Fragments in silico, confirmed by X-ray

I’ve always been something of an empiricist, and have therefore been wary of computational fragment screening. It’s not that I think it’s impossible, just that the algorithms and parameters developed to date have not often shown themselves up to the task. A paper just published in Nature Chemical Biology from Brian Shoichet’s group at UCSF has caused me to reconsider my skepticism.

Shoichet and Yu Chen used the program DOCK to screen 67,489 commercially available fragment-sized molecules contained in the database ZINC against the active site of the beta lactamase CTX-M, a bacterial enzyme responsible for resistance to penicillin and cephalosporin. Of 69 top hits, 10 actually inhibited the enzyme when tested experimentally. In contrast, of 37 high-scoring hits from a similar computational screen of 1,147,326 larger lead-like molecules, none showed any inhibition up to the limit of their solubilities.

Interestingly, each of the ten active fragments contained an anionic group: 3 carboxylates, 2 sulfates, and 5 tetrazoles among the set. A reexamination of the docked lead-like molecules revealed a relatively high-scoring tetrazole, which exhibited an experimental Ki value of 21 micromolar (see figure). Although this was an in silico hit, it was swamped by the number of (inactive) hits and so had not been selected for experimental follow-up until the fragment results revealed tetrazoles to be privileged pharmacophores. Additional similarity searching of the lead-like molecules led to two additional low micromolar inhibitors.



Five of the inhibitory fragments and one of the lead-like molecules were characterized crystallographically, and the results were remarkable: all of them bound in a similar manner to that predicted by docking.

Chen and Shoichet also investigated the specificity of the fragments compared to the lead-like compounds, and the results agreed well with those predicted by Hann and colleagues (as discussed on our sister blog FBDD-Lit here). Namely, while the fragments had relatively low specificity against a mechanistically distinct beta lactamase (AmpC), the lead-like molecule exhibited roughly 100-fold tighter inhibition of CTX-M. In other words, fragments likely have a higher hit rate (and correspondingly lower specificity) due in part to their simplicity, but as fragments are elaborated, specificity can be readily built into the molecules.

So does this mean the era of computational fragment-based screening has arrived? While these results are impressive, it is important to keep them in perspective. CTX-M has a relatively rigid active site, while many proteins of interest show a level of flexibility that confounds modeling. Moreover, Chen and Shoichet were working with an ultra-high resolution (0.88-Angstrom) crystal structure of CTX-M in which they could actually see density for hydrogen atoms on some polar groups. Needless to say, this is atypical. Still, the paper does give hope that the computational tools are ready, as long as they are applied to appropriate systems.

Fragments on Glass

I’m always a fan of new fragment technologies, and Hioryuki Osada and colleagues at RIKEN have just published a very intriguing one which they call a “fragment combination array,” or FCA.

The approach involves immobilizing fragments onto a specially prepared glass slide using a photogenerated carbene reaction; this can be done as an array of microscopic spots. Next, the glass slide is treated with a fluorescently labeled protein and washed. If the protein sticks to the small molecule, it will show up as a fluorescent spot. Appealingly, if the protein of interest is genetically fused to a fluorescent protein, crude cell lysates can be used, simplifying the assay. The researchers previously demonstrated that natural products and drugs could successfully be immobilized to a treated glass chip using this method, and that the molecules retained their ability to bind to protein targets, despite the covalent linkage to the chip.

Of course, binding interactions between drugs and their targets are generally much stronger than between fragments and their targets. Also, because fragments are so small, there is a higher probability that the part of the fragment used to attach to the glass will be critical to but inaccessible for binding. Fortunately, the carbene chemistry is fairly non-selective, inserting into C-H and O-H bonds at random; thus, the likelihood is that at least some of the fragments will bind in a productive fashion. The technique is conceptually similar to the SPR-based methodology used by Graffinity, though to my knowledge Graffinity screens individual fragments as opposed to binary pairs.

But does it actually work? An initial proof-of-concept used FKBP12 ligands, the same ones previously described in the first famous “SAR by NMR” paper. In that example, a low micromolar pipecolinic acid derivative was linked to a high micromolar benzanilide derivative to generate a nanomolar binder to FKBP12. In the current case, the immobilized pipecolinic acid derivative was able to capture fluorescently-labeled FKBP12, while the benzanilide was not. However, co-spotting the two fragments led to a much stronger signal (more fluorescence) than the pipecolinic acid spot alone, suggesting synergy between the two immobilized fragments.

Having shown this, the researchers next turned to the protein carbonic anhydrase II (CAII), which has a predilection for sulfonamides. They created an array from four aromatic sulfonamide-containing fragments (and one negative control) and ten diverse non-sulfonamide-containing fragments. A screen of these 50 different mixtures against fluorescently-labeled CAII revealed a number of hits, and by merging elements of one of the diverse compounds onto a sulfonamide “anchor” fragment, the researchers were able to improve the potency of the sulfonamide from 435 nM to 29 nM.

Of course, there are limits: clearly the technique is not as sensitive as many other fragment-detection methods, as illustrated by the inability to detect benzanilide binding to FKBP12, an interaction with a Kd in the mid to high micromolar range. In fact, both test cases involve protein targets that have been shown to be highly amenable to fragment-based methods, and both start with known fragments with relatively high affinities. Moreover, the covalent immobilization methodology won’t work for all fragments; acetazolamide, a fragment-like high-affinity binder of CAII, didn’t work in this assay, likely due to poor geometry or sterics of the immobilized fragment.

Still, FCA is a neat and potentially very rapid method for finding a second fragment once a first has been identified. It will be fun to watch how the technique evolves.

Fragments 2009

Just a few quick thoughts on RSC BMCS Fragments 2009, which I had the pleasure of attending at AstraZeneca’s beautiful new conference center in Alderley Park, UK. The quality of the talks and posters was very high, and in many cases speakers presented unpublished and exciting research, so I don’t want to steal their thunder here (though see the FBDD-Lit blog for some nice summaries).

One striking observation was the number of speakers from big pharma. Of the 16 oral presentations, almost a third were from AstraZeneca, Pfizer, GlaxoSmithKline, or F Hoffmann-La Roche. Biotech represented about half the talks, with the remainder from academia.

Attendees were similarly diverse, both by employer as well as geography. Besides the UK and USA, many European countries were represented, as were China, Japan, and Korea. I remember recently it was rare to find anyone exploring fragments outside of the US and the UK.

Rod Hubbard observed in his closing talk that just a few years ago fragment-based drug discovery was seen as the domain of “exotic eccentrics.” No longer. The concept has gone mainstream, there has been a convergence as to the methods (particularly a rapid adoption of surface plasmon resonance), and large pharmaceutical companies are investing substantial resources in FBDD. I think the field can look forward to a wealth of new discoveries.

And for those of you who missed it, feedback was sufficiently positive that there will likely be a sequel: Fragments 2011.

Guest Blogger: Brian Stockman

[DrZ: Most of you probably know Brian and his excellent work in NMR and drug discovery, especially fragments. I have asked Brian to summarize his most recent paper for us. Below is his contribution. The Editors would welcome others to do the same if they are so inclined.]


A recent paper from Pfizer [Chemical Biology & Drug Design 73, 179-188 (2009)] described the concerted use of NMR screening, competition binding, TROSY-based binding site mapping, and NMR-based activity assays to identify allosteric fragment activators of 3-phosphoinositide-dependent kinase-1 (PDK1). This protein kinase presented an interesting challenge since, in addition to the ATP site typically targeted by structure-based drug design efforts, it was known to have an allosteric site that could activate (or potentially inhibit) activity.

An STD-based NMR screen resulted in 372 fragment hits out of 10,237 fragments screened. Testing the compounds in an activity assay would normally eliminate the many false-positive artifacts of the STD assay. A first pass of the hits through a Kinase-Glo assay revealed that many were in fact inhibitors. Fragments without activity in this assay, however, could not be discarded since this assay was not capable of monitoring events at the allosteric site and could not distinguish ‘non-inhibitors’ from activators. Thus fragments that did not inhibit in the Kinase-Glo assay were also run in a Caliper assay. This assay uses a shorter peptide substrate and is capable of detecting inhibition and activation. Ultimately, a subset of the original fragment hits that were either inhibitors with high ligand efficiencies, activators, and/or had very novel chemical structures were chosen for further studies.

STD competition binding experiments using the known ATP-site binder staurosporine or a short peptide known to bind in the allosteric pocket were very useful to distinguish these two binding sites. TROSY-based binding site mapping, using 15N-labeled PDK1 expressed in baculovirus, was used to confirm the binding site for several key compounds. Finally, the biochemical assay data was complemented with 19F NMR-based activity assays. These assays used the 2-fluoro-ATP method described in a previous paper from Pfizer [Journal of the American Chemical Society 130, 5870-5871 (2008)].

NMR-based activity assays proved very valuable since they could easily handle high fragment concentrations, and, since they directly monitor conversion of substrate to product, were capable of detecting both inhibition and activation. NMR-based activity assays are single-enzyme assays. As such, they are quite useful as both primary fragment screening assays and as orthogonal HTS-triage assays. NMR-based activity assays have been characterized as the ‘uncola’ of biochemical assays because, as opposed to many HTS and bench top assays, they do not rely on any coupling enzymes for their detection. NMR-based activity assays should prove very valuable for accurately evaluating compounds in the 10 uM to 1 mM dynamic range of activity typical of fragments.

Fragments in the clinic: How many?

At the Tri-Conference last week, Maria M. Flocco of Pfizer stated that a search of the IDDB3/Prous databases yielded 30 examples of compounds that had made it into the clinic from fragment-based approaches, of which 23 are still active, and 4 are in Phase II testing.

And not just in the clinic. According to her, tipranavir, an HIV protease inhibitor approved by the FDA in 2005, was derived from a 30 micromolar hydroxycoumarin fragment, back before people really thought in terms of fragments. This leads to the question, how many approved drugs could be considered the result of fragment-based drug discovery? I have argued that sorafenib fits the bill, having started from a relatively weak (17 micromolar) fragment-like screening hit. Any others?

BTW: Readers of Practical Fragments had previously identified 17 clinical compounds discovered through fragment-based methods. You can read that discussion here.

Hopping to selective nNOS inhibitors

Richard Silverman, the discoverer of pregabalin, has published a trifecta of papers describing the use of his “fragment hopping”strategy to discover selective, potent, and pharmacologically active inhibitors of neuronal nitric oxide synthase (nNOS).

nNOS is itself part of a triad of closely related enzymes: nNOS, iNOS, and eNOS. All synthesize the radical signaling molecule NO from arginine, but their tissue localizations and functions differ considerably. Both nNOS and iNOS have been pursued as drug targets, with nNOS implicated in a variety of diseases of the central nervous system. However, as eNOS is involved in maintaining blood pressure, identifying inhibitors selective for the desired NOS is essential. Doing so is difficult because all three enzymes share very similar active sites: of the 18 amino acids close to the substrate binding site, 16 are identical, and one of the two residues that vary has its side chain facing away from the substrate binding site.

The Silverman group has been working on selective nNOS inhibitors for over a decade, and succeeded in generating remarkably selective inhibitors, such as the compound shown on the left. But with its peptidic nature and dramatic CLogP, this compound is a long way from a drug. Enter “fragment hopping.” First, a known inhibitor is computationally deconstructed into its minimal pharmacophores; these can be as rudimentary as a positive charge or a hydrophobic spot. Next these virtual fragments are rebuilt into new virtual molecules; further computation weeds out molecules that are likely to be metabolically unstable or toxic. Finally, the best molecules are synthesized and tested. The process is computationally intensive, and I’m simplifying it greatly here, but the results, first published in J. Am. Chem. Soc. last year, are impressive: the dipeptide was transformed into a smaller, more drug-like molecule (center in figure), with increased ligand efficiency. It also retained selectivity over iNOS and eNOS.



In the latest issue of J. Med. Chem., Silverman and colleagues report using the technique again, this time to not only improve potency, but to improve the drug-like properties as well. The resulting molecule (right in figure) still maintains good selectivity, but now also boasts a respectable CLogP. Consistent with this, the molecule shows efficacy in a rabbit model of cerebral palsy. For a great review summarizing the long march to these compounds, check out this just released Acc. Chem. Res. paper.

What I really like about this work is that the researchers use fragment-based methods to actually improve the pharmaceutical properties of their molecules. Much of the focus of FBDD has been in discovery of early leads; these papers show that the approach can be useful downstream as well.

And finally, we can’t let today pass without sending out a Happy 200th Birthday to Charles Darwin (as well as Abraham Lincoln). As Teddy noted in an earlier post, “it’s evolution baby.”

Updated: Fragment Events in 2009

Here’s an updated schedule of known fragment events this year. Some of these have been previously discussed in more detail (here, and here) and are just highlighted briefly below.

February 24 and 25-27: CHI Molecular Medicine Tri-Conference, San Francisco, CA and FBDD short course

February 26: The New York Academy of Sciences is holding a symposium in New York City on “Molecular Diversity in Chemical Biology and Drug Discovery”, at which I’ll be giving a general talk on FBDD. Please come and introduce yourself!

March 4-5: Royal Society of Chemistry’s Fragments 2009, Alderley Park, UK

March 22-26: A full one and a half day session on “Library Design, Search Methods and Applications of Fragment-based Drug Design” is being held at the 237th American Chemical Society National Meeting and Exposition, in Salt Lake City, Utah. There are also a number of fragment-themed talks and posters scattered throughout the conference. ACS meetings are massive, sprawling affairs, but there’s always plenty of great science on tap.

April 7-8: CHI’s Fragment-Based Techniques, San Diego

September 21-23: FBLD 2009, York, UK

Know of anything else? Let us know and we’ll get the word out!

It's Evolution Baby

So, after Pfizer announces it acquisition of Wyeth the rumors start to fly. BMS is the winner of the who's next poll at Fiercebiotech...could this by why?

So, it appears likely that Sanofi-Aventis is going to buy BMS creating the world's larger-est pharmaceutical company. Like a senator once said, a billion here a billion there and soon you are talking about real money. Speculation is rampant that Pfizer would not go gently into that good night, of being #2. So, are more deals in the offing?

This is the evolution of the business we live in. If we are lucky, some of us will actually have a job in the future DynaMegaUltiCorp.

Ligand Efficiency (Redux Again and Over...)

There is an excellent recap of the latest literature on ligand efficiency at our friends' place. I read the Bembenek paper, several times, and something inherently bother me about it.
This is what bothers me. An empirically derived weighting function. To me, ligand efficiency makes sense from a physical standpoint. It's a value that measure how well every atom contributes overall to the binding. It makes sense to me that bigger molecules are worse at using their atoms.
This scaling function makes no physical sense to me. Somebody please explain to me (and admittedly I maybe totally miss the point), but please explain why Fit Quality is a better measure than LE from a physical standpoint of the origin of the measures.

Fragments in the Clinic: AT9283

Returning to the discussion of fragment-derived compounds that have made it into the clinic, researchers at Astex have published a nice account of the discovery of AT9283, an Aurora kinase inhibitor, in the latest issue of J. Med. Chem. The compound is in phase I testing for the treatment of solid tumors and in phase I/II testing for hematological malignancies.

While pursuing CDK inhibitors, an effort that yielded the clinical compound AT7519 (as highlighted in August last year), Astex researchers discovered that some of their pyrazole-benzimidazoles were potent and highly ligand-efficient Aurora A inhibitors. This illustrates that Nobel laureate James Black’s famous dictum, “the most fruitful basis of the discovery of a new drug is to start with an old drug,” applies to fragments as well – especially when going after kinases.



Crystallography revealed the binding modes of Compounds 5 and 7 (above) to Aurora A, and structure based design suggested adding a morpholine group to improve potency (as well as solubility). This did improve cell potency, but the resulting molecules exhibited very high plasma protein binding. A further series of structure-guided SAR studies succeeded in replacing the phenyl amide with a cyclopropyl urea, resulting in the highly potent and less lipophilic AT9283. This molecule inhibits both Aurora A and B and shows low nanomolar cellular activity consistent with inhibition of Aurora B. It also shows a clean CYP profile, good solubility, and exhibits significant tumor growth inhibition in mouse xenograft models.

Perhaps unsurprisingly given the molecule’s origins, AT9283 hits a number of other kinases too. Some of these, such as JAK2, Flt-3, and the Abl T315I mutant, are attractive cancer targets in their own right. Indeed, the fact that the molecule binds exclusively in the ATP-binding pocket allows it to inhibit kinases, such as Abl(T315I), that are resistant to many adaptive-pocket binding inhibitors such as imatinib. However, the molecule also hits more than 20 other kinases with similar potency, which could lead to off-target side effects. That said, specificity may not be everything it was once thought to be: sales of sunitinib, probably the most non-selective of approved kinase inhibitors, were $627 million for the first nine months of 2008. There is a raging debate in the kinase field over the importance of specificity. It is a debate that only more data will resolve, and AT9283 represents an attractive data point.

The Big Get Bigger

In case you missed it, Pfizer, the 800 pound Gorilla of Big Pharma, just ate Wyeth. I can tell you in the little town of Collegeville, where Wyeth has a site, there is immediate concern, not just about friends and neighbors, but about the town in general. (Although, GSK also has a site here, but still 8000 jobs are probably gone.)

What does it mean for FBDD? Wyeth has an active group in Boston and Pfizer has one in San Diego. I think there are also groups scattered at other sites (Groton ?).

Here are the key 'grafs:

The deal came as New York-based Pfizer set out a full house of issues: a 90 percent drop in income, a hefty charge to end an investigation, a severe cut in its dividend, a shockingly low profit forecast for 2009 and 8,000 job cuts starting immediately.

That's all on top of the colossal problem triggering this deal: the expected loss of $13 billion a year in revenue for cholesterol fighter Lipitor starting in November 2011, when it gets generic competition.

Pfizer also plans by 2011 to cut about 8,190 jobs, 10 percent of its workforce, as part of what it expects will be a staff reduction totaling 15 percent of the combined companies' workers -- implying a total job loss of almost 20,000.

That's a lot of jobs lost, a lot of them will be R&D. I can't imagine that Pfizer will want more than one FBDD group when many companies have zero. I think we will see many colleagues out of a job, fragment and non-fragment.


There are >48,000 hits for Pfizer wyeth merger as of 9pm EST. There is lots of excellent analysis. I wpn't try to duplicate the efforts of others much better at that than I.

Golden discoveries or numerology?

Masaya Orita and colleagues from Astellas Pharmaceuticals have published a thought-provoking paper in Drug Discovery Today (in press). In it, they describe two new measurements based on the golden ratio.

As mathematicians, art historians, and readers of The Da Vinci Code know, the golden ratio, or phi, is an irrational number whose first ten digits are 1.618033988. Phi describes the relationship between two numbers, such as 6765 and 4181, in which the ratio of the sum of the numbers to the larger number is equal to the ratio of the larger number to the smaller number. It pops up in many unexpected places, though, like Elvis, many of these sightings are disputed. Now it may have made (two!) appearances in the world of fragment-based drug discovery.

The authors examined 30 examples of fragment-based ligand discovery in which the final compound had an affinity better than 100 nM and a MW less than 600 while the starting fragment had an affinity greater than 1 micromolar. They found that the average number of heavy (non-hydrogen) atoms of the final compound was 28.933, the average number of non-hydrogen atoms of the fragment was 17.833, and thus 11.1 heavy atoms were grown or added to the fragment during optimization. 28.933 / 17.833 is approximately equal to 17.833 / 11.1, which is approximately equal to phi, the golden ratio.

The authors suggest that, if a protein target has known inhibitors with N heavy atoms, a fragment library might be more likely to produce hits if it contains compounds that have N/phi heavy atoms. I’m not sure this is the best strategy. It seems that, regardless of the target, one will want to keep the final molecular weight low, and thus a “Rule of 3” approach is probably the best bet (which, as the authors note, is related by phi to the “Rule of 5”). That said, perhaps it is worth screening larger fragments for particularly intractable targets such as protein-protein interactions, which seem to require larger ligands.

The second observation of phi is based on a reanalysis of Kuntz’s seminal “Maximal affinity of ligands”, which includes binding data for more than 150 ligand-receptor interactions. After removing heavy metals and other non-drug like ligands, and plotting ligand efficiency vs heavy atoms for the strongest-binding ligands, Orita and colleagues found that, as the number of heavy atoms doubled, the maximal ligand efficiency decreased by a factor of phi. From this they derived a new measurement:

%LE = (LE / maxLE)*100
Where maxLE = phi^log2(10/HA)

This measurement is intended to give a sense of how closely any ligand with a certain number of heavy atoms approaches the maximum ligand efficiency achievable for a ligand with the same number of heavy atoms.

The paper is a fun read (don’t be put off by the equations!), but will the observations of phi hold up to further scrutiny? And will the new indices be useful? The authors are appropriately circumspect:

Why does the Golden Ratio appear in FBDD? This might be an artefact caused by human minds (medicinal chemists), to whom such a ratio is attractive. It is expected that arguments about the existence and usefulness of the Golden Ratio in the field of drug discovery will be advanced in future.

What do you think? Are these demonstrations of patterns in medicinal chemistry, or of pattern-finding instincts in medicinal chemists?

Ligand efficiency for antibiotics

Back in October of last year we highlighted a paper in Science that disclosed a new antibiotic targeting the bacterial protein FtsZ. The compound was derived through fragment-based techniques, though at the time no details were provided. A new paper in BMCL now provides some of the early medicinal chemistry, and also introduces an interesting new tool for evaluating antibiotics.

As mentioned in the Science paper, the researchers (led by Prolysis but with a number of contributors from Evotec and Key Organics) started with the fragment-like (MW = 151, 11 heavy atoms) 3-methoxybenzamide. An initial survey of “SAR by catalog” soon moved to the synthesis of analogs that could be assembled in up to four steps from commercially available compounds. This study found that the amide was essential, and only limited substitutions around the aromatic ring were tolerated. Turning to the alkoxy group, the authors took the classic “methyl, ethyl, butyl” approach, but kept going all the way to dodecyl. Intriguingly, a nonyloxy substituent proved to be optimal, better than either 8 or 10 carbon chains. Adding two fluorine atoms to the aromatic ring improved the potency further. Although the paper does not describe the final push to PC190723, the authors do describe the desire to replace the long alkyl chain and its likely attendant problems.



The paper also defines an interesting variation of ligand efficiency:

Antibacterial efficiency = -ln (MIC) / N, where
MIC = minimum inhibitory concentration (mg/ml) and
N = non-hydrogen atoms

Although the metric has a few quirks (for example, low-efficiency compounds can actually have negative numbers), “good” values correspond roughly to good LE values; clinically approved low molecular weight antibiotics have antibacterial efficiencies in the 0.26-0.32 mg/ml/atom range.

So for all you folks working on antibiotics, not only are fragments a viable starting point, you now have a new way to evaluate progress.

Fragments in the Clinic: Indeglitazar

Following up on the discussion of fragment-derived compounds that have made it into the clinic, the first 2009 issue of PNAS describes the discovery of indeglitazar, which I believe is the USAN name of Plexxikon’s PLX-204/PPM-204. Indeglitazar is a pan-agonist of the peroxisome proliferator-activated receptors (PPARs), and has been in clinical trials for treatment of type 2 diabetes.

Plexxikon’s version of fragment-based screening, “scaffold-based discovery,” entails screening several thousand small to medium sized fragments (150-350 Da) in a biochemical assay, followed by crystallographic analysis of active molecules. In the current case, the researchers screened their collection against PPAR alpha, gamma, and delta, looking for molecules that activated two or more. After the primary screen, 170 molecules were characterized crystallographically, and about a quarter produced at least one structure. The substituted indole fragment (below) showed very weak activity, but bound snugly in a large pocket with its NH positioned toward a second pocket. Structure-guided design led to the more potent phenyl sulfonamide shown in the middle of the figure, and synthesis of just 20 additional compounds resulted in indeglitazar, which activates PPARs alpha, gamma, and delta. Ligand efficiency remained fairly constant throughout optimization.



Indeglitazar is a full agonist of PPAR alpha but only a partial agonist of PPAR gamma and delta; this may provide a better side effect profile than full activators. The molecule shows impressive pharmaceutical properties (high oral bioavailability, long half-life, etc.) as well as promising activity in mouse and rat models of diabetes (lower blood glucose, insulin, total cholesterol, triglycerides, free fatty acids, etc.). In contrast to other PPAR agonists, which sometimes cause weight gain, indeglitazar also caused weight loss in rodent and primate models; the authors suggest this could be because it affects all three PPARs.

Although indeglitazar was advanced to phase 2 trials in collaboration with Wyeth, increasing concerns over the potential side effects of PPAR agonists have caused Wyeth to discontinue development of this compound for diabetes, and as of November of 2008 the molecule was available for licensing.

Nonetheless, this is an impressive story, and appears to be the first example of using fragment-based methods to discover an agonist, as opposed to an inhibitor.

Fragments in the Clinic

Jeff Albert posted an interesting topic in the LinkedIn FBDD group's discussion section.
What is the current status of FBDD based drugs in the clinic.

Justin Bower from AZ posted:

ABT 263 (Phase II Bcl-2/Bcl-xl inhibitor) Abbott
ABT 869 (VEGF & PDGFR Phase I) Abbott
SGX-523 (Met Phase I) SGX (No Longer in Clinic, per comments)
SGX-393 (Bcr-Abl) SGX
AT-7519 (CDK1, CDK2 Phase I) Astex
VER-52296 or NVP-AUY-922 (hsp90, Phase I/II) Vernalis plus another in Phase I

Gianni Chessari, from Astex, noted this list (from a review coming out soon-ish?), with repeats removed:

AT9283 Astex Aurora Phase 2
LY-517717 Lilly/Protherics FXa Phase 2
PLX-204 Plexxikon PPAR agonist Phase 2

ABT-518 Abbott MMP-2 & 9 Phase 1
AT13387 Astex HSP90 Phase 1
IC-776 Lilly/ICOS LFA-1 Phase 1
PLX-4032 Plexxikon B-RafV600E Phase 1
PLX-5568 Plexxikon Kinase Inhibitor Phase 1
SNS-314 Sunesis Aurora Phase 1
LP-261 Locus Tubulin Phase 1
DG051 deCODE LFA4H Phase 1

So, what's missing? I would also be curious as to how these projects progressed.

Update: I have removed duplicates from the two lists. One (SGX-523) has fallen out of the clinic (per comments).

SGX does JAK-2

2008 has been an interesting year. The drug-discovery industry has shrunk dramatically in market capitalization, as well as, I suspect, in the number of companies. One of the pioneers of biotech fragment-based drug discovery, SGX Pharmaceuticals, was acquired by Lilly for $64 million in August; hopefully the fragment-based know-how will percolate throughout Lilly. I thought I’d end this year by highlighting a recent communication from SGX published in the first 2009 issue of Bioorganic and Medicinal Chemistry Letters. The paper was accepted on 18 August, two days before the merger with Lilly was completed.



SGX relied heavily on crystallographic discovery of fragments, and their efforts towards inhibitors of JAK-2, a protein tyrosine kinase target for myloproliferative disorders, began by crystallizing the protein and performing fragment-soaking experiments. A bromoaminoindazole fragment with a mid-micromolar IC50 and high ligand efficiency was found to bind to the hinge region of the kinase. Examination of the crystal structure revealed a hydrophobic groove nearby, and replacement of the bromine by a phenyl group boosted the affinity by a factor of 25. Further elaboration of the phenyl group improved the IC50 to 78 nM, more than 500-fold better than the initial fragment. The molecule also exhibited respectable (38-fold) selectivity over JAK-3. Although ligand efficiency fell throughout the optimization process, it remained high; the final molecule remains relatively small and does not appear to violate Lipinski’s Rule of Five. There is no mention of cell activity or other pharmaceutical properties, but the authors do promise future publications.

In closing out this year, we would like to thank everyone for reading, and especially for commenting. Please pass along any fragment news or events and we will get the word out. May you all have a happy and productive 2009!

50% ain’t half-bad

In the world of fragment-based ligand discovery, researchers hope that two fragments, when linked together, will behave at least additively: the free energies of binding for each fragment will sum together, with a multiplicative effect on affinity. In ideal cases, linked fragments will behave synergistically (see for example the post from 18 August, below). But all too often, linking two fragments produces disruptive behavior, and the resulting molecule actually binds less tightly than would be predicted based on the binding energies of the individual fragments. This occurs not just when linking fragments, but in fragment merging and growing as well. Can such phenomena be modeled?

The mathematical groundwork was described more than forty years ago by Spencer Free and James Wilson at the old Smith Kline and French company, and came to be known as a Free-Wilson analysis. In a nice update of this work, Julen Oyarzabal and co-workers have applied this technique to the screening results of eight libraries consisting of several hundred compounds total. The molecules belong to five diverse chemical scaffolds (shown), and were tested against a variety of different targets, including a kinase, GPCRs, ion channels, and P450s.



For each library tested against each target, the authors asked whether the binding contribution due to a substituent Rx was additive, partially additive, or non-additive with the binding contribution of a substituent Ry. The mathematics get pretty intense, and the paper goes far beyond what I can summarize in a blog post, but the main conclusion is surprisingly encouraging: roughly half of all the data sets (10 of 19) show clear additive behavior, while another quarter (5 of 19) show partially additive effects. Only 4 data sets show non-additive behavior.

In many fields, a 50% success rate wouldn’t look too impressive, but in medicinal chemistry (in fact in much of chemistry in general), half-right sounds pretty good. The authors don’t further divide the non-additive data sets into sub-additive versus super-additive categories. In other words, the non-additive effects could well be due to synergy, the quality those of us pursuing FBLD ardently desire. But even if synergy is elusive, the paper suggests that you’ve got a better than even shot of producing a whole that is at least equal to the sum of its parts.

Smacks of SMAC

Maurizio Pellecchia’s lab at the Burnham Institute has been one of the most active academic groups using fragment-based ligand discovery, and their recent paper in J. Med. Chem. describes an NMR-based approach to discover small-molecule mimetics of SMAC. The four N-terminal amino acids of SMAC bind to the protein XIAP, thereby blocking its interaction with caspase-9 and allowing apoptosis to proceed. A small-molecule mimic of SMAC could thus be useful as a chemical probe to better understand the biology of apoptosis, and, ultimately, could be useful as a cancer therapeutic.

The researchers started with the alanine “fragment” of the tetrapeptide Ala-Val-Pro-Ile (AVPI) and generated a virtual library of nearly 1400 alanine-containing derivatives. Molecular modeling narrowed this down to 15 which were then actually synthesized and tested by NMR to assess their binding affinity to a domain of XIAP; BI-75A1 was found to be a weak binder. Molecular modeling suggested that this new fragment (with a molecular weight just under 300) could in turn be “grown” to improve affinity, and after roughly 900 compounds were docked, 28 were then synthesized and tested. Of these, the most potent turned out to be BI-75D2, with a low micromolar dissociation constant in both NMR and isothermal titration calorimetry assays.



BI-75D2 exhibited improved stability in human plasma and S9 fraction compared to the starting peptide AVPI, as well as increased permeability. BI-75D2 also showed modest (16 micromolar) activity in a cell-based apoptosis induction assay, in contrast to the (inactive) AVPI peptide. Further biological experiments support the hypothesis that the small molecule induces apoptosis by binding to XIAP.

From a drug perspective, BI-75D2 still has a long way to go: it is a relatively weak binder, has a molecular weight greater than 500 Daltons, and contains several structural features that make a medicinal chemist squirm and a toxicologist squeal. Moreover, BI-75D2 has a fairly low ligand efficiency (LE), and this actually got worse as the affinity was improved. Nonetheless, as a chemical probe it may have value. It is also a demonstration of how fragment-inspired techniques can be used to attain novel molecules in an academic setting.

Great Discussion

Those of who didn't read this link have missed a fabulous discussion buried in the comments.

Mekie started by asking (for a school paper) how widely FBDD is used.

Dan said widely. However, the current economic situation is seeing early technologies (those farthest from making money, like FBDD) getting axed. Exactly what Sunesis did :-(

Mekie followed up with the obvious question. Is it he cost of the biophysical techniques, such as X-ray/NMR/SPR that is the big problem. Would a cheaper technique be better

I jumped in with both feet and unafraid to piss anyone off by saying, "Nope. It's the chemist's hubris."

Then Dan, being the voice of reason, said it is more pragmatism over hubris. Too often weak hits ended up being complete crap and we are paying for that.

Tony G. joined in and said SPR may be the savior of FBDD (highly paraphrased. Go read his comments, quite cogent).

Then Pete joined the party and FBDD can negate the huge advantage in chemical space that Big Pharma has over small companies. He also agreed with Dan and expanded in that FBDD has not really been shown with membrane targets (which are only 50% of all the targets).
My comment about this is, the natural ligands are already fragments (Count the number of heavy atoms in serotonin.) He also says you need structural data and that is not forthcoming for membrane proteins. Hogwash says I. But we can debate that at a later time.

Finally NMR-soul pointed out that FBDD needs an early committment of resources when the chance of failure is the highest.

These were some excellent comments, well worth going in and reading. I think everyone would agree that FBDD practitioners (and can we come up with a cool name already) are also to blame for overselling what FBDD can deliver (I call this the NMR effect for obvious reasons.)

New FBDD Literature Resource

A blog devoted to tracking literature related to fragment-based drug discovery has recently been launched by Peter Kenny. It sorts papers into various categories (X-ray crystallography, NMR, FBDD theory, etc.) and should be a great resource. Coming soon: DOI links to all of the references!