Fragments in cells

A couple months ago I considered writing an April Fools’ post on screening fragments in vivo. A recent paper in J. Med. Chem. reports something similar, only it’s no joke.

Alexander Shekhtman and colleagues at SUNY Albany have developed a method they call “screening of small molecule interactor library by using in-cell NMR”, or SMILI-NMR. The process starts by overexpressing two proteins within cells (E. coli, in this case). If the proteins are sequentially expressed, one of them can be selectively labeled with NMR-active isotopes. To test their system, the researchers overexpressed the model proteins FKBP and FRB. These proteins interact only weakly by themselves, but in the presence of the small molecule rapamycin they form a high affinity complex. By performing NMR on the cells, the researchers could observe changes in NMR peaks corresponding to formation of the ternary complex inside the cells when rapamycin was added. They could also do competition studies: adding the small molecule ascomycin to this complex causes a change in the NMR peaks corresponding to the rapamycin being competed away by the ascomycin.

The next step was to look for new molecules that would modulate the interaction between FKBP and FRB, and the researchers chose a library of 289 dipeptides, which are actively transported into cells. The dipeptides were mostly fragment-sized, ranging from a low molecular weight of 132 (Gly-Gly) to a high of 390 (Trp-Trp). The dipeptides were screened in pools (organized in a matrix) and then deconvoluted to identify the most active molecules. Interestingly, none of the molecules caused discrete changes to the NMR spectra as observed with rapamycin or ascomycin, but several caused some of the NMR peaks to disappear and the remaining peaks to broaden dramatically. The most potent compound was Ala-Glu (MW 218), which caused this phenomenon at 5 mM concentration. The authors interpret this effect as being caused by the formation of a large complex consisting of many molecules of FKBP, FRB, and Ala-Glu. Interestingly, although ascomycin could reverse the effect of Ala-Glu, rapamycin could not.

The dipeptide Ala-Glu also behaved similarly to rapamycin in yeast cells: both molecules prevented growth by yeast expressing FKBP, while having no effect on yeast lacking FKBP. This was attributed to both molecules facilitating complex formation between FKBP and FRB within yeast.

The Ala-Glu “fragment” has some issues (ClogP = -4, for example); it would be interesting to see how some of the original FKBP fragments discovered at Abbott behave in this assay. And although not everyone has access to a 700 MHz NMR with a cryoprobe, this is an intriguing approach for studying protein-protein interactions in a very biologically relevant milieu.

Fragments of the future - part 2 (The intersection of chemical and biological space)

In a previous post about heterocycles that appear chemically feasible but have not been reported, we wondered whether these molecules would show biological activity. The structure of biologically relevant chemical space – that fraction of possible molecules that will exhibit some biological effect – is of great interest, but as yet unknown. Brian Shoichet and coworkers at UCSF have just published a thought-provoking analysis in Nature Chemical Biology that is also relevant to developing new fragment libraries. 

The researchers ask why it is that HTS collections of a million or so compounds, vanishingly small in comparison to the roughly 1,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000 possible small drug-sized molecules, nonetheless so often succeed in identifying hits. A lovely paper by Tobias Fink and Jean-Louis Reymond had previously computationally enumerated all possible compounds with up to 11 C, N, O, and F atoms. Of these 26,429,328 molecules, 25,810 are commercially available. 

Shoichet and colleagues compared the structures of these compounds with the structures of metabolites and natural products (all of which have by definition been processed by at least one protein) and found that the commercially available compounds were much more similar to natural products and metabolites than were non-commercially available compounds. Indeed, the more similar a molecule is to a known natural product or metabolite, the more likely that it is available for purchase; 2918 of the commercially available compounds are in fact natural products or metabolites. 

The bias also increases exponentially with molecular size: a random 11-atom commercial compound is almost 1000-times more likely to resemble a natural product or metabolite than is a non-commercially available molecule, whereas the bias is only about 2-fold for 6-atom molecules. Similar results were observed with other libraries. 

The authors conclude that: A major reason why the screening of synthetic compounds ever finds notable hits is that our libraries are biased toward the sort of molecules that proteins have evolved to recognize.  

This resemblance is reasonable. After all, most commercially available compounds are ultimately derived from naturally occurring starting materials, so their similarity to natural products isn’t surprising. Moreover, historically much of chemistry was devoted to natural product synthesis, so many of the intermediates built up over the years resemble natural products. And of course, once you learn how to do chemistry on one moiety, you will tend to stick with it unless you have a good reason to do otherwise; each heterocycle behaves (often frustratingly) differently, so if a natural-product-like molecule does the job, why look for trouble? 

But does this “biogenic bias” mean that the rest of chemical space is a biological desert? Not necessarily. I can imagine at least two alternative models of chemical-biological diversity space. 

Let’s call one model “lamp posts in dark fields.” Consider a vast field of some crop that can only be harvested by night. There are lights scattered haphazardly throughout the field. One might expect that the crops immediately under the lamp posts would be harvested more intensively than crops in darker parts of the field, even if other areas are equally productive. In this scenario, the lamp posts reveal natural products and similar molecules, but much – or even most – of (unlit) chemical space may also be biologically active, it just hasn’t been sampled yet. 

Another possibility is the “oil-field model.” As we are all too aware, petroleum is distributed very unevenly across the globe. In some areas, such as Texas, oil was easy to find and easy to extract. In others, such as the deep ocean or the high arctic, oil is harder to find and more technically demanding to access. In this scenario, there are vast pockets of chemical space that are relevant to biology, they just haven’t been identified (let alone accessed) yet. 

These are fun, speculative questions, but the paper provides some practical data. Specifically, 83% of core ring scaffolds found in natural products are absent from commercial libraries. In fragment or lead-sized molecules of MW < 350 with less than three stereocenters, 1891 rings scaffolds found in natural products are not commercially available. These could be useful additions to fragment libraries, and the paper lists 18 examples. 

In fact, at least one company, deCODE, is explicitly enriching its fragment collection with molecules based on natural products and metabolites. This might be a good strategy. After all, even if the “lamp posts in dark fields” model is correct, there are plenty of brightly illuminated, unharvested chemotypes. At least for now, picking these may be more productive than venturing into the twilight-zone of uncharted chemical space.

Hidden Talent Pool

I have a question for the followes/readers here. Is there a hidden talent pool of recent Ph.Ds who have training in FBDD and can immediately walk into a pharmaceutical company? I am aware of two companies that had openings for FBDD people. Both companies wanted only freshly minted Ph.Ds or just post-doctoral experience. There is a big and deep (and obviously more expensive) pool of FBDD out there who would jump for these jobs.

I was also under the impression that industrial post-docs were largely a thing of the past. So, two questions: 1. are there academic programs/labs who are specifically training NMR-FBDD people, and more in general FBDD practitioners at all? 2. If not, are jobs like these a way for management to dip their toe in the water without actually resourcing FBDD efforts?

Fragments of the future

We recently provided a list of suppliers of commercial fragment libraries. A problem with buying compounds from these sources, of course, is that all your competitors can buy the same compounds. And while talented medicinal chemists are adept at turning common fragments into novel clinical candidates, it’s awfully nice to start with fresh fragments (see here for examples of both).

Researchers at UCB Celltech have recently taken this to an interesting extreme: they’ve computationally enumerated all neutral mono- and bicyclic 5 and 6 membered heteroaromatic rings containing carbon, nitrogen, oxygen, sulfur, and hydrogen. The resulting VEHICLe (virtual exploratory heterocylic library) is a set of 24,847 ring systems, of which only 1701 have been reported.

Of course, as the authors note, many of the remaining molecules “are outlandish and would obviously be either very difficult or impossible to make.” To address this, they used a machine learning approach to gauge synthetic tractability. This resulted in over 3000 molecules, some of which look quite reasonable:



Interestingly, the researchers estimate that only 5 to 10 of these heterocycles are being made each year, which leaves hundreds of virgin synthetic targets.

Are these a rich source of new fragments? Or, as the authors also speculate, do many of these lie outside biological activity space?

Size Doesn't Matter...Complexity Does...or does it?

With 16 days left to vote (Use you franchise!!!) 17 of 20 respondents have said that FBDD is integrated in the hit finding stage at their companies. WOW! and Awesome!
Lorenzo Williams posted a discussion topic on one of the LinkedIn groups (I of course forget which one) asking how many chemists does your company use for going from Hit to Lead. Below are the answers he shared with me...

Aurigene 8 FTEs
Arqule 1-5FTEs
Roche up to 10-13 FTEs
Bayer 1-10 FTEs
Shanghai Medicilon 6 FTEs
Chiron/Novartis 4-6 FTEs

Of course, the proviso was that it all depends on the complexity of the project. My question to this group, since we know so many of your have integrated FBDD in the hit finding stage, is: "Are FBDD based hits resourced differently than non FBDD hits?"

Commercial fragments – part 2

Teddy recently observed that it’s not the size of your library that matters, but how you use it. But how do you get a fragment library in the first place? You can of course build one up from scratch, but it may be easier to just buy one. Last year we put out a call for sources of commercial fragments and received some good comments. There are now some new suppliers of which we’ve recently become aware, so an updated list follows.

Enamine
1190 fragments w. strict “Rule of 3”
11,717 fragment extension set

Iota Pharmaceuticals
Focused on fragment-based discovery
1500 fragments available for purchase
4000 additional fragments in collaboration with Vitas-M

Life Chemicals
22,000 fragments w. MW < 300, clogP < 3
9000 fragments with rotatable bond, PSA, HBA limits

Maybridge
30,000 fragment library (MW < 350)
1000 fragments w. “Rule of 3” and solubility > 1mM
1500 Br- and 5300 F- containing fragments

Zenobia Therapeutics
352 very small fragments (Avg. MW 155)
Verified solubility at 200 mM

Does anyone have any experience using any of these? Are there others we’re missing? Let us know or post comments – anonymously if need be!

It's Not How Big it Is, It's How You Use It.

Boys will be boys, won't they. There is some gene buried on the Y chromosome that makes them think if something works as is, the bigger you make it the more success you will have. I bring this up because as we all know, many companies are slow to pick up FBDD; it is typically the "Hail Mary" pass, so success is slow in coming, as is uptake of the method as a primary tool. But once there is success, everybody jumps on the bandwagon. So, then the "crappy" little library you had needs to be increased in size (because obviously that's why it wasn't deliver superdrugs before); thank god for the medchemists!!!

So, what is the optimal size of a fragment library.
This is a table put together by the Good Folks® at Evotec for this fabulous book, with some added data bny the Editor of said Tome. What does this show us? FBDD libraries range all over in size. They obviously know something. What do they know?
No matter your screening paradigm, fragment hits need to be confirmed by an orthogonal method. So, even though you can blow through 50-100k compounds by a biochemical screen, you are still limited by your ability to confirm the hits by NMR or SPR or whatever.
If you don't think you need orthogonal methods (and really you do?) then your fragments need to be whistle-clean, because even low level impurities screened at 1-10mM can negatively impact the results of the screen. So, you think you have 10k-50k whistle-clean compounds?
Then, comes this [Shoichet and Austin (J Med Chem. 2008 Apr 24;51(8):2502-11)]. Aggregators!!!
Egads, it's like the Vikings crashing across the North Sea. So, to filter them out, you still need an orthogonal method(s).
So, creating massive (relatively) fragment libraries because you can screen them biochemically cheaply and quickly, doesn't buy you anything, because you still need to confirm them (typically by the same methods you chose not to use in the first place).

In conclusion, it's not the size, but how you use it.

Fragment linking: too strained, too flexible, or too positive?

One of the most rewarding fragment-based outcomes is to link two fragments together and get a pop in activity, as predicted by William Jencks almost three decades ago. Unfortunately, all too frequently linking two fragments gives a less than additive boost in binding energies, and often it doesn’t work at all. A new paper from James Stivers and colleagues published in Nature Chemical Biology investigates why.

The authors had previously discovered bipartite inhibitors of the DNA repair enzyme uracil DNA glycosylase (UNG): one piece of the inhibitor was fixed as the substrate uracil, and the other piece was chosen empirically from a library of fragments; the two fragments were each attached by rigid oxime connectors to a flexible linker. A crystal structure of one of these inhibitors bound to UNG showed that the uracil fragment does indeed bind in the uracil-binding pocket, while the other fragment binds in a nearby phosphodiester-binding pocket. However, the linker exhibited an unusual kink, suggesting it might be strained. The researchers have now followed up on this observation to explore the effects of varying the linker.

Four of the molecules made and tested are shown below; these vary only in how fragments connect to the linker. Importantly, the authors were able to determine co-crystal structures of all of these molecules bound to UNG. The most potent molecule, MA1, has a (flexible) secondary amine connection to the uracil fragment and a (rigid) oxime connection to the benzoate fragment; the linker appears unstrained in the crystal structure. In contrast, although the two fragments of DO bind in the same manner as the two fragments of MA1, the linker assumes the apparently strained “kinked” conformation previously observed, and the molecule binds with a thirty-fold lower affinity. In the case of the other two molecules in this set, the uracil fragment still binds as expected, but the benzoate is either not visible in the electron density (MA2) or binds to a nearby molecule of UNG in the crystal (DA). Both of these molecules are weak inhibitors, with IC50s comparable to that of uracil connected to the linkers alone, without the benzoate fragment (700-750 micromolar).



The authors argue that the greater linker flexibility in MA1 compared to DO reduces linker strain when the two fragments assume their optimal positions. They also suggest that the effect of the linker on the tighter-interacting uracil fragment will be less pronounced than on the more “loosely interacting” benzoate fragment; uracil’s specific binding interactions are able to overcome linker strain, while the weaker benzoate requires more precise positioning. In other words, the flexible connector to the uracil and the rigid connector to the benzoate give a Goldilocks-type situation for MA1.

This is reasonable. But there may be more than strain and flexibility at work here. In particular, introducing a (positively charged) secondary amine near the benzoate may have a considerable electrostatic effect on binding. The authors consider this possibility unlikely, and provide some evidence against it, but given that this enzyme binds to negatively charged DNA, I can’t dismiss it. Although the linkers are solvent-exposed, the electrostatic surface of UNG is quite positive, and in fact the benzoate linkage is not far from a histidine residue. It would be interesting to see whether replacement of the oxime linkages with similarly uncharged ethers or methylenes has the same effects as the amines.

Still, this type of systematic analysis is a valuable experimental addition to the field of fragments. I hope someone will do high-level computational modeling on these complexes to try to further dissect the origins of the differences in affinities.

More on DOCKing fragments and sampling chemical space

A few weeks ago, we highlighted a paper from Brian Shoichet’s group at UCSF demonstrating that computational screening could successfully identify fragments binding to a protein target, and that the binding modes predicted were actually observed experimentally. A companion paper just published online in PNAS now extends these results, and also beautifully illustrates that it is possible to cover much more chemical space with fragments than with lead-like molecules.

Denise Teotico, Shoichet, and colleagues used the program DOCK 3.5.54 to screen 137,639 fragments against AmpC beta-lactamase, a bacterial protein responsible for antibiotic resistance. The protein had previously been the target of HTS and computational screens of drug-like like molecules. The computational screens had modest success rates (2-7%), but the HTS screen was a total bust: of the more than 1200 hits from the 70,000+ compound screening collection, more than 95% of these turned out to be false positives, mostly aggregators, with just a few dozen true inhibitors, all of which turned out to be covalent (irreversible).

In contrast, of the 48 high-scoring fragments that were experimentally tested, 23 had Ki values better than 10 mM, for a hit rate of 48%. The authors also assessed potential for false negatives by choosing 20 random fragments and testing these for inhibition; only one showed inhibition (with a Ki value of 3.1 mM), and this molecule had scored in the top 5% of docked fragments.

The paper presents a fascinating empirical test of the Hannian chemical complexity hypothesis. Starting with the 23 active fragments, the researchers calculated how many lead-like molecules (up to 25 non-hydrogen atoms) could contain these fragments. Of the roughly 47,000,000,000 to 430,000,000,000 possible lead-like molecules, only 675 are commercially available. By repeating this analysis with fragment-sized molecules (up to 17 non-hydrogen atoms), the size of the haystack was reduced by six orders of magnitude: only about 10,000 possible molecules contain these fragments, of which 93 are commercially available. Moreover, many of the active fragments represent unique chemotypes not previously observed in AmpC inhibitors. As the authors note:

The chances of discovering interesting chemotypes for biological targets is many orders of magnitude higher when targeting molecules in the fragment weight range than even at slightly higher size ranges.

But, as the paper asks, “are the docking predictions right for the right reasons?” The researchers solved the crystal structures of 8 fragments bound to AmpC. Four of these reproduced the docking predictions well, two were somewhat different, and two were way off. In these last two cases, the protein itself adopted different conformations than had been used in the docking studies.

Protein conformational flexibility is remarkably common, and likely to be a persistent difficulty for computational methods. Clearly, current computational methods can’t identify all possibilities, particularly with fluxional proteins. Still, especially with relatively rigid proteins, computational fragment-screening may reveal chemotypes that HTS won’t.

A notable feature of the fragments is their relatively poor ligand efficiency: with one unusual exception (a phosphinate), all of the active fragments have ligand efficiencies less than 0.3 (kcal/mol)/atom. AmpC has a large, open active site, and the authors suggest that the failure of other hit-ID methods against this target may reflect issues such as solubility.

It remains to be seen whether these fragments can be advanced to low nanomolar inhibitors, but at least fragment-screening has provided many new starting points. And the paper demonstrates, once again, that triaging a fragment set computationally can be an effective means for concentrating the needles in a haystack.

Updated Again: Fragment Events in 2009

It seems the fragment calendar was front-loaded this year, but there are still a few upcoming events.

June 8-9: GTCbio is holding its “Fourth Assay Development and Screening Technologies” conference in San Francisco, and there is one session on fragment-based screening. (Full disclosure: I’ll be speaking at that one - stop by and introduce yourself!)

June 26: Select Biosciences has a “Fragment-Based Lead Discovery Summit” in London. It’s only one day, but there are a number of great speakers.

September 21-23: Last but much-anticipated, FBLD 2009 will be held in York, UK.

Regarding previous events, RSC’s Fragments 2009 has been covered both here as well as on FBDD-Lit. There is also an excellent eBriefing of the NYAS symposium on molecular diversity that can be found here.

As always, let us know if we’ve missed anything and we’ll get the word out.

LELP fragments reach their potential

In last month’s issue of Nature Reviews Drug Discovery, György Keserü of Gedeon Richter and Gergely Makara of Merck published a thought-provoking analysis of recent trends in lead discovery. Their results illustrate the potential of fragment-based methods, but also point out the still sizable gap from current practice.

The authors assembled a database of 335 hit-lead pairs derived from high-throughput screening (HTS) that were published between 2000 and 2007. They also assembled a database of 84 non-HTS hit-lead pairs published between 2000 and February 2008, consisting of fragment-based, virtual screening, natural product, and miscellaneous examples. They then compared properties – such as potency, molecular mass, logP, logS (a calculated measure of solubility), and ligand efficiency – of the initial hits with the resulting leads.

The results for HTS hits are not pretty: the lipophilicity as assessed by logP was considerably higher on average for HTS hits than for hits from any other methods, and this only increased as the hits were progressed to leads. The same goes for (in)solubility (as measured by logS). Even more alarming, the average properties of even the hits are worse than those of a collection of 541 approved drugs.

Fragment hits start out with the lowest lipophilicity and highest predicted solubility, but during hit-to-lead optimization these properties deteriorate to the point where they are similar on average to leads derived from HTS. Also surprisingly, the ligand efficiency of fragment hits and leads are, if anything, lower than their HTS counterparts, contrary to expectations. Even the average molecular weight of fragment-derived leads is not much lower than HTS-derived leads.

So what’s going wrong? The authors point out that, at most larger companies, fragment-based approaches are often only attempted after HTS has failed, suggesting that the targets tackled by fragment-based methods may be inherently more difficult. But they also suggest that in the early stages of hit-to-lead optimization the primary measure of success is how many compounds are delivered to lead optimization, which could encourage rapid hit expansion with simple chemistries to rapidly boost potency by adding grease, leading to more hydrophobic, less soluble molecules that will ultimately struggle in the clinic.

The authors suggest a new metric, ligand-efficiency-dependent lipophilicity, or LELP, to help avoid this trap:

LELP = (log P / LE)

Since a desirable logP range is between 0 and 3, and a desirable ligand efficiency is above 0.4, one should strive for LELP values between 0 and 7.5. There are already lots of metrics out there for evaluating molecules: see, for example, discussions of %LE, antibacterial efficiency, and fit quality (also here and here). Is a new one really necessary? Perhaps, if it gets people to focus on non-lipophilic means of increasing potency.

The authors end on a positive note for fragments:

Bearing in mind the sampling of chemical space, hit properties and synthetic accessibility, we consider that fragment hits are the optimum starting points for lead discovery and optimization.

There is, however, a burden on the team transforming a fragment hit into a viable lead: it is important to focus not merely on improving potency, but on maintaining as many of the fragment-like properties that make fragments attractive starting points in the first place. Although this goes without saying, analyses like this one suggest that it still needs to be said – and heard.

Book Review on FBDD Book

There is a review just publish ASAP in JACS of the Zartler and Shapiro edited book on FBDD. Overall, it is a nice review (Thanks to Andrew and Phil). There is one error (chapters 4-11 are EIGHT chapters, not seven) and one critique that I want to address.

Although there is a paragraph in Chapter 3 covering X-ray methods, which are mentioned in the introductory chapters, it would have been nice to have an entire chapter dedicated to these methods as several groups in industry have applied them successfully.

Mike and I made a conscious choice NOT to include any chapters on X-ray. We thought that of all the methods for FBDD X-ray has been done; there was nothing new to the field that our book could contribute. The focus of this book was on practical applications and newer techniques. There are a plethora of nice reviews out there, X-ray focused companies, and three chapters entirely or mostly about using X-ray in the Jahnke and Erlanson book.

What are the feelings of others? Did we swing and miss by leaving that topic out of the book or is X-ray the "mature" FBDD method? I would argue (and did in my editorial choice) that there is little left to say about X-ray that hasn't already been said.

[Update]: Zartler and Shapiro:Amazon.com Sales Rank: #1,595,845 in Books.

Jahnke and Erlanson: Amazon.com Sales Rank: #1,238,437 in Books

Nuclear Magnetic Crystallography part II

In what can only be seens as a cosmic convergence, a second paper has appeared on NMR-X-ray hybridization. This one is a collaboration from Medivir, The University of Florence, and Bruker Biospin. This method is aimed at generating structural information for a family of related proteins (in this case MMPs). The authors argue that the cost of 13C and 15N labeling is so low that such samples should be readily available, making this method widely applicable. The thrust of their method is the use of X-filtered NOESY spectroscopy to generate distance constraints, then use Autodock to determine binding. I expect that this will get covered on our FriendBlog, the FBDD-Lit Blog, so I won't go into many details.
Instead I would like to make this a discussion of the perceived value of methods such as this to the FBDD community. I, despite being an NMR jock by trade, don't feel that labeled protein methods, give enough bang for the buck, compared to ligand-based methods. Will methods such as described Isaksson et al. change that cost-benefit analysis?
What do other people think about the value and the proper role of NMR?

Nuclear Magnetic Crystallography

There is often a competition, explicit or implied, between NMR spectrometrists and X-ray crystallographers. A new technique merges the best of both worlds

Researchers at the University of Shutka, Russia, have constructed a unique NMR spectrometer with a hole bored all the way through the magnet and probe, perpendicular to the main sample cavity. This hole allows the researchers to send an X-ray beam directly into a crystal mounted in a specially designed sample chamber, allowing them to screen for compound binding by NMR while simultaneously obtaining crystal structures. Of course, due to the solid state (crystalline) form of the protein, the researchers can’t actually detect the protein itself by NMR, but by mounting the crystal in a flow cell and testing pools of fragments, they can use target-based NMR to determine which fragments bind to the protein. Once they find a fragment that binds, they can then immediately obtain the crystal structure. The researchers are planning to bring their NMR to a synchrotron to have access to a brighter X-ray source.

Will the technique become widely accepted? If so, this could be the start of a beautiful friendship.

Fragments and kinases at Abbott

Of the fragment-derived drugs that have entered the clinic, roughly half target protein kinases. Phil Hajduk (of SAR-by-NMR fame) and Irini Akritopoulou-Zanze provide a nice overview in a recent paper of how Abbott applies fragment-based approaches to this target class.

As anyone who works in the field of kinases can attest, there’s a lot of competition: the authors state that, since 2001, more than 10,000 patents or patent applications describing protein kinase inhibitors have been published. With so many inhibitors already identified, developing novel molecules is a particular challenge. This is somewhat due to the fact that most kinase inhibitors bind at least in part to the conserved purine binding site, or hinge-region. This is a thermodynamic hot-spot, usually accounting for 40-60% of the total binding energy for fully elaborated molecules. It is straightforward to carve out fragments that bind in this site from existing molecules, as shown in the figure.


But as also shown in the figure, this approach can create complicated IP, with dozens or even hundreds of overlapping patents covering the fragments. Of course, this doesn’t mean that clever medicinal chemistry can’t navigate the IP minefield, as examples described on this site from SGX and Astex have shown.

Nonetheless, the Abbott researchers decided to steer away from this hazard. They have designed and synthesized about 50 novel hinge-binders and over 5000 more elaborated molecules, and used these in their screens against kinases as well as other targets. The results are quite interesting.

First, many of the fragments show quite a bit of selectivity, hitting only one or two kinases out of a panel of 11 different kinases. In other cases, selectivity could be achieved through subsequent optimization, though in these cases the process was more often driven empirically than by structure-based design.

Another interesting observation is that the same fragment sometimes bound to different kinases in different fashions, or changed its binding mode during elaboration. This phenomenon has been previously reported by researchers at Vernalis.

The third observation is that, while these molecules exhibited a 10-fold enrichment against 13 different kinase targets compared to the generic Abbott screening collection, they also exhibited a 3-fold enrichment for 20 non-kinase targets. The authors suggest this is due to the fact that they may be acting as adenine mimetics, but it is also consistent with the Hann model of less complex fragments being able to bind to more targets (as discussed here and here).

Of course, fragment-based methods are not the only way to identify kinase inhibitors. As the authors note, “there has been almost universal success in the design and identification of potent kinase inhibitors.” Still, this brief review provides some practical advice on how fragment-based philosophies can complement more traditional lead discovery approaches.

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!

More Fragment Events for 2009

In addition to FBLD 2009 from September 21-23 of next year, there are at least three other interesting conferences on our calendar.

First up are a few fragment events at the CHI Molecular Medicine Tri-Conference extravaganza next February in San Francisco, CA. A pre-conference course on fragment-inspired medicinal chemistry will be held on February 24, followed by several fragment-based talks on February 25 and 26 (full disclosure: Teddy and I will both be presenting at this one).

Fragments 2009, held on March 4 and 5 in Alderley Park, UK (near Manchester), is organized by the Biological and Medicinal Chemistry Sector of the Royal Society of Chemistry. There is still space for posters, with abstracts due January 5.

And on April 7 and 8, Cambridge Healthtech Institute’s Fragment-Based Techniques will be held in sunny San Diego.

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

New FBDD Literature

Cho, Y., Ioerger, T. R. & Sacchettini, J. C. (2008). Discovery of novel nitrobenzothiazole inhibitors for Mycobacterium tuberculosis ATP phosphoribosyl transferase (HisG) through virtual screening. Journal of Medicinal Chemistry 51, 5984-5992.



This paper details the use of FLEXX and GOLD to screen >500k compounds against HisG, a potential tuberculosis target. In the end, two compounds showed bacteriocidal activity.

It is interesting to see docking actually working with fragments. It has always been my impression that you can get a lot of poses out of a dock with a fragment. With this paper I am proven wrong.

N.B. The clickable link may not work for everyone.