), which has been implicated in melanoma, is one of these “atypical” bromodomains. Researchers at the Structural Genomics Consortium (SGC) led by Frank von Delft (Diamond Light Source) and Paul Brennan (University of Oxford) took a crystallography-first approach toward this target, as they report in an open-access paper in Chemical Science.

The researchers started by assembling what they call a “poised fragment library”. This is essentially a library designed for rapid follow-up chemistry, in which each library member can be deconstructed into individual components, which can be systematically varied. For example, a fragment might consist of two moieties connected by an amide bond, so that analogs could be easily made using parallel synthesis. The initial 2347 fragments were a subset of the 11,677 fragments available in-house or through collaborators, but the researchers also identify a set of 10,448 commercially available poised fragments. Commendably, they also provide full identities of both sets of fragments, which could be useful for folks building or adding to their own collections.

The Diamond Light Source is able to crystallographically screen 1000 fragments per week, but in this case only 406 diverse fragments were tested. Rather than using the nearly universal DMSO as a solvent, the researchers dissolved their fragments in ethylene glycol, since DMSO actually binds to bromodomains. Previous solution-phase screens of PHIP(2) at the SGC had come up empty, so the crystallographic screen was done at the very high concentration of 200 mM. Not surprisingly, this yielded just four hits.

Each of the hits bound in the acetyl-lysine recognition pocket, and three of them even showed high-micromolar activity in an AlphaScreen assay, with impressive ligand efficiency values. A few dozen analogs were made, which led to slight increases in activity in all cases, and measurable activity for analogs of the fragment which had shown no activity by itself. Although there is still a long way to go to find chemical probes for PHIP(2), at least there are now good starting points.

And that concludes bromodomain month. The number of papers and chemical probes that have come out just this year are a testament to the power of fragments to tackle this class of targets, perhaps equaled only by kinases. And while I'm not aware of any clinical candidates targeting bromodomains that started as fragments, I'm sure these will be coming soon.

20 July 2016

Fragments deliver a chemical probe for Family VIII bromodomains

Today’s post continues the theme of July as bromodomain month at Practical Fragments. The 61 human bromodomains (found in 46 proteins – some proteins have more than one) have been divided into eight families based on their sequences. Family VIII contains ten members, some of which are involved in keeping stem cells from differentiating. Two papers describe chemical probes that target some or most members of this family.

The first paper, which actually came out last year in Science Advances, is from a multinational group including Thomas Günther (Universität Freiburg), Stefan Knapp and Susanne Müller (both University of Oxford) and collaborators at Pfizer. The researchers started by screening libraries of acetyl lysine mimetics that had yielded inhibitors against other bromodomains. These came up empty; even promiscuous bromodomain inhibitors failed to hit Family VIII members. As is so often the case, when all else fails, the researchers turned to fragments. A thermal shift assay revealed that salicylic acid – the polypharmacological metabolite of aspirin – binds to the bromodomain PB1(5). Isothermal titration calorimetry (ITC) confirmed this result, providing a dissociation constant of 250 µM.

The researchers were also able to obtain a crystal structure of PB1(5) bound to salicylic acid in the acetyl lysine binding site common to all bromodomains, with the carbonyl making the usual hydrogen bond with a conserved asparagine. But whereas most other bromodomain binders make a water-mediated bridge to a conserved tyrosine, the phenol makes a direct hydrogen bond. The benzene ring also binds deeper in the pocket, displacing four highly conserved water molecules.

The subsequent medicinal chemistry optimization of this fragment is described in a paper published earlier this year in J. Med. Chem. by Dafydd Owen and colleagues at Pfizer, along with collaborators at the University of Oxford, DiscoveRx, Eurofins, the University of Massachusetts Worcester, and Johann Wolfgang Goethe University. Testing commercial and proprietary analogs of salicylic acid quickly revealed that uncharged enamides such as compound 2 were more effective at stabilizing PB1(5) against thermal denaturation than salicylic acid, and crystallography confirmed a similar binding mode.

Two rounds of library synthesis were conducted, first with 130 amines and then with 320 amines, with physicochemical properties of target compounds chosen in advance such that cLogP would range between 1 and 4. Seven family VIII bromodomains were screened in parallel, and compounds were identified with differing specificities. Some of the compounds were unstable in water, but introducing steric hindrance around the amine improved stability and led to compounds such as PFI-3. This is potent against the family VIII bromodomains PB1(5), SMARCA2A, and SMARCA4 and did not hit at least 40 other bromodomains tested. A related compound is active against more of the family VIII bromodomains while still maintaining good selectivity against other bromodomains.

Both of these probes are able to bind to family VIII bromodomains in cells and were used to explore the proteins’ biological roles. A variety of cellular phenotypic assays showed minimal changes, and the compounds do not appear to be toxic. They did attenuate myocyte or adipocyte differentiation, while PFI-3 caused embryonic stem cells to differentiate. One gets the impression that the researchers were hoping for more profound effects, but that’s why you make chemical probes in the first place. Whether or not these compounds will ultimately prove useful as drug leads, they should help to unravel some fiendishly complex biology.

15 July 2016

Fragments in the clinic: 2016 edition

There’s a new FBDD review out today in Nat. Rev. Drug Discovery. I know - there are lots of reviews each year - but this one is written by a who's who list of luminaries, including Steve Fesik (Vanderbilt), Rod Hubbard (Vernalis and University of York),  Wolfgang Jahnke (Novartis), and Harren Jhoti (Astex). I'm also an author so I'm undoubtedly biased, but I think it provides a nice overview of the field, especially for those who don't have time to read the recent book.

The review distills hard-won wisdom from two decades of work and covers practical decisions needed when using fragments: library design, screening methods, protein-ligand interactions, hit to lead strategies, and applications. Another useful feature is what I believe to be the most complete and up-to-date list of fragment-derived drugs that have entered clinical development. Where possible these include chemical structures, so definitely check it out.

The drugs themselves are listed below. Although it has not even been two years since the last compilation, it is exciting to see several promotions and new entrants. This table includes compounds whether or not they are still in development (indeed, some of the companies no longer even exist). A few compounds from earlier lists have been removed because their fragment origins could not be confirmed. 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 Plexxikon B-Raf(V600E)
Venetoclax AbbVie/Genentech Selective Bcl-2
Phase 3

PLX3397 Plexxikon FMS, KIT, and FLT-3-ITD
Verubecestat Merck BACE1
AZD3293 AstraZeneca/Astex/Lilly BACE1
Phase 2

AT7519 Astex CDK1,2,4,5,9
AT9283  Astex Aurora, JAK2
AZD5363 AstraZeneca/Astex/CR-UK AKT
Erdafitinib J&J/Astex FGFR1-4
Indeglitazar Plexxikon pan-PPAR agonist
LY2886721 Lilly BACE1
LY517717 Lilly/Protherics FXa
Navitoclax (ABT-263) Abbott Bcl-2/Bcl-xL
NVP-AUY922 Vernalis/Novartis HSP90
Onalespib Astex HSP90
Phase 1

ABL001 Novartis BCR-ABL
ABT-518AbbottMMP-2 & 9
ASTX660 Astex XIAP/cIAP1
AT13148AstexAKT, p70S6K, ROCK
AZD5099AstraZenecaBacterial topoisomerase II
BCL201 Vernalis/Servier/Roche BCL-2
PF06650833 Pfizer IRAK4

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.

11 July 2016

Fragments deliver a chemical probe for CBP and EP300

As we mentioned last week, July is bromodomain month at Practical Fragments. Today we’ll start by looking at two closely related bromodomains, one found in cyclic-AMP response element binding protein (CBP) and another from adenoviral E1A binding protein of 300 kDa (EP300). Both proteins have been implicated in a variety of diseases, particularly cancer, so a chemical probe would be very valuable.

Alexander Taylor and collaborators at Constellation Pharmaceuticals, Genentech, and WuXi, describe such a probe in a recent paper in ACS Med. Chem. Lett. The researchers screened about 2000 fragments in a thermal shift assay using 0.8 mM of each fragment. Compounds that increased the melting temperature of the CBP bromodomain by at least 1° C were validated first by time-resolved fluorescence resonance energy transfer and then by 15N HSQC NMR, ITC, and X-ray crystallography. Compound 1 was one of the more attractive hits, in particular because it was considerably less active against BRD4, whose inhibition causes all sorts of changes to cells.

Crystallography of the racemic compound clearly showed that only one of the enantiomers bound, and this was confirmed in functional assays when both enantiomers were tested separately. The active enantiomer makes some of the same interactions typical of all bromodomains with the natural ligand (N-acetylated lysine). Fragment growing was attempted off the aromatic ring, and although several vectors were tolerated, most decreased selectivity against BRD4. However, close examination of the structures revealed a promising vector that led to compound 14, with good selectivity against BRD4. Further optimization ultimately led to CPI-637, with low nanomolar activity against both CBP and EP300 as well as good cell-based activity. Crystallography revealed that this compound binds in a similar manner as the initial fragment.

The selectivity of CPI-637 against other bromodomains is also good (> 700-fold less active against BRD4), though it does hit BRD9 with sub-micromolar activity. Just as with the initial fragment, the opposite enantiomer of CPI-637 is considerably less active. Although no pharmacokinetic data are provided, at the very least this should be a useful probe for cell-based studies.

Switching gears to another aspect of CBP, the multidomain protein p300/CBP-associated factor (PCAF) has a bromodomain that may bind to CBP, though the biology is not entirely clear. PCAF is known to bind an acetylated HIV protein, and has been proposed as a target for AIDS. Obviously this is another opportunity for a chemical probe! The first steps are reported in a paper by Stefan Knapp and collaborators at Goethe University Frankfurt, University of Oxford, Leiden University, ZoBio, and University of Cambridge, published in J. Med. Chem (and open-access).

The researchers screened two separate fragment libraries using either thermal shift assays (at 1 mM fragment) or TINS. Hits were confirmed using SPR and crystallography, resulting in seven structures. As expected, all the fragments bound at the site where N-acetylated lysine normally binds. The PCAF bromodomain appears to be quite rigid, with little movement in structures with the different bound fragments. A few elaborated molecules were tested, with the best showing low micromolar affinity as assessed by ITC; crystal structures with these molecules are also reported and deposited in the protein data bank. It will be fun to see whether their potency can be improved.

We’ll have another post on bromodomains next week, but first stay tuned later this week for an updated list of fragment-derived drugs that have entered the clinic.

05 July 2016

Fragments deliver a chemical probe for BRD9

Bromodomains have nothing to do with bromine. Rather, they are small (~110 amino acid) domains that recognize acetylated lysine residues, a common modification on histones, and are thus key epigenetic “readers”. Humans have more than 60 of them, and as you can imagine selectivity is not assured. However, fragments have proven very useful in targeting these proteins. Since the first mention of bromodomains on Practical Fragments back in 2011 the number of posts has been growing rapidly, so for the first time ever we’ve decided to devote an entire month to the topic.

In other words, July is bromodomain month! We’ll start with two papers against the bromodomain BRD9, part of the SWI/SNF chromatin remodeling complex that seems to be important for acute myeloid leukemia.

The first paper, in J. Med. Chem. (and open access), is published by Laetitia Martin and collaborators at Boehringer Ingelheim, University of Oxford, and Cold Spring Harbor. The researchers used three orthogonal biophysical screening methods: differential scanning fluorimetry (DSF), surface plasmon resonance (SPR), and microscale thermophoresis (MST). A library of 1697 fragments was screened at 0.4 mM (DSF), 0.1 mM (SPR) or 0.5 mM (MST), and hits were then validated using 15N HSQC NMR. The 77 hits that confirmed were taken into crystallography, producing 55 structures.

Validation rates in the NMR secondary screen were excellent for DSF (94%) and SPR (84%) but less so for MST (31%). That said, of the 38 validated hits from MST, 29 were not found in either of the other techniques, and 14 of these produced crystal structures. This is a useful reminder that while screening cascades can whittle down many hits, they do run the risk of throwing out the proverbial babies along with the bathwater.

In parallel with the biophysical screens, a virtual screen of ~73,500 fragments was conducted using Glide to identify 208 fragments that were then tested using SPR and DSF. This led to 23 hits, 11 of which produced crystal structures.

Two of the more potent fragments were the structurally related compound 3 (from the biophysical screen) and compound 4 (from the virtual screen). Optimization started with compound 4 by adding electron donating groups to the phenyl ring to try to improve a stacking interaction observed in the crystal structure. This led to compound 10, and building out the other ring to make it more similar to fragment 3 led to BI-9564.

BI-9564 has low nanomolar activity in both a biochemical assay as well as isothermal titration calorimetry (ITC). It is also quite selective: among 48 other bromodomains, it only hits the closely related BRD7 and CECR, and it is >10-fold more potent on BRD9. None of a panel of 321 kinases were inhibited with IC50 < 5 µM, and only 2 of 55 GPCRs were inhibited. The compound is also cell active, reasonably soluble, has good pharmacokinetics in mice, and orally bioavailable. In short, BI-9564 is an excellent chemical probe – and is in fact being offered as such.

While we’re on the subject of BRD7 and BRD9, it’s worth noting another recent paper, this one in ChemBioChem from Ke Ruan and colleagues at the University of Science and Technology of China. The researchers screened their library of 890 fragments against BRD7 using three different ligand-detected NMR techniques: STD, WaterLOGSY, and CPMG. Fragments were screened in pools of 10 with each fragment present at 400 µM. This yielded just 10 hits, of which 5 confirmed when tested individually. Protein-observed NMR was then performed on these, suggesting that they all bind in the acetyl-lysine recognition sites; they have similar affinities for both BRD7 and BRD9, with dissociation constants between 22 and 600 µM. Crystallography confirmed the binding mode for one of the fragments bound to BRD9. Interestingly, this showed quite a bit of plasticity in the protein compared to the un-liganded structure. Indeed, the BI researchers suggest that different degrees of protein flexibility between BRD7 and BRD9 could account for the selectivity differences observed for BI-9564.

Stay tuned next week for more fragment-screening against a different class of bromodomains!

27 June 2016

Fragments vs Lp-PLA2 – less greasily

Human lipoprotein-associated phospholipase A2 (Lp-PLA2) is an enzyme involved in lipid metabolism that is implicated in multiple diseases, from atherosclerosis to Alzheimer’s. Because the natural substrates are lipophilic phospholipids, it is no surprise that reported inhibitors are also large and hydrophobic. A case in point is darapladib: with a molecular weight of 667 Da and a clogP of 8.3 this is a poster child for molecular obesity – and it also failed in phase 3 clinical trials. A new paper in J. Med. Chem. by Alison Woolford (Astex), Joseph Pero (GlaxoSmithKline) and colleagues describes an effort to discover less lipophilic inhibitors.

The researchers performed a screen of 1360 fragments using thermal shift and ligand-detected NMR and a smaller screen of 150 fragments using crystallography. This yielded 34 fragments that were ultimately characterized crystallographically; screening commercial and in-house collections for related fragments yielded another 16. Interestingly, rather than clustering at a single hot spot, these fragments bound to different regions of the extended active site, with some – such as fragment 6 – a full 13 Å from the catalytic center. This is reminiscent of a fragment campaign against soluble epoxide hydrolase, another enzyme with a long, hydrophobic active site.

In addition to binding in an interesting site, fragment 6 also has good affinity and ligand efficiency. Moreover, its binding site overlaps partly with that of fragment 5. Thus, the researchers merged the two fragments together, resulting in compound 7, with submicromolar activity.

Further structure-guided optimization, which included growing into a polar region of the protein, ultimately led to compound 16, with low nanomolar potency.

Compound 16 has a molecular weight of 411 Da and a clogP of 3.4 and is correspondingly reasonably soluble (> 0.3 mM). Whereas darapladib showed a dramatic 700-fold potency decrease upon addition of human plasma – presumably due to nonspecific binding to other proteins – the decrease in potency for compound 16 is only 13-fold. Indeed, though darapladib is a picomolar binder, compound 16 is slightly more potent in plasma.

Unfortunately, compounds in this series turned out to have high clearance in rats, proving once again that lead optimization is often a frustrating game of whack a mole. Still, the fact that the researchers were able to develop smaller, more soluble inhibitors of an enzyme with such a lipophilic substrate gives hope that the game is perhaps winnable.

20 June 2016

19F-NMR-guided fragment linking on BACE1

Fragment growing has been the dominant strategy of most of the recent posts involving lead optimization, consistent with our poll results. However, fragment linking can be powerful too, as illustrated by the recent approval of venetoclax, which was derived from fragment linking. A recent paper in J. Med. Chem. by Brad Jordan and colleagues at Amgen provides another nice case study.

Amgen researchers had previously used fragment growing to discover inhibitors of BACE1, an Alzheimer’s target which has been heavily tackled by fragments. However, the most potent molecules in the series also inhibited the related aspartic protease cathepsin D (CatD), which could cause serious side effects. The researchers sought to gain selectivity by building inhibitors to occupy the so-called S3subpocket of BACE1. To do so, they used 19F-NMR to find fragments that would bind to BACE1 in the presence of a “blocking compound” that filled most of the active site but not the S3subpocket. This led to the discovery of seven fragments, the most potent being compound 3. Interestingly, this fragment only bound in the presence of the blocking compound as assessed both by NMR and SPR. Also, it could be competed by a compound that binds in the S3subocket.

Having thus identified a fragment that bound in the presence of one of their inhibitors, the researchers used interligand NOE (ILOE) to determine how the two compounds bind relative to one another. This supported the idea that compound 3 binds in the S3subpocket, and also suggested how the fragment could be linked onto the existing lead series, exemplified by compound 5. Just four compounds were designed and synthesized, and all of them were more potent than either of the starting points, with compound 9 being the best. More importantly, this compound also proved to be ~2000-fold selective for BACE1 over CatD in enzymatic and cell-based assays.

Despite the excellent (high picomolar) affinity of compound 9 for BACE1, this is actually about 25-fold worse than would be predicted by a simplistic additivity of binding energies – a not uncommon occurrence when linking molecules. Still, with its combined used of multiple NMR techniques and structure-based design to solve a specificity challenge, this paper is worth perusing.

15 June 2016

Covalent fragments writ large

We’ve written previously about irreversible covalent fragment-based lead discovery. The nice thing about irreversible inhibitors is that they have an infinite no off-rate: once they bind and react with a target, that protein is permanently out of action. A paper published today in Nature by Keriann Backus, Benjamin Cravatt, and colleagues at Scripps Research Institute takes this approach to a whole new level.

The researchers assembled a library of just over 50 fragments containing cysteine-reactive electrophiles, such as chloroacetamides and acrylamides; the average molecular weight was 284 Da. These were then screened against human cells or cell lysates using a proteomic approach called isotopic tandem orthogonal proteolysis-activity based protein profiling (isoTOP-ABPP). This technique, previously developed by the Cravatt laboratory, uses mass spectrometry to differentiate contents of treated and untreated cells and identify specific regions of proteins that are modified.

In all, 758 cysteine residues in 637 different proteins were found to be modified by at least one of the fragments. These included targets (such as BTK) with known covalent drugs as well as many proteins with no small molecule inhibitors. Even more exciting, this set included some particularly challenging classes of proteins, such as transcription factors and various adapter and scaffolding proteins. Most proteins only had a single modified cysteine, and these were not necessarily in the active site (see also here). Happily, computational docking did a good job of (retrospectively) predicting the modified cysteine residues.

The fragments themselves ranged significantly in how many cysteines they modified, from < 0.1% to > 15%, with a median of 3.8%. Interestingly, the correlation with intrinsic electrophilicity – as measured by reaction with the small molecule thiol glutathione – was fairly weak. This suggests that the fragments are modifying proteins based on other properties, such as specific interactions between fragment and protein.

The initial studies were done using cell lysates at high (500 µM) fragment concentrations. Follow-up studies in whole cells using 50-200 µM fragment gave similar results, with 64% of the cysteines from the lysate experiments reacting with the same fragments in cells, even at the lower concentrations. Interestingly though, four fragment-cysteine interactions were found only in cells and not in lysates.

One class of proteins you might expect reactive fragments to hit are cysteine proteases, such as the caspases, and indeed one chloroacetamide-containing fragment reacted with the active site cysteine of caspase-8 (CASP8). Surprisingly though, this fragment showed only marginal activity in an inhibition assay, and subsequent experiments revealed that it is selective for the inactive zymogen (or proenzyme) form of the protein, thereby preventing activation. This fragment does not react with the related caspases 2, 3, 6, or 9, though it does hit CASP10. Modest modifications led to a compound that was also selective for CASP8 over CASP10. These two molecules were used to show that both CASP8 and CASP10 appear to be essential for extrinsic apoptosis in primary human T cells, but not in the immortalized Jurkat T-cell line.

Of course, it will be essential to rigorously characterize any covalent molecules used as probes. Chloroacetamides are well-known electrophiles – so well known in fact that they are generally excluded from screening libraries, including those that helped define the original PAINS filters. A single digit percentage hit rate means that any given covalent fragment could easily hit hundreds of proteins. The researchers here do careful control experiments – such as using an inactive enantiomer and extensive proteomic analyses – but someone less careful could easily mislead themselves and others. Done rigorously, though, this is an exciting approach that may well increase the number of ligandable targets.

13 June 2016

Fragments vs MetAP2: reversible inhibitors

Methionine aminopeptidases, or MetAPs, cleave the N-terminal methionine residue from newly translated proteins. The human enzyme MetAP2 is a potential target for obesity, as demonstrated by the impressive clinical results of beloranib. But this drug hasn't been approved, and patients have died while taking it. Beloranib is an irreversible inhibitor that may also hit other targets, so researchers at Takeda California have been seeking non-covalent inhibitors. They report their results in two recent papers in Bioorg. Med. Chem. Lett.

In the first paper, Zacharia Cheruvallath and colleagues describe a biochemical fragment screen of ~5000 fragments (11-19 non-hydrogen atoms) conducted at 0.1 mM. This produced an impressive number of hits (110 compounds with > 20 % inhibition), which were triaged based on both ligand efficiency and LLE, ultimately yielding 16 interesting fragments. In particular, fragment 6 is remarkably potent.
Crystallography was not successful for any of the fragments. Undeterred, the researchers performed classic “SAR by catalog” (and corporate collection) to develop a binding model. This quickly revealed that the hydroxyl group was unnecessary. It also suggested that one of the indazole nitrogen atoms might be interacting with an active site metal ion, and that the bromine might be pointing towards a hydrophobic pocket where the side chain of the methionine substrate normally binds. Growing led to compound 16, and a closely related compound was characterized crystallographically bound to the protein, confirming the model. Further optimization led to compound 38, with low nanomolar potency in both biochemical and cell-based assays, excellent selectivity against a panel of >100 other targets, good oral bioavailability, and reasonable pharmacokinetics. This compound caused dose-dependent weight loss in a mouse model of obesity.

The second paper, by Christopher McBride and colleagues, involved more dramatic changes to the fragment. The indazole 4 is very potent, but indazoles are quite common in the literature, so the researchers sought to scaffold-hop to a novel core. This led them to design compound 6’, and using some of the SAR from the previous series ultimately led to compound 10. As with compound 38 above, this compound showed good cell-based activity, acceptable pharmacokinetics, oral bioavailability, and a clean profile against > 100 off-targets at 10 µM. It also showed measurable weight loss in a rodent model of obesity.

The question sometimes arises as to how many fragment hits are necessary for a program to move forward. These two papers show that a single fragment can be elaborated to two very different lead series with animal efficacy. In contrast to some of our recent posts, these efforts did not initially require crystallography. There are many ways to advance fragments, and no single technique is essential.

06 June 2016

Fragments vs Dengue virus polymerase

Dengue fever, evocatively called “breakbone fever” for the severe pain it can inflict, is caused by a mosquito-borne virus that infects hundreds of millions of people each year. There are no approved antiviral treatments. Two papers from researchers at the Novartis Institute for Tropical Diseases and the University of Texas Galveston provide some promising early leads.

The first, in J. Biol. Chem., by Christian Noble, Pei-Yong Shi, and collaborators, describes a crystallographic screen of 1408 fragments against Dengue virus RNA-dependent RNA polymerase (DENV RdRp), which is highly conserved among the four serotypes of Dengue virus. Crystals were soaked in pools of eight fragments, with each present at only 0.625 mM, ten to one hundred times lower than other recent crystallographic screens. Perhaps because of this low concentration, only a single hit was identified – compound JF-31-MG46. The crystal structure revealed that the molecule binds in the “palm subdomain” of the protein, which is analogous to a druggable site on the hepatitis C virus protein.

Surface plasmon resonance (SPR) showed that this fragment had a dissociation constant of 0.21 mM against RdRp from serotype 3 and 0.61 mM against RdRp from serotype 4, suggesting weak but real binding. Isothermal titration calorimetry (ITC) was not successful, perhaps because of compound solubility, but replacing the terminal phenyl group with a thiophene led to more potent compounds which could be characterized both by SPR and ITC. The compounds were also active in an enzymatic assay, with IC50 values comparable to their affinities.

The second paper, by Fumiaki Yokokawa and collaborators and published in J. Med. Chem., describes the optimization of these fragments. Fragment growing was performed to try to displace a bound water molecule, resulting in the low micromolar compound 17. Compounds that contain carboxylic acids often have low cell permeability, so several bioiosteres were tested to try to replace this moiety, and compound 23 showed increased affinity. However, this compound was still quite polar, showed poor permeability, and no cell activity. Adding a lipophilic substituent and decreasing the acidity led to compound 27, with nanomolar affinity and enzymatic inhibition of all four Dengue virus serotypes. Importantly, this compound also showed low micromolar activity against all four serotypes in cell assays.

The J. Med. Chem. paper notes that a high-throughput screen against RdRp had been plagued with false positives. One validated low micromolar hit was optimized to nanomolar potency, but this was very lipophilic and displayed no cell activity. It is interesting that the fragment-derived leads initially displayed no cell activity for the opposite reason: they were too polar. This is a useful reminder that physicochemical properties matter. The successful optimization of the fragment-derived series suggests that it can be easier to make leads more lipophilic than less.

01 June 2016

Fragment library vendors - 2016 version

It's been two years since we last updated our list of commercial fragment libraries, and there have been several changes. The prompt for updating the list is a new Perspective published in J. Med. Chem. by György M. Keserű & György G. Ferenczy (Hungarian Academy of Sciences), Mike Hann & Stephen Pickett (GlaxoSmithKline), Chris Murray (Astex), and me. This covers all aspects of fragment library design, so definitely check it out.

One table in the Perspective compares various libraries, both commercial and proprietary. One of the manuscript reviewers asked if we could evaluate the various vendors, particularly given some negative experiences with commercial compounds. Such direct criticism (and praise!) can be awkward in the peer-reviewed literature, but is more acceptable in an online forum - think of Yelp for library suppliers. Please comment (anonymously if desired) if you've had experiences, positive or negative, with these vendors, and please feel free to add any we omitted.

Note that this list only includes companies that sell their libraries (as opposed to just using them internally).

ACB Blocks: 1280 compounds, 19F NMR-oriented, RO3 compliant, predicted to be soluble, purity >96%

Analyticon: 213 compounds, fragments from nature, RO3 compliant, high solubility, purity >95%

Asinex: >22,000 compounds

ChemBridge: >7000 compounds, RO3 compliant with predicted solubility; minimum purity 90% by 1H NMR

ChemDiv: >4000 3D fragments

Enamine: Multiple subsets including >18,000 RO3 compliant, ~1800 "Golden", and >126,000 with < 20 heavy atoms. Also separate fluorinated, brominated, sp3-rich, and covalent subsets.

InFarmatik: 1700 member consolidated library with different subsets (3D, GPCR, kinase)

IOTA: 1500 diverse, mainly RO3 compliant fragments

Integrex: 1500 compounds with diversity in shape and chemical structure, RO3 allowing one violation

Key Organics: ~26,000 compounds total with multiple subsets including 1166 with assured solubility and RO3 compliant as well as brominated, fluorinated, and CNS-directed fragments

Life Chemicals: 31,000 fragments of which 14,000 are RO3 compliant; also fluorinated, brominated, covalent, Fsp3-enriched, and covalent subsets

Maybridge: >30,000 fragments in total. The 2500 Diversity collection is guranteed soluble at 200 mM in DMSO and 1 mM in PBS.  NMR spectra are available (in organic solvent). It is available in many formats, from powder to DMSO-d6 solution. A smaller 1000-fragment subset is also available.

Otava: >12,000 fragments with various subsets including fluorinated, brominated, and metal-chelating

Prestwick: 910 mainly derived from drugs, RO3 compliant

Timtec: 3200 compounds, structurally diverse with predicted high solubility

Vitas-M: ~19,000 fragments, RO3 compliant

Zenobia:  968 fragments from different design paradigms, cores from drugs, higher Fsp3, flexible cores

30 May 2016

Fragments in Texas

The meeting Development of Novel Therapies through Fragment Based Drug Discovery was held last week in Houston, Texas, organized by the Gulf Coast Consortium for Quantitative Biomedical Sciences. Although it was only a single day, it was packed, with thirteen speakers, a couple vendor lunch talks, and some two dozen posters. Below is just a flavor – please add your own impressions if you were there.

I kicked off the first session by giving an overview of FBDD, highlighting both pitfalls and successes. Beth Knapp-Reed (GlaxoSmithKline) then discussed efforts against LDHA, a target previously tackled successfully using fragment linking (see here and here). In this case, an HTS screen of 1.9 million compounds produced only a single hit that resulted in a crystal structure, while fragment screens yielded 16 structures at three binding sites. An NMR-based functional screen (using 13C-labeled substrate) was key to obtaining robust SAR, and using information from both the HTS hit and the fragments ultimately led to nanomolar inhibitors. Next, Tom Davies provided an overview of Astex’s discovery platform, focusing on a success with KEAP1. We recently highlighted research suggesting that crystallography should be used as a primary screen, which Astex does for some targets. Tom noted that doing so currently takes about a month, though only after spending somewhere between 3 and 12 months establishing a robust protein construct as well as crystallization and soaking conditions.

Jane Withka opened the next session by discussing the continuing evolution and use of the Pfizer fragment library. Out of 32 targets screened, only one produced no hits, and this was a particularly flexible protein. Interestingly, despite being relatively balanced among basic, acidic, and neutral members, hits were strong enriched in neutral compounds and strongly depleted in basic fragments. Neutral fragments were exactly what was sought by Daniel Cheney (Bristol-Meyers Squibb), who discussed successful efforts to replace a basic amidine moiety in Factor VIIa inhibitors. And Brad Jordan (Amgen) discussed the successful application of 19F NMR screening to find fragments that could be linked to previously discovered inhibitors to obtain selective picomolar inhibitors of BACE1.

Alex Waterson (Vanderbilt) started the first afternoon session by discussing how fragments had been successfully applied to RPA, RAS, and MCL-1. In the last case, the best compounds now have dissociation constants in the picomolar range, are active in cells, and show activity in xenograft models. IND-enabling studies are slated to begin as early as this year, with the hope of developing a cousin of venetoclax. Inna Krieger (Texas A&M) described how fragments could be used to understand the mechanism of M. tuberculosis malate synthase, while Dawn George (AbbVie) described selective (but inexplicably toxic) PKCθ inhibitors, which are now being made available to researchers to probe the biology. Finally, Damian Young (Baylor) gave an update on his sp3-carbon enriched fragments. Jane had mentioned that following up on hits with multiple stereocenters was not always easy, but Damian’s DOS approach efficiently and systematically yields each possibility. Whether these will meet the Safran-Zunft challenge remains to be seen.

The last session was focused on success stories. Michael Mesleh (Broad Institute) discussed Cubist’s bacterial DNA gyrase inhibitors. Marion Lanier (Takeda) described how fragment screening and careful medicinal chemistry led to a low nanomolar, selective inhibitor of BTK. With a molecular weight of just 318, the molecule is scarcely larger than a Texas fragment, and has good pharmacokinetics and activity in a rat arthritis model. And Yi Liu (Kura) discussed the optimization of covalent KRAS inhibitors originally discovered using Tethering.

This was my first visit to Houston, and I was struck by the number of researchers who had relocated from around the world, particularly from (previously) large(r) pharma companies. Whenever scientists meet the talk often turns to funding shortages, but not here: everyone seemed to have plenty of money and resources, and one of the organizers announced that he was trying to fill several positions. This was the first major fragment meeting in Texas but likely not the last – there is talk of turning it into a recurring event. And there are still several good upcoming events this year; early registration for FBLD 2016 closes in just a few weeks.

23 May 2016

Calculating hotspots in detail

In the eight years since Practical Fragments first started, Moore’s law has held strong and computational power has increased accordingly. Last year we described how tools such as FTMap can be used to identify hot spots – regions on proteins where fragments are most likely to bind. Although FTMap is quite successful at identifying these, it is less able to point to specific interactions (such as hydrogen bond donors or acceptors) that are likely to drive binding. In other words, computational chemists have become adept at identifying where fragments might bind but lag in predicting how. A new paper in J. Med. Chem. by Chris Radoux at the Cambridge Crystallographic Data Centre and collaborators at UCB and the University of Cambridge addresses this challenge.

The approach starts with a set of three simple molecular probes: toluene, to look for hydrophobic interactions; aniline, to look for hydrogen bond acceptors; and cyclohexa-2,5-dien-1-one, to look for hydrogen bond donors. These probes are larger than those (such as ethanol) used in many other programs, the idea being that too-small molecules might find hot spots so small as to be useless. Indeed, with 7 non-hydrogen atoms, these probes are near the low end of the consensus size for fragments.

Calculations are performed on protein structures – either with no ligand bound or with a bound ligand computationally removed – to determine whether each surface atom of the protein is a hydrogen bond donor, acceptor, or hydrophobic, as well as how exposed the particular atom is. The three probes are then mapped onto the proteins to look for favorable interactions. Regions where multiple probes can bind are scored higher, with hotspots defined as those regions of the protein having the highest scores. The type of probe with the highest score also describes what type of interactions are likely to be favorable at various regions within a given hot spot. Although the researchers note that multiple software packages could be used for these calculations, they used a program called SuperStar, and calculations took just a few minutes on an ordinary laptop.

To validate the approach, the researchers used a previously published data set (discussed here) of 21 fragment-to-lead pairs against a variety of proteins for which crystal structures and binding affinities were available. In general, the method was able to identify the fragment binding site quite effectively; the one outright failure was on the fragment with the lowest affinity, which also had poorly resolved electron density in the crystal structure. Importantly, the fragments tended to have the highest scores, with added portions of the leads scoring lower. This data set was used to calibrate the scoring system for identifying hot spots, as well as specific molecular interactions within each hot spot.

Having thus validated the approach, the researchers took a more detailed look at two published fragment-to-lead programs for protein kinase B and pantothenate synthetase. In both these cases, group efficiency analyses had previously been performed to establish which portions of the ligands contributed most significantly to binding. Gratifyingly, the computations correctly predicted these.

Overall this approach appears promising. At a minimum, it is another tool for assessing the ligandability of potential targets. More significantly, by highlighting the hottest bits of hot spots, it could be useful for medicinal chemists trying to optimize and grow fragments and leads. Unfortunately, as currently described, the process will require a skilled modeler. It would be nice if the authors built a simple web-based interface for people to upload pdb files for analysis, as is the case for FTMap. Also, all the data presented are retrospective – a prospective example would be the true test. Does anyone have experience to share?