About this Author
College chemistry, 1983
The 2002 Model
After 10 years of blogging. . .
Derek Lowe, an Arkansan by birth, got his BA from Hendrix College and his PhD in organic chemistry from Duke before spending time in Germany on a Humboldt Fellowship on his post-doc. He's worked for several major pharmaceutical companies since 1989 on drug discovery projects against schizophrenia, Alzheimer's, diabetes, osteoporosis and other diseases.
To contact Derek email him directly: email@example.com
December 13, 2013
The Danishevsky group has published their totally synthetic preparation of erythropoetin. This is a work that's been in progress for ten years now (here's the commentary piece on it), and it takes organic synthesis into realms that no one's quite experienced yet:
The ability to reach a molecule of the complexity of 1 by entirely chemical means provides convincing testimony about the growing power of organic synthesis. As a result of synergistic contributions from many laboratories, the aspirations of synthesis may now include, with some degree of realism, structures hitherto referred to as “biologics”— a term used to suggest accessibility only by biological means (isolation from plants, fungi, soil samples, corals, or microorganisms, or by recombinant expression). Formidable as these methods are for the discovery, development, and manufacturing of biologics, one can foresee increasing needs and opportunities for chemical synthesis to provide the first samples of homogeneous biologics. As to production, the experiments described above must be seen as very early days. . .
I can preach that one both ways, as the old story has it. I take the point about how synthesis can provide these things in more homogeneous form than biological methods can, and it can surely provide variations on them that biological systems aren't equipped to produce. At the same time, I might put my money on improving the biological methods rather than stretching organic synthesis to this point, at least in its present form. I see the tools of molecular biology as hugely powerful, but in need of customization, whereas organic synthesis can be as custom as you like, but can (so far) only reach this sort of territory by all-out efforts like Danishevsky's. In other words, I think that molecular biology has to improve less than organic chemistry has to get the most use out of such molecules.
That said, I think that the most impressive part of this impressive paper is the area where we have the fewest molecular biology tools: the synthesis of the polysaccharide side chains. Assembling the peptide part was clearly no springtime stroll (and if you read the paper, you find that they experienced the heartbreak of having to go back and redesign things when the initial assembly sequence failed). But polyglycan chemistry has been a long-standing problem (and one that Danishevsky himself has been addressing for years). I think that chemical synthesis really has a much better shot at being the method of choice there. And that should tell you what state the field is in, because synthesis of those things can be beastly. If someone manages to tame the enzymatic machinery that produces them, that'll be great, but for now, we have to make these things the organic chemistry way when we dare to make them at all.
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December 4, 2013
Here's some work that gets right to the heart of modern drug discovery: how are we supposed to deal with the variety of patients we're trying to treat? And the variety in the diseases themselves? And how does that correlate with our models of disease?
This new paper, a collaboration between eight institutions in the US and Europe, is itself a look at two other recent large efforts. One of these, the Cancer Genome Project, tested 138 anticancer drugs against 727 cell lines. Its authors said at the time (last year) that "By linking drug activity to the functional complexity of cancer genomes, systematic pharmacogenomic profiling in cancer cell lines provides a powerful biomarker discovery platform to guide rational cancer therapeutic strategies". The other study, the Cancer Cell Line Encyclopedia, tested 24 drugs against 1,036 cell lines. That one appeared at about the same time, and its authors said ". . .our results indicate that large, annotated cell-line collections may help to enable preclinical stratification schemata for anticancer agents. The generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of ‘personalized’ therapeutic regimens."
Well, will they? As the latest paper shows, the two earlier efforts overlap to the extent of 15 drugs, 471 cell lines, 64 genes and the expression of 12,153 genes. How well do they match up? Unfortunately, the answer is "Not too well at all". The discrepancies really come out in the drug sensitivity data. The authors tried controlling for all the variables they could think of - cell line origins, dosing protocols, assay readout technologies, methods of estimating IC50s (and/or AUCs), specific mechanistic pathways, and so on. Nothing really helped. The two studies were internally consistent, but their cross-correlation was relentlessly poor.
It gets worse. The authors tried the same sort of analysis on several drugs and cell lines themselves, and couldn't match their own data to either of the published studies. Their take on the situation:
Our analysis of these three large-scale pharmacogenomic studies points to a fundamental problem in assessment of pharmacological drug response. Although gene expression analysis has long been seen as a source of ‘noisy’ data, extensive work has led to standardized approaches to data collection and analysis and the development of robust platforms for measuring expression levels. This standardization has led to substantially higher quality, more reproducible expression data sets, and this is evident in the CCLE and CGP data where we found excellent correlation between expression profiles in cell lines profiled in both studies.
The poor correlation between drug response phenotypes is troubling and may represent a lack of standardization in experimental assays and data analysis methods. However, there may be other factors driving the discrepancy. As reported by the CGP, there was only a fair correlation (rs < 0.6) between camptothecin IC50 measurements generated at two sites using matched cell line collections and identical experimental protocols. Although this might lead to speculation that the cell lines could be the source of the observed phenotypic differences, this is highly unlikely as the gene expression profiles are well correlated between studies.
Although our analysis has been limited to common cell lines and drugs between studies, it is not unreasonable to assume that the measured pharmacogenomic response for other drugs and cell lines assayed are also questionable. Ultimately, the poor correlation in these published studies presents an obstacle to using the associated resources to build or validate predictive models of drug response. Because there is no clear concordance, predictive models of response developed using data from one study are almost guaranteed to fail when validated on data from another study, and there is no way with available data to determine which study is more accurate. This suggests that users of both data sets should be cautious in their interpretation of results derived from their analyses.
"Cautious" is one way to put it. These are the sorts of testing platforms that drug companies are using to sort out their early-stage compounds and projects, and very large amounts of time and money are riding on those decisions. What if they're gibberish? A number of warning sirens have gone off in the whole biomarker field over the last few years, and this one should be so loud that it can't be ignored. We have a lot of issues to sort out in our cell assays, and I'd advise anyone who thinks that their own data are totally solid to devote some serious thought to the possibility that they're wrong.
Here's a Nature News summary of the paper, if you don't have access. It notes that the authors of the two original studies don't necessarily agree that they conflict! I wonder if that's as much a psychological response as a statistical one. . .
+ TrackBacks (0) | Category: Biological News | Cancer | Chemical Biology | Drug Assays
November 1, 2013
Here's a paper that's just come out in JACS that's worth a look on more than one level. It describes a way to image prostate cancers in vivo by targeting the GPR receptors on the cell surfaces, which are overexpressed in these tumors. Now, this is already done, using radiolabeled bombesin peptides as ligands, but this new work brings a new dimension to the idea.
What the authors have done is targeted the cell surface with antagonists and agonists at the same time, by hooking these onto a defined molecular framework. That's poly-proline, which is both soluble and adopts a well-defined structure once it's in solution. The bombesin derivatives are attached via a click Huisgen triazole linkage, and since you can slot in an azidoproline wherever you want, this lets you vary the distance between the two peptides up and down the scale. The hope is that having both kinds of ligand going at the same time might combine their separate advantages (binding potency and uptake into the cells).
And that idea seems to work: one of the combinations (the one with about a 20A spacing between the two ligands) works noticeably better than either radiolabeled peptide alone, with greater uptake and longer half-life. I'd say that proof of concept has been achieved, and the authors are planning to extend the idea to other known cell-surface-binding oncology ligands used diagnostically and/or therapeutically. Each of these will have to be worked out empirically, since there's no way of knowing what sort of spacing will be needed, of course.
That's the second thing I wanted to emphasize about this paper. Note how quickly I ran through its basic concepts above - I hope it was intelligible, but I think that the idea (which seems well worth exploring) can be expressed pretty easily. What's striking is how quickly these sorts of things can be realized these days. We've learned more about appropriate scaffolds (one of the authors of this paper, Helma Wennemers, has put in a good amount of work on the polyproline idea). And thanks to the near-universal applicability of the "click" triazole reaction, one can assemble hybrid structures like this with a high chance of success. That's not something to take for granted - doing bespoke chemistry every time on such molecules is no fun. You find yourself getting bogged down in the details rather than getting a chance to see if the main idea is worth anything or not.
There was talk before this last Nobel season of Barry Sharpless getting a second prize for the click work. Some have said that this doesn't make sense, because the click reaction that's been used the most (azide/acetylene cycloaddition) was certainly not a new one. But did anyone else see its possibilities, or the possibilities of any such universal connector reactions? Both providing such reactions and publicizing what could be done with them have been Sharpless's contributions, and the impossible-to-keep-up-with literature using them is testimony to how much was waiting to be exploited. So how come nobody did?
+ TrackBacks (0) | Category: Cancer | Chemical Biology
September 6, 2013
Acetate is used in vivo as a starting material for all sorts of ridiculously complex natural products. So here's a neat idea: why not hijack those pathways with fluoroacetate and make fluorinated things that no one's ever seen before? That's the subject of this new paper in Science, from Michelle Chang's lab at Berkeley.
There's the complication that fluoroacetate is a well-known cellular poison, so this is going to be synthetic biology all the way. (It gets processed all the way to fluorocitrate, which is a tight enough inhibitor of aconitase to bring the whole citric acid cycle to a shuddering halt, and that's enough to do the same thing to you). There a Streptomyces species that has been found to use fluoroacetate without dying (just barely), but honestly, I think that's about it for organofluorine biology.
The paper represents a lot of painstaking work. Finding enzymes (and enzyme variants) that look like they can handle the fluorinated intermediates, expressing and purifying them, and getting them to work together ex vivo are all significant challenges. They eventually worked their way up to 6-deoxyerythronolide B synthase (DEBS), which is a natural goal since it's been the target of so much deliberate re-engineering over the years. And they've managed to produce compounds like the ones shown, which I hope are the tip of a larger fluorinated iceberg.
It turns out that you can even get away with doing this in living engineered bacteria, as long as you feed them fluoromalonate (a bit further down the chain) instead of fluoroacetate. This makes me wonder about other classes of natural products as well. Has anyone ever tried to see if terpenoids can be produced in this way? Some sort of fluorinated starting material in the mevalonate pathway, maybe? Very interesting stuff. . .
+ TrackBacks (0) | Category: Chemical Biology | Chemical News | Natural Products
August 23, 2013
We chemists have always looked at the chemical machinery of living systems with a sense of awe. A billion years of ruthless pruning (work, or die) have left us with some bizarrely efficient molecular catalysts, the enzymes that casually make and break bonds with a grace and elegance that our own techniques have trouble even approaching. The systems around DNA replication are particularly interesting, since that's one of the parts you'd expect to be under the most selection pressure (every time a cell divides, things had better work).
But we're not content with just standing around envying the polymerase chain reaction and all the rest of the machinery. Over the years, we've tried to borrow whatever we can for our own purposes - these tools are so powerful that we can't resist finding ways to do organic chemistry with them. I've got a particular weakness for these sorts of ideas myself, and I keep a large folder of papers (electronic, these days) on the subject.
So I was interested to have a reader send along this work, which I'd missed when it came out on PLOSONE. It's from Pehr Harbury's group at Stanford, and it's in the DNA-linked-small-molecule category (which I've written about, in other cases, here and here). Here's a good look at the pluses and minuses of this idea:
However, with increasing library complexity, the task of identifying useful ligands (the ‘‘needles in the haystack’’) has become increasingly difficult. In favorable cases, a bulk selection for binding to a target can enrich a ligand from non-ligands by about 1000-fold. Given a starting library of 1010 to 1015 different compounds, an enriched ligand will be present at only 1 part in 107 to 1 part in 1012. Confidently detecting such rare molecules is hard, even with the application of next-generation sequencing techniques. The problem is exacerbated when biologically-relevant selections with fold-enrichments much smaller than 1000-fold are utilized.
Ideally, it would be possible to evolve small-molecule ligands out of DNA-linked chemical libraries in exactly the same way that biopolymer ligands are evolved from nucleic acid and protein libraries. In vitro evolution techniques overcome the ‘‘needle in the haystack’’ problem because they utilize multiple rounds of selection, reproductive amplification and library re-synthesis. Repetition provides unbounded fold-enrichments, even for inherently noisy selections. However, repetition also requires populations that can self-replicate.
That it does, and that's really the Holy Grail of evolution-linked organic synthesis - being able to harness the whole process. In this sort of system, we're talking about using the DNA itself as a physical prod for chemical reactivity. That's also been a hot field, and I've written about some examples from the Liu lab at Harvard here, here, and here. But in this case, the DNA chemistry is being done with all the other enzymatic machinery in place:
The DNA brings an incipient small molecule and suitable chemical building blocks into physical proximity and induces covalent bond formation between them. In so doing, the naked DNA functions as a gene: it orchestrates the assembly of a corresponding small molecule gene product. DNA genes that program highly fit small molecules can be enriched by selection, replicated by PCR, and then re-translated into DNA-linked chemical progeny. Whereas the Lerner-Brenner style DNA-linked small-molecule libraries are sterile and can only be subjected to selective pressure over one generation, DNA-programmed libraries produce many generations of offspring suitable for breeding.
The scheme below shows how this looks. You take a wide variety of DNA sequences, and have them each attached to some small-molecule handle (like a primary amine). You then partition these out into groups by using resins that are derivatized with oligonucleotide sequences, and you plate these out into 384-well format. While the DNA end is stuck to the resin, you do chemistry on the amine end (and the resin attachment lets you get away with stuff that would normally not work if the whole DNA-attached thing had to be in solution). You put a different reacting partner in each of the 384 wells, just like in the good ol' combichem split/pool days, just with DNA as the physical separation mechanism.
In this case, the group used 240-base-pair DNA sequences, two hundred seventeen billion of them. That sentence is where you really step off the edge into molecular biology, because without its tools, generating that many different species, efficiently and in usable form, is pretty much out of the question with current technology. That's five different coding sequences, in their scheme, with 384 different ones in each of the first four (designated A through D), and ten in the last one, E. How diverse was this, really? Get ready for more molecular biology tools:
We determined the sequence of 4.6 million distinct genes from the assembled library to characterize how well it covered ‘‘genetic space’’. Ninety-seven percent of the gene sequences occurred only once (the mean sequence count was 1.03), and the most abundant gene sequence occurred one hundred times. Every possible codon was observed at each coding position. Codon usage, however, deviated significantly from an expectation of random sampling with equal probability. The codon usage histograms followed a log-normal distribution, with one standard deviation in log- likelihood corresponding to two-to-three fold differences in codon frequency. Importantly, no correlation existed between codon identities at any pair of coding positions. Thus, the likelihood of any particular gene sequence can be well approxi- mated by the product of the likelihoods of its constituent codons. Based on this approximation, 36% of all possible genes would be present at 100 copies or more in a 10 picomole aliquot of library material, 78% of the genes would be present at 10 copies or more, and 4% of the genes would be absent. A typical selection experiment (10 picomoles of starting material) would thus sample most of the attainable diversity.
The group had done something similar before with 80-codon DNA sequences, but this system has 1546, which is a different beast. But it seems to work pretty well. Control experiments showed that the hybridization specificity remained high, and that the micro/meso fluidic platform being used could return products with high yield. A test run also gave them confidence in the system: they set up a run with all the codons except one specific dropout (C37), and also prepared a "short gene", containing the C37 codon, but lacking the whole D area (200 base pairs instead of 240). When they mixed that in with the drop-out library (in a ratio of 1 to 384), and split that out onto a C-codon-attaching array of beads. They then did the chemical step, attaching one peptoid piece onto all of them except the C37 binding well - that one got biotin hydrazide instead. Running the lot of them past streptavidin took the ratio of the C37-containing ones from 1:384 to something over 35:1, an enhancement of at least 13,000-fold. (Subcloning and sequencing of 20 isolates showed they all had the C37 short gene in them, as you'd expect).
They then set up a three-step coupling of peptoid building blocks on a specific codon sequence, and this returned very good yields and specificities. (They used a fluorescein-tagged gene and digested the product with PDE1 before analyzing them at each step, which ate the DNA tags off of them to facilitate detection). The door, then, would now seem to be open:
Exploration of large chemical spaces for molecules with novel and desired activities will continue to be a useful approach in academic studies and pharmaceutical investigations. Towards this end, DNA-programmed combinatorial chemistry facilitates a more rapid and efficient search process over a larger chemical space than does conventional high-throughput screening. However, for DNA-programmed combinatorial chemistry to be widely adopted, a high-fidelity, robust and general translation system must be available. This paper demonstrates a solution to that challenge.
The parallel chemical translation process described above is flexible. The devices and procedures are modular and can be used to divide a degenerate DNA population into a number of distinct sub-pools ranging from 1 to 384 at each step. This coding capacity opens the door for a wealth of chemical options and for the inclusion of diversity elements with widely varying size, hydrophobicity, charge, rigidity, aromaticity, and heteroatom content, allowing the search for ligands in a ‘‘hypothesis-free’’ fashion. Alternatively, the capacity can be used to elaborate a variety of subtle changes to a known compound and exhaustively probe structure-activity relationships. In this case, some elements in a synthetic scheme can be diversified while others are conserved (for example, chemical elements known to have a particular structural or electrostatic constraint, modular chemical fragments that independently bind to a protein target, metal chelating functional groups, fluorophores). By facilitating the synthesis and testing of varied chemical collections, the tools and methods reported here should accelerate the application of ‘‘designer’’ small molecules to problems in basic science, industrial chemistry and medicine.
Anyone want to step through? If GSK is getting some of their DNA-coded screening to work (or at least telling us about the examples that did?), could this be a useful platform as well? Thoughts welcome in the comments.
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July 31, 2013
Evolutionary and genetic processes fascinate many organic chemists, and with good reason. They've provided us with the greatest set of chemical catalysts we know of: enzymes, which are a working example of molecular-level nanotechnology, right in front of us. A billion years of random tinkering have accomplished a great deal, but (being human) we look at the results and wonder if we couldn't do things a bit differently, with other aims in mind than "survive or die".
This has been a big field over the years, and it's getting bigger all the time. There are companies out there that will try to evolve enzymes for you (here's one of the most famous examples), and many academic labs have tried their hands at it as well. The two main routes are random mutations and structure-based directed changes - and at this point, I think it's safe to say that any successful directed-enzyme project has to take advantage of both. There can be just too many possible changes to let random mutations do all the work for you (20 to the Xth power gets out of hand pretty quickly, and that's just the natural amino acids), and we're usually not smart enough to step in and purposefully tweak things for the better every time.
Here's a new paper that illustrates why the field is so interesting, and so tricky. The team (a collaboration between the University of Washington and the ETH in Zürich) has been trying to design a better retro-aldolase enzyme, with earlier results reported here. That was already quite an advance (15,000x rate enhancement over background), but that's still nowhere near natural enzymes of this class. So they took that species as a starting point and did more random mutations around the active site, with rounds of screening in between, which is how we mere humans have to exert selection pressure. This gave a new variant with another lysine in the active site, which some aldolases have already. Further mutational rounds (error-prone PCR and DNA shuffling) and screening let to a further variant that was over 4000x faster than the original enzyme.
But when the team obtained X-ray structures of this enzyme in complex with an inhibitor, they got a surprise. The active site, which had already changed around quite a bit with the addition of that extra lysine, was now a completely different place. A new substrate-binding pocket had formed, and the new lysine was now the catalytic residue all by itself. The paper proposes that the mechanistic competition between the possible active-site residues was a key factor, and they theorize that many natural enzymes may have evolved through similar paths. But given this, there are other questions:
The dramatic changes observed during RA95 evolution naturally prompt the question of whether generation of a highly active retro-aldolase required a computational design step. Whereas productive evolutionary trajectories might have been initiated from random libraries, recent experiments with the same scaffold dem- onstrate that chemical instruction conferred by computation greatly increases the probability of identifying catalysts. Although the programmed mechanisms of other computationally designed enzymes have been generally reinforced and refined by directed evolution, the molecular acrobatics observed with RA95 attest to the functional leaps that unanticipated, innovative mutations—here, replacement of Thr83 by lysine—can initiate.
So they're not ready to turn off the software just yet. But you have to wonder - if there were some way to run the random-mutation process more quickly, and reduce the time and effort of the mutation/screening/selection loop, computational design might well end up playing a much smaller role. (See here for more thoughts on this). Enzymes are capable of things that we would never think of ourselves, and we should always give them the chance to surprise us when we can.
+ TrackBacks (0) | Category: Chemical Biology | In Silico
July 25, 2013
Ben Cravatt is talking about this work on activity-based protein profiling of serine hydrolase enzymes. That's quite a class to work on - as he says, up to 2% of all the proteins in the body fall into this group, but only half of them have had even the most cursory bit of characterization. Even among the "known" ones, most of their activities are still dark, and only 10% of them have useful pharmacological tools.
He's detailed a compound (PF-3845) that Pfizer found as a screening hit for FAAH, which although it looked benign, turned out to be a covalent inhibitor due to a reactive arylurea. Pfizer, he says, backed off when this mechanism was uncovered - they weren't ready at the time for covalency, but he says that they've loosened up since then. Studying the compound in various tissues, including the brain, showed that it was extremely selective for FAAH.
Another reactive compound, JZL184, is an inhibitor of monoacylglycerol hydrolase (MAGL). Turns out that its carbamate group also reacts with FAAH, but there's a 300-fold window in the potency. The problem is, that's not enough. In mouse models, hitting both enzymes at the same time leads to behavioral problems. Changing the leaving group to a slightly less reactive (and nonaromatic) hexafluoroisopropanol, though, made the compound selective again. I found this quite interesting - most of the time, you'd think that 300x is plenty of room, but apparently not. That doesn't make things any easier, does it?
In response to a question (from me), he says that covalency is what makes this tricky. The half-life of the brain enzymes is some 12 to 14 hours, so by the time the next once-a-day dose comes in, there's still 20 or 30% of the enzyme still shut down, and things get out of hand pretty soon. For a covalent mechanism, he recommends 2000-fold or 5000-fold. On the other hand, he says that when they've had a serine hydrolase-targeted compound, they've never seen it react out of that class (targeting cysteine residues, though, is a very different story). And the covalent mechanism gives you some unique opportunities - for example, deliberate engineering a short half-life, because that might be all you need.
+ TrackBacks (0) | Category: Chemical Biology | The Central Nervous System
Kurt Deshayes of Genentech has been speaking at the Challenges in Chemical Biology meeting, on protein-protein inhibitor work. And he's raised a number of issues that I think that we in drug discovery are going to have to deal with. For one thing, given the size of PPI clinical molecules like ABT-199, what does that tell us about what makes an orally available molecule? (And what does that tell us about what we think we know about the subject?) You'd think that many (most?) protein-protein inhibitors will be on the large side, and if you were to be doctrinaire about biophysical properties, you wouldn't go there at all. But it can be done - the question is, how often? And how do you increase your chances of success? I don't think that anyone doubts that more molecules with molecular weights of 1000 will have PK trouble than those with molecular weights of 300. So how do you lengthen the odds?
Another point he emphasized is that Genentech's work on XIAP led them to activities that they never would have guessed up front. The system, he points out, is just too complicated to make useful predictions. You have to go in an perturb it and see what happens (and small molecules are a great way to do that). I'd say that this same principle applies to most everything in biochemistry: get in and mess with the system, and let it tell you what's going on.
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Ali Tavassoli has just given a very interesting talk at the Challenges in Chemical Biology conference on his SICLOPPS method for generating huge numbers of cyclic peptides to screen for inhibitors of protein-protein interactions. I'll do a post in detail on that soon; it's one of those topics I've been wanting to tackle. His lab is applying this to a wide range of PPI systems.
But he had a neat update on another topic, as well. His group has made triazole-linked DNA sequences, and investigated how they behave in bacteria. He now reports that these things are biocompatible in mammalian cells (MCF-7).
This opens up some very interesting artificial-gene ideas, and I look forward to seeing what people can make of it. The extent to which DNA can be modified by things like triazole linkages is remarkable (see here and here for other examples). What else is possible?
+ TrackBacks (0) | Category: Chemical Biology
Kevan Shokat is now talking about his lab's work on using Drosophila models for kinase inhibitor discovery in oncology. I always like hearing about this sort of thing; very small living models have a lot of appeal for drug discovery.
You'd think that screening in fruit flies would be problematic for understanding human efficacy, but if you pick your targets carefully, you can get it to work. In Shokat's case, he's looking at a kinase called Ret, which is a target in thyroid cancer and is quite highly conserved across species. They set up a screen where active compounds would rescue a lethal phenotype (which gives you a nice high signal-to-noise), and screened about a thousand likely kinase inhibitor molecules.
Here's the paper that discusses much of what Shokat's group found. It turned out that Ret kinase inhibition alone was not the answer - closely related compounds with very similar Ret activity had totally different phenotypes in the flies. The key was realizing that some of them were hitting and missing other kinases in the pathways (specifically Raf and TOR) that could cancel out (or enhance) the effects. This was a very nice job of direct discovery of the right sort of kinase fingerprint needed for a desired effect. We need more tiny critters for screens like these.
+ TrackBacks (0) | Category: Cancer | Chemical Biology
July 24, 2013
Now Udo Opperman is talking about histone modifications, which takes us into epigenetics. Whatever it is, epigenetics seems to be a big topic at this meeting - there are several talks and many posters addressing this area.
His efforts at Oxford and the Structural Genomics Consortium are towards generating chemical tools for all the histone-modifying enzymes (methylases/demethylases, acetylases/deacetylases, and so on). That covers a lot of ground, and a number of different mechanisms. To make things harder, they're going for tens of nanomolar in potency and high selectivity - but if these compounds are going to be really useful, that's the profile that they'll need.
One of the things that's coming up as these compounds become available is that these enzymes aren't necessarily confined to histones. Why shouldn't lysines, etc., on other proteins also be targets for regulation? Studies are just getting started on this, and it could well be that there are whole signaling networks out there that we haven't really appreciated.
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I'm listening to Stuart Schreiber make his case for diversity-oriented synthesis (DOS) as a way to interrogate biochemistry. I've written about this idea a number of times here, but I'm always glad to hear the pitch right from the source.
Schreiber's team has about 100,000 compounds from DOS now, all of which are searchable at PubChem. He says that they have about 15mg of each of them in the archives, which is a pretty solid collection. They've been trying to maximize the biochemical diversity of their screening (see here and here for examples), and they're also (as noted here) building up a collection of fragments, which he says will be used for high-concentration screening.
He's also updating some efforts with the Gates Foundation to do cell-based antimalarial screening with the DOS compounds. They have 468 compounds that they're now concentrating on, and checking these against resistant strains indicates that some of them may well be working through unusual mechanisms (others, of course, are apparently hitting the known ones). He's showing structures, and they are very DOSsy indeed - macrocycles, spiro rings, chirality all over. But since these assay are done in cells, some large hoops have already been jumped through.
He's also talking about the Broad Institutes efforts to profile small-molecule behavior in numerous tumor cell lines. Here's a new public portal site on this, and there's apparently a paper accepted at Cell on it as well. They have hundreds of cell lines, from all sorts of sources, and are testing those against an "informer set" of small-molecule probes and known drugs. They're trying to make this a collection of very selective compounds, targeting a wide variety of different targets throughout the cell. There are kinase inhibitors, epigenetic compounds, and a long list of known oncology candidates, as well as many other compounds that don't hit obvious cancer targets.
They're finding out a lot of interesting things about target ID with this set. Schreiber says that this work has made him more interested in gene expression profiles than in mutations per se. Here, he says, is an example of what he's talking about. Another example is the recent report of the natural product austocystin, which seems to be activated by CYP metabolism. The Broad platform has identified CYP2J2 as the likely candidate.
There's an awful lot of work on these slides (and an awful lot of funding is apparent, too). I think that the "Cancer Therapeutics Response Portal" mentioned above is well worth checking out - I'll be rooting through it after the meeting.
+ TrackBacks (0) | Category: Cancer | Chemical Biology | Infectious Diseases
June 18, 2013
Natural products come up around here fairly often, as sources of chemical diversity and inspiration. Here's a paper that combines them with another topic (epigenetics) that's been popular around here as well, even if there's some disagreement about what the word means.
A group of Japanese researchers were looking at the natural products derived from a fungus (Chaetomium indicum). Recent work has suggested that fungi have a lot more genes/enzymes available to make such things than are commonly expressed, so in this work, the team fed the fungus an HDAC inhibitor to kick its expression profile around a bit. The paper has a few references to other examples of this technique, and it worked again here - they got a significantly larger amount of polyketide products out of the fermentation, included several that had never been described before.
There have been many attempts to rejigger the synthetic machinery in natural-product-producing organisms, ranging from changing their diet of starting materials, adding environmental stresses to their culture, all the way to manipulating their actual
genomic sequences directly. This method has the advantage of being easier than most, and the number of potential gene-expression-changing compounds is large. Histone deacetylase inhibitors alone have wide ranges of selectivity against members of the class, and then you have the reverse mechanism (histone actyltranferase), methyltransferase and demethylase inhibitors, and many more. These should be sufficient to produce weirdo compounds a-plenty.
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June 3, 2013
Here's a worthwhile paper from Donna Huryn, Lynn Resnick, and Peter Wipf on the academic contributions to chemical biology in recent years. They're not only listing what's been done, they're looking at the pluses and minuses of going after probe/tool compounds in this setting:
The academic setting provides a unique environment distinct from traditional pharmaceutical or biotechnology companies, which may foster success and long-term value of certain types of probe discovery projects while proving unsuitable for others. The ability to launch exploratory high risk and high novelty projects from both chemistry and biology perspectives, for example, testing the potential of unconventional chemotypes such as organometallic complexes, is one such distinction. Other advantages include the ability to work without overly constrained deadlines and to pursue projects that are not expected to reap commercial rewards, criteria and constraints that are common in “big pharma.” Furthermore, projects to identify tool molecules in an academic setting often benefit from access to unique and highly specialized biological assays and/or synthetic chemistry expertise that emerge from innovative basic science discoveries. Indeed, recent data show that the portfolios of academic drug discovery centers contain a larger percentage of long-term, high-risk projects compared to the pharmaceutical industry. In addition, many centers focus more strongly on orphan diseases and disorders of third world countries than commercial research organizations. In contrast, programs that might be less successful in an academic setting are those that require significant resources (personnel, equipment, and funding) that may be difficult to sustain in a university setting. Projects whose goals are not consistent with the educational mission of the university and cannot provide appropriate training and/or content for publications or theses would also be better suited for a commercial enterprise.
Well put. You have to choose carefully (just as commercial enterprises have to), but there are real opportunities to do something that's useful, interesting, and probably wouldn't be done anywhere else. The examples in this paper are sensors of reactive oxygen species, a GPR30 ligand, HSP70 ligands, an unusual CB2 agonist (among other things), and a probe of beta-amyloid.
I agree completely with the authors' conclusion - there's plenty of work for everyone:
By continuing to take advantage of the special expertise resident in university settings and the ability to pursue novel projects that may have limited commercial value, probes from academic researchers can continue to provide valuable tools for biomedical researchers. Furthermore, the current environment in the commercial drug discovery arena may lead to even greater reliance on academia for identifying suitable probe and lead structures and other tools to interrogate biological phenomena. We believe that the collaboration of chemists who apply sound chemical concepts and innovative structural design, biologists who are fully committed to mechanism of action studies, institutions that understand portfolio building and risk sharing in IP licensing, and funding mechanisms dedicated to provide resources leading to the launch of phase 1 studies will provide many future successful case studies toward novel therapeutic breakthroughs.
But it's worth remembered that bad chemical biology is as bad as anything in the business. You have the chance to be useless in two fields at once, and bore people across a whole swath of science. Getting a good probe compound is not like sitting around waiting for the dessert cart to come - there's a lot of chemistry to be done, and some biology that's going to be tricky almost by definition. The examples in this paper should spur people on to do the good stuff.
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April 18, 2013
Just as a quick example of how odd molecular recognition can be, have a look at this paper from Chemical Communications. It's not particularly remarkable, but it's a good example of what's possible. The authors used a commercial phage display library (this one, I think) to run about a billion different 12-mer peptides past the simple aromatic hydrocarbon naphthalene (immobilized on a surface via 2-napthylamine). The usual phage-library techniques (several rounds of infection into E. coli followed by more selectivity testing against bound naphthalene and against control surfaces with no ligand) gave a specific 12-mer peptide. It's HFTFPQQQPPRP, for those who'd like to make some. Note: I typo-ed that sequence the first time around, giving it only one phenylalanine, unhelpfully.
Now, an oligopeptide isn't the first thing you'd imagine being a selective binder to a simple aromatic hydrocarbon, but this one not only binds naphthalene, but it has good selectivity versus benzene (34-fold), while anthracene and pyrene weren't bound at all. From the sequence above, those of you who are peptide geeks will have already figured out roughly how it does it: the phenylalanines are pi-stacking, while the proline(s) make a beta-turn structure. Guessing that up front would still not have helped you sort through the possibilities, it's safe to say, since that still leaves you with quite a few.
But the starting phage library itself doesn't cover all that much diversity. Consider 20 amino acids at twelve positions: 4.096 times ten to the fifteenth. The commercial library covers less than one millionth of the possible oligopeptide space, and we're completely ignoring disulfide bridges. To apply the well-known description from the Hitchhiker's Guide to the Galaxy, chemical space is big. "Really big. You just won't believe how vastly, hugely, mindbogglingly big it is. . ."
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April 1, 2013
Nature Chemical Biology has an entire issue on target selection and target validation, and it looks well worth a read. I'll have more to say about some of the articles in it, but I wanted to mention a point that comes up in the introductory comment, "Stay On Target". This is the key point: "Chemical probes and drugs are fundamentally distinct entities".
A drug-company scientist's first reaction might be (as mine was) to think "That's true. The bar is higher for drugs". But the editorial goes on to say that this isn't the case, actually:
For example, multiple authors emphasize that when it comes to in-cell selectivity between on- and off-target activity, chemical probes should be held to a higher standard than drugs, as clinical responses may in fact improve from off-target activity (via polypharmacology), whereas the interpretation of biological responses to chemical probes requires the deconvolution of outcomes associated with on- and off-target activities.
They're right. A drug is defined by its effects in a living creature (I'm tempted to add "Preferably, one that is willing to pay for it"). A chemical probe, on the other hand, is defined by its specificity. It's important not to confuse the two - you can get all excited about how specific your drug candidate is, how exquisitely it hits its target, but (as we have proven over and over in this business) that means nothing if hitting that target isn't clinically meaningful. Being impressed by the specificity of a chemical probe compound, on the other hand, is entirely appropriate - but no one should think that this makes it closer to being a drug.
These concepts came up at the EMBL Chemical Biology meeting I attended last fall, and anyone doing work in the field would do well to keep them in mind. If you don't, you risk producing the worst sorts of compounds. On one end of the spectrum, you have the wonderfully selective compound that has eaten up vast amounts of money in development costs, but does nothing that anyone finds useful. And on the other end of that scale, you have so-called probe compounds that probably hit all sorts of other things, rendering any results in any system past a single purified protein suspect. Stay out of both of those mudpits if you can.
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March 27, 2013
I wrote here about DNA-barcoding of huge (massively, crazily huge) combichem libraries, a technology that apparently works, although one can think of a lot of reasons why it shouldn't. This is something that GlaxoSmithKline bought by acquiring Praecis some years ago, and there are others working in the same space.
For outsiders, the question has long been "What's come out of this work?" And there is now at least one answer, published in a place where one might not notice it: this paper in Prostaglandins and Other Lipid Mediators. It's not a journal whose contents I regularly scan. But this is a paper from GSK on a soluble epoxide hydrolase inhibitor, and therein one finds:
sEH inhibitors were identified by screening large libraries of drug-like molecules, each attached to a DNA “bar code”, utilizing DNA-encoded library technology  developed by Praecis Pharmaceuticals, now part of GlaxoSmithKline. The initial hits were then synthesized off of DNA, and hit-to-lead chemistry was carried out to identify key features of the sEH pharmacophore. The lead series were then optimized for potency at the target, selectivity and developability parameters such as aqueous solubility and oral bioavailability, resulting in GSK2256294A. . .
That's the sum of the med-chem in the article, which certainly compresses things, and I hope that we see a more complete writeup at some point from a chemistry perspective. Looking at the structure, though, this is a triaminotriazine-derived compound (as in the earlier work linked to in the first paragraph), so yes, you apparently can get interesting leads that way. How different this compound is from the screening hit is a good question, but it's noteworthy that a diaminotriazine's worth of its heritage is still present. Perhaps we'll eventually see the results of the later-generation chemistry (non-triazine).
+ TrackBacks (0) | Category: Chemical Biology | Chemical News | Drug Assays | Drug Development
March 20, 2013
Here's an ingenious use for DNA that never would have occurred to me. David Liu and co-workers have been using DNA-templated reactions for some time, though, so it's the sort of thing that would have occurred to them: using the information of a DNA sequence to make other kinds of polymers entirely.
The schematic above gives you the idea. Each substrate has a peptide nucleic acid (PNA) pentamer, which recognizes a particular DNA codon, and some sort of small-molecule monomer piece for the eventual polymer, with cleavable linkers holding these two domains together. The idea is that when these things line up on the DNA, their reactive ends will be placed in proximity to each other, setting up the bond formation in the order that you want.
Even so, they found that if you use building blocks whose ends can react with each other intramolecularly (A----B), they tend to do that as a side reaction and mess things up. So the most successful runs had an A----A type compound on one codon, with a B----B one on the next, and so on. So what chemical reactions were suitable? Amide formation didn't get very far, and reductive amination failed completely. Hydrazone and oxime formation actually worked, though, although you can tell that Liu et al. weren't too exciting about pursuing that avenue much further. But the good ol' copper-catalyzed acetylene/azide "click" reaction came through, and appears to have been the most reliable of all.
That platform was used to work out some of the other features of the system. Chain length on the individual pieces turned out not to be too big a factor (Whitesides may have been right again on this one). A nice mix-and-match experiment with various azides and acetylenes on different PNA codon recognition sequences showed that the DNA was indeed templating things the in the way that you would expect from molecular recognition. Pushing the system by putting rather densely functionalized spacers (beta-peptide sequences) in the A----A and B----B motifs also worked well, as did pushing things to make 4-, 8-, and even 16-mers. By the end, they'd produced completely defined triazole-linked beta-peptide polymers of 90 residues, with a molecular weight of 26 kD, which pushes things into the realm of biomolecular sizes.
You can, as it turns out, take a sample of such a beast (with the DNA still attached) and subject it to PCR, amplifying your template again. That's important, because it's the sort of thing you could imagine doing with a library of these things, using some sort of in vitro selection criterion for activity, and then identifying the sequence of the best one by using the attached DNA as a bar-code readout. This begins to give access to a number of large and potentially bioactive molecules that otherwise would be basically impossible to synthesize in any defined form. Getting started is not trivial, but once you get things going, it looks like you could generate a lot of unusual stuff. I look forward to seeing people take up the challenge!
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February 27, 2013
There's an interesting addendum to yesterday's post about natural product fragments. Dan Erlanson was pointing out that many of the proposed fragments were PAINS, and that prompted Jonathan Baell (author of the original PAINS paper) to leave a comment there mentioning this compound. Yep, you can buy that beast from Millipore, and it's being sold as a selective inhibitor of two particular enzymes. (Here's the original paper describing it). If it's really that selective, I will join one of those Greek monasteries where they eat raw onions and dry bread, and spend my time in atonement for ever thinking that a double nitrophenyl
Schiff base enone with an acrylamide on it might be trouble.
Honestly, guys. Do a Ben Cravatt-style experiment across a proteome with that think, and see what you get. I'm not saying that it's going to absolutely label everything it comes across, but it's surely going to stick to more than two things, and have more effects than you can ascribe to those "selective" actions.
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February 1, 2013
The short answer is "by looking for compounds that grow beta cells". That's the subject of this paper, a collaboration between Peter Schulz's group, the Novartis GNF. Schultz's group has already published on cell-based phenotypic screens in this area, where they're looking for compounds that could be useful in restoring islet function in patient with Type I diabetes.
These studies have used a rat beta-cell line (R7T1) that can be cultured, and they do good ol' phenotypic screening to look for compounds that induce proliferation (while not inducing it across the board in other cell types, of course). I'm a big fan of such approaches, but this is a good time to mention their limitations. You'll notice a couple of key words in that first sentence, namely "rat" and "cultured". Rat cells are not human cells, and cell lines that can be grown in vitro are not like primary cells from a living organism, either. If you base your entire approach this way, you run the risk of finding compounds that will, well, only work on rat cells in a dish. The key is to shift to the real thing as quickly as possible, to validate the whole idea.
That's what this paper does. The team has also developed an assay with primary human beta cells (which must be rather difficult to obtain), which are dispersed and plated. The tricky part seems to be keeping the plates from filling up with fibroblast cells, which are rather like the weeds of the cell culture world. In this case, their new lead compound (a rather leggy beast called WS-6) induced proliferation of both rat and human cells.
They took it on to an even more real-world system, mice that had been engineered to have a switchable defect in their own beta cells. Turning these animals diabetic, followed by treatment with the identified molecule (5 mpk, every other day), showed that it significantly lowered glucose levels compared to controls. And biopsies showed significantly increases beta-cell mass in the treated animals - all together, about as stringent a test as you can come up with in Type I studies.
So how does WS6 accomplish this? The paper goes further into affinity experiments with a biotinylated version of the molecule, which pulled down both the kinase IKK-epsilon and another target, Erb3 binding protein-1 (EBP1). An IKK inhibitor had no effect in the cell assay, interestingly, while siRNA experiments for EBP1 showed that knocking it down could induce proliferation. Doing both at the same time, though, had the most robust effect of all. The connection looks pretty solid.
Now, is WS6 a drug? Not at all - here's the conclusion of the paper:
In summary, we have identified a novel small molecule capable of inducing proliferation of pancreatic β cells. WS6 is among a few agents reported to cause proliferation of β cells in vitro or in vivo. While the extensive medicinal chemistry that would be required to improve the selectivity, efficacy, and tolerability of WS6 is beyond the scope of this work, further optimization of WS6 may lead to an agent capable of promoting β cell regeneration that could ultimately be a key component of combinatorial therapy for this complex disease.
Exactly so. This is excellent, high-quality academic research, and just the sort of thing I love to see. It tells us useful, actionable things that we didn't know about an important disease area, and it opens the door for a real drug discovery effort. You can't ask for more than that.
+ TrackBacks (0) | Category: Chemical Biology | Diabetes and Obesity | Drug Assays
January 17, 2013
Here's a recent paper in J. Med. Chem. on halogen bonding in medicinal chemistry. I find the topic interesting, because it's an effect that certainly appears to be real, but is rarely (if ever) exploited in any kind of systematic way.
Halogens, especially the lighter fluorine and chlorine, are widely used substituents in medicinal chemistry. Until recently, they were merely perceived as hydrophobic moieties and Lewis bases in accordance with their electronegativities. Much in contrast to this perception, compounds containing chlorine, bromine, or iodine can also form directed close contacts of the type R–X···Y–R′, where the halogen X acts as a Lewis acid and Y can be any electron donor moiety. . .
What seems to be happening is that the electron density around the halogen atom is not as smooth as most of us picture it. You'd imagine a solid cloud of electrons around the bromine atom of a bromoaromatic, but in reality, there seems to be a region of slight positivecharge (the "sigma hole") out on the far end. (As a side effect, this give you more of a circular stripe of negative charge as well). Both these effects have been observed experimentally.
Now, you're not going to see this with fluorine; that one is more like most of us picture it (and to be honest, fluorine's weird enough already). But as you get heavier, things become more pronounced. That gives me (and probably a lot of you) an uneasy feeling, because traditionally we've been leery of putting the heavier halogens into our molecules. "Too much weight and too much hydrophobicity for too little payback" has been the usual thinking, and often that's true. But it seems that these substituents can actually earn out their advance in some cases, and we should be ready to exploit those, because we need all the help we can get.
Interestingly, you can increase the effect by adding more fluorines to the haloaromatic, which emphasizes the sigma hole. So you have that option, or you can take a deep breath, close your eyes, and consider. . .iodos:
Interestingly, the introduction of two fluorines into a chlorobenzene scaffold makes the halogen bond strength comparable to that of unsubstituted bromobenzene, and 1,3-difluoro-5-bromobenzene and unsubstituted iodobenzene also have a comparable halogen bond strength. While bromo and chloro groups are widely employed substituents in current medicinal chemistry, iodo groups are often perceived as problematic. Substituting an iodoarene core by a substituted bromoarene scaffold might therefore be a feasible strategy to retain affinity by tuning the Br···LB (Lewis base) halogen bond to similar levels as the original I···LB halogen bond.
As someone who values ligand efficiency, the idea of putting in an iodine gives me the shivers. A fluoro-bromo combo doesn't seem much more attractive, although almost anything looks good compared to a single atom that adds 127 mass units at a single whack. But I might have to learn to love one someday.
The paper includes a number of examples of groups that seem to be capable of interacting with halogens, and some specific success stories from recent literature. It's probably worth thinking about these things similarly to the way we think about hydrogen bonds - valuable, but hard to obtain on purpose. They're both directional, and trying to pick up either one can cause more harm than good if you miss. But keep an eye out for something in your binding site that might like a bit of positive charge poking at it. Because I can bet that you never thought to address it with a bromine atom!
Update: in the spirit of scientific inquiry, I've just sent in an iodo intermediate from my current work for testing in the primary assay. It's not something I would have considered doing otherwise, but if anyone gives me any grief, I'll tell them that it's 2013 already and I'm following the latest trends in medicinal chemistry.
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December 19, 2012
Well, I've been away from the computer a good part of the day, but I return to find that the author of the NSF press release that I spoke unkindly of has shown up in the comments to that post. I'm going to bring those up here to make sure that his objections get a fair hearing:
I wrote this press release, and I am a bit concerned that instead of discussing the research with myself, or more importantly the researchers, you decide to attack the text.
We presented information based on research that has been underway for some time, at least two years with NSF peer-reviewed support.
Additionally, we were careful to not overstate either the technology or the impact, but to present an illustration of what the technology can do in the limited space that a press release allows.
A journalist is expected to follow the initial reading of the press release with questions for the researchers involved -- not attack the limited text that we provide as an introduction.
In my eleven years at NSF, I have never had someone attack my work -- particularly without first getting their facts straight.
Please contact the researchers to discuss the technology and limit your criticism for those thongs for which you are informed.
Media Officer for Engineering
National Science Foundation
(To add, my supervisor pointed out a stellar typo in my last line.
I'm fear that's where the discussion will go next, but if you do wish to learn more about the actual research you are disparaging, please do contact the researchers to learn more about the technology and the approach.)
Several regular readers have already responded in the comments section to that earlier post, making the point that experienced drug discovery scientists found the language in the press release hard to believe (and reminiscent of overhyped work from the past). Josh Chamot's response is reproduced here:
Thank you for the thoughtful responses. This is exactly the engagement I was hoping for.
First, I agree that hype is never what we want to communicate -- and I appreciate that skepticism is critical to ensuring accuracy and the complete communication of news. However, I do hope many of you will explore the research further so that any skepticism is completely informed.
I want to be clear that I have no intention of misleading the research or pharma communities, nor do I want to give false hope to those who might need any of the treatments that we referenced. Our language was intended to convey that the breakthrough to date is exciting, but clearly more work is needed before this can start producing drugs for patients -- and I believe we stated this.
Through links to additional information (such as the full patent application) and clear contact information for the principal investigator, it is our hope that the primary audience for the press release (reporters) will present a thorough and complete account of the work.
We do not wish to mislead, but we also cannot convey a full news story in press release format. The intent is to serve as an alert, and importantly, an accurate one.
Journalists are the primary audience for the press releases, and our system of information is reliant on their services. To the best of my knowledge, the information we presented on Parabon is accurate and states only results that Parabon has demonstrated and announced in their patent application -- the starting point for a journalist to explore the story further.
As background, the pieces I work on cover research efforts that are originally proposed to NSF in a review process informed by peers in the community. Parabon has received both Phase I and Phase II NSF small business funding, so they had succeeded in that competitive peer review twice.
That setting served as a baseline to inform my office that the research approach was a valid starting point -- however, as with almost all NSF research, this is research at the very earliest stages. I can accept that while I wrote the release to reflect this, I was not successful in conveying this clearly. However, the assertions that data in support of the research effort do not exist are incorrect.
The company first came to our office (public affairs) more than two years ago, and it is only now that the company had enough publicly available information for us to pull together an announcement of the technology and some introduction of how it works.
I have some lessons learned here in how to try to clarify caveats, but I stand by my original assertion that the research is valid and exciting. While I have no way to predict Parabon's ultimate success, I do believe that public discussion of their technique can only prove of value to the broader drug development effort -- including the identification of any obstacles that this, or a similar technique, must overcome.
I think what I'll do now is close off the comments to the previous post and have things move over to this entry, with appropriate pointers, so we don't have two discussion going on at the same time. Now, then. I'm not blaming Mr. Chamot for what went out on the wires, because I strongly suspect that he worked with what he was given. It's the people at Parabon that I'd really like to have a word with. If the press release is an accurate reflection of what they wanted to announce, then we have a problem, and it's not with Jack Chamot.
I realize that a press release is, in theory, supposed to be for the press - for reporters to use as a starting point for a real story. But how many of them do that, versus just rewording the release a bit? There are reporters who could pick up on all the problems, but there are many others who might not. The information in the Parabon release, as it stands, makes little sense to those of us who do drug discovery for a living, seems full of overstated claims, and raises many more questions than it answers. Specialists in the field (as many readers here are) will have an immediate and strong reaction to this sort of thing.
And that's one of the purposes of this blog (and of many others): to bring expertise out into the open, to provide people within some specialized area a chance to talk with each other, and to provide people outside it (anyone at all) a chance to sit in and learn about things they otherwise might never hear discussed. I think that the process that Mr. Chamot has described is an older one: scientists describe a discovery of theirs to some sort of press officer, who puts into some useful and coherent form in order to get the word out to reporters, who then can contact the people involved for more details as they write up their stories for a general readership. That's fine, but these days that whole multistep procedure is subject to disintermediation. And that's what we're seeing right now.
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December 18, 2012
I'm having a real problem understanding this press release from the NSF. I've been looking at it for a few days now (it's been sent to me a couple of times in e-mail), and I still can't get a handle on it. And I'm not the only one. I see just this morning that Chemobber is having the same problem. Here, try some. See how you do:
Using a simple "drag-and-drop" computer interface and DNA self-assembly techniques, researchers have developed a new approach for drug development that could drastically reduce the time required to create and test medications. . ."We can now 'print,' molecule by molecule, exactly the compound that we want," says Steven Armentrout, the principal investigator on the NSF grants and co-developer of Parabon's technology. "What differentiates our nanotechnology from others is our ability to rapidly, and precisely, specify the placement of every atom in a compound that we design."
Say what? Surely they don't mean what it sounds like they mean. But they apparently do:
"When designing a therapeutic compound, we combine knowledge of the cell receptors we are targeting or biological pathways we are trying to affect with an understanding of the linking chemistry that defines what is possible to assemble," says Hong Zhong, senior research scientist at Parabon and a collaborator on the grants. "It's a deliberate and methodical engineering process, which is quite different from most other drug development approaches in use today."
OK, enough. I'd love for atom-by-atom nanotech organic synthesis and precisely targeted drug discovery to be a reality, but they aren't. Not yet. The patent application referenced in the press release is a bit more grounded in reality, but not all that much more:
The present invention provides nanostructures that are particularly well suited for delivery of bioactive agents to organs, tissues, and cells of interest in vivo, and for diagnostic purposes. In exemplary embodiments, the nanostructures are complexes of DNA strands having fully defined nucleotide sequences that hybridize to each other in such a way as to provide a pre-designed three dimensional structure with binding sites for targeting molecules and bioactive agents. The nanostructures are of a pre-designed finite length and have a pre-defined three dimensional structure
Ah, and these complexes of DNA strands will survive after in vivo dosing just exactly how? And will be targeted, via that precisely defined structure, just how? And bind to what, exactly, and with what sort of affinities? And are the binding sites on these DNA thingies, or do they bind to other things, anyway? No, this is a mess. And this press release is an irresponsible mishmosh of hype. I'd be glad to hear about some real results with some real new technology, and I'd like to ask the Parabon people to cough some up. I'd be equally glad to feature them on this blog if they can do so, but not if they're going to start talking like they're from the future and come to save us all. Sheesh.
Update: the discussion on this press release features a number of interesting comments. It's now moved over to this post, for reasons explained there. Thanks!
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December 17, 2012
I wrote here about "stapled peptides", which are small modified helical proteins. They've had their helices stabilized by good ol' organic synthesis, with artificial molecular bridging between the loops. There are several ways to do this, but they all seem to be directed towards the same end.
That end is something that acts like the original protein at its binding site, but acts more like a small molecule in absorption, metabolism, and distribution. Bridging those two worlds is a very worthwhile goal indeed. We know of hordes of useful proteins, ranging from small hormones to large growth factors, that would be useful drugs if we could dose them without their being cleared quickly (or not making it into the bloodstream in the first place). Oral dosing is the hardest thing to arrange. The gut is a very hostile place for proteins - there's a lot of very highly developed machinery in there devoted to ripping everything apart. Your intestines will not distinguish the live-saving protein ligand you just took from the protein in a burrito, and will act accordingly. And even if you give things intravenously, as is done with the protein drugs that have actually made it to clinical use (insulin, EPO, etc.), getting their half-lives up to standard can be a real challenge.
So the field of chemically modified peptides and proteins is a big one, because the stakes are high. Finding small molecules that modulate protein-protein interactions is quite painful; if we could just skip that part, we'd be having a better time of it in this industry. There's an entire company (Aileron, just down the road from me) working on this idea, and many others besides. So, how's it going?
Well, this new paper will cause you to wonder about that. It's from groups in Australia and at Genentech, (Note: edited for proper credit here) and they get right down to it in the first paragraph:
Stabilized helical peptides are designed to mimic an α-helical structure through a constraint imposed by covalently linking two residues on the same helical face (e.g., residue i with i + 4). “Stapling” the peptide into a preformed helix might be expected to lower the energy barrier for binding by reducing entropic costs, with a concomitant increase in binding affinity. Additionally, stabilizing the peptide may reduce degradation by proteases and, in the case of hydrocarbon linkages, reportedly enhance transport into cells, thereby improving bioavailability and their potential as therapeutic agents. The findings we present here for the stapled BH3 peptide (BimSAHB), however, do not support these claims, particularly in regards to affinity and cell permeability.
They go on to detail their lack of cellular assay success with the reported stapled peptide, and suggest that this is due to lack of cell permeability. And since the non-stapled peptide control was just as effective on artificially permeabilized cells, they did more studies to try to figure out what the point of the whole business is. A detailed binding study showed that the stapled peptide had lower affinity for its targets, with slower on-rates and faster off-rates. X-ray crystallography suggested that the modifying the peptide disrupted several important interactions.
Update: After reading the comments so far, I want to emphasize that this paper, as far as I can see, is using the exact same stapled peptide as was used in the previous work. So this isn't just a case of a new system behaving differently; this seems to be the same system not behaving the way that it was reported to.
The entire "staple a peptide to make it a better version of itself" idea comes in for some criticism, too:
Our findings recapitulate earlier observations that stapling of peptides to enforce helicity does not necessarily impart enhanced binding affinity for target proteins and support the notion that interactions between the staple and target protein may be required for high affinity interactions in some circumstances.19 Thus, the design of stapled peptides should consider how the staple might interact with both the target and the rest of the peptide, and particularly in the latter case whether its introduction might disrupt otherwise stabilizing interactions.
That would be more in line with my own intuition, for what it's worth, which is that making such changes to a peptide helix would turn it into another molecule entirely, rather than (necessarily) making it into an enhanced version of what it was before. Unfortunately, at least in this case, this new molecule doesn't seem to have any advantages over the original, at least in the hands of the Genentech group. This is, as they say, very much in contrast to the earlier reports. How to resolve the discrepancies? And how to factor in that Roche has a deal with Aileron for stapled-peptide technology, and this very article is (partly) from Genentech, now a part of Roche? A great deal of dust has just been stirred up; watching it settle will be interesting. . .
+ TrackBacks (0) | Category: Cancer | Chemical Biology | Pharmacokinetics
November 26, 2012
I don't know how many readers have been following this, but there's been some interesting work over the last few years in using streptavidin (a protein that's an old friend of chemical biologists everywhere) as a platform for new catalyst systems. This paper in Science (from groups at Basel and Colorado State) has some new results in the area, along with a good set of leading references. (One of the authors has also published an overview in Accounts of Chemical Research). Interestingly, this whole idea seems to trace back to a George Whitesides paper from back in 1978, if you can believe that.
(Strept)avidin has an extremely well-characterized binding site, and its very tight interaction with biotin has been used as a set of molecular duct tape in more experiments than anyone can count. Whitesides realized back during the Carter administration that the site was large enough to accommodate a metal catalyst center, and this latest paper is the latest in a string of refinements of that idea, this time using a rhodium-catalyzed C-H activation reaction.
A biotinylated version of the catalyst did indeed bind streptavidin, but this system showed very low activity. It's known, though, that the reaction needs a base to work, so the next step was to engineer a weakly basic residue nearby in the protein. A glutamate sped things up, and an aspartate even more (with the closely related asparagine showing up just as poorly as the original system, which suggests that the carboxylate really is doing the job). A lysine/glutamate double mutant gave even better results.
The authors then fine-tuned that system for enantioselectivity, mutating other residues nearby. Introducing aromatic groups increased both the yield and the selectivity, as it turned out, and the eventual winner was run across a range of substrates. These varied quite a bit, with some combinations showing very good yields and pretty impressive enantioselectivities for this reaction, which has never until now been performed asymmetrically, but others not performing as well.
And that's promise (and the difficulty) with enzyme systems. Working on that scale, you're really bumping up against individual parts of your substrates on an atomic level, so results tend, as you push them, to bin into Wonderful and Terrible. An enzymatic reaction that delivers great results across a huge range of substrates is nearly a contradiction in terms; the great results come when everything fits just so. (Thus the Codexis-style enzyme optimization efforts). There's still a lot of brute force involved in this sort of work, which makes techniques to speed up the brutal parts very worthwhile. As this paper shows, there's still no substitute for Just Trying Things Out. The structure can give you valuable clues about where to do that empirical work (otherwise the possibilities are nearly endless), but at some point, you have to let the system tell you what's going on, rather than the other way around.
+ TrackBacks (0) | Category: Chemical Biology | Chemical News
November 15, 2012
I like to highlight phenotypic screening efforts here sometimes, because there's evidence that they can lead to drugs at a higher-than-usual rate. And who couldn't use some of that? Here's a new example from a team at the Broad Institute.
They're looking at the very popular idea of "cancer stem cells" (CSCs), a population of cells in some tumors that appear to be disproportionately resistant to current therapies (and disproportionately responsible for tumor relapse and regrowth). This screen uses a surrogate breast cell line, with E-cadherin knocked down, which seems to give the dedifferentiated phenotype you'd want to target. That's a bit risky, using an artificial system like that, but as the authors correctly point out, isolating a pure population of the real CSCs is difficult-to-impossible, and they're very poorly behaved in cell culture. So until those problems are solved, you have your choice - work on something that might translate over to the real system, or ditch the screening idea for now entirely. I think the first is worth a shot, as long as its limitations are kept in mind.
This paper does go on to do something very important, though - they use an isogenic cell line as a counterscreen, very close to the target cells. If you find compounds that hit the targets but not these controls, you have a lot more confidence that you're getting at some difference that's tied to the loss of E-cadherin. Using some other cell line as a control leaves too many doors open too wide; you could see "confirmed hits" that are taking advantage of totally irrelevant differences between the cell lines instead.
They ran a library of about 300,000 compounds (the MLSMR collection) past the CSC model cells, and about 3200 had the desired toxic effect on them. At this point, the team removed the compounds that were flagged in PubChem as toxic to normal mammalian cell lines, and also removed compounds that had hit in more than 10% of the assays they'd been through, both of which I'd say are prudent moves. Retesting the remaining 2200 compounds gave a weird result: at the highest concentration (20 micromolar), 97 per cent of them were active. I probably would have gotten nervous at that point, wondering if something had gone haywire with the assay, and I'll bet that a few folks at the Broad felt the same way.
But when used the isogenic cell line, things narrowed down rather quickly. Only 26 compounds showed reasonable potency on the target cells along with at least a 25-fold window for toxicity to the isogenic cells. (Without that screen, then, you'd have been chasing an awful lot of junk). Then they ordered up fresh samples of these, which is another step that believe me, you don't want to neglect. A number of compounds appear to have not been quite what they were supposed to be (not an uncommon problem in a big screening collection; you trust the labels unconditionally at your own peril).
In the end, two acylhydrazone compounds ended up retaining their selectivity after rechecking. So you can see how things narrow down in these situations: 300K to 2K to 26 to 2, and that's not such an unusual progression at all. The team made a series of analogs around the lead chemical matter, and then settled on the acylhydrazone compound shown (ML239) as the best in show. It's not a beauty. There seems to be some rule that more rigorous and unusual a phenotypic screen, the uglier the compounds that emerge from it. I'm only half kidding, or maybe a bit less - there are some issues to think about in there, and that topic is worth a post of its own.
More specifically, the obvious concern in that fulvene-looking pyrrole thingie on the right (I use "thingie" in its strict technical sense here). That's not a happy-looking (that is, particularly stable-looking) group. The acylhydrazine part might raise eyebrows with some people, but Rimonabant (among other compounds) shows that that functional group can be part of a drug. Admittedly, Rimonabant went down with all hands, but it wasn't because of the acylhydrazine. And the trichloroaryl group isn't anyone's favorite, either, but in this context, it's just sort of a dessert topping, in an inverse sense.
But the compound appears to be the real thing, as a pharmacological tool. It was also toxic to another type of breast cancer cell that had had its E-cadherin disrupted, and to a further nonengineered breast cancer cell line. Now comes the question: how does this happen? Gene expression profiling showed a variety of significant changes, with all sorts of cell death and free radical scavenging things altered. By contrast, when they did the same profiling on the isogenic controls, only five genes were altered to any significant extent, and none of those overlapped with the target cells. This is very strong evidence that something specific and important is being targeted here. A closer analysis of all the genes suggests the NF-kappaB system, and within that, perhaps a protein called TRIB3. Further experiments will have to be done to nail that down, but it's a good start. (And yes, in case you were wondering, TRIB3 does, in fact, stand for "tribble-3", and yes, that name did originate with the Drosophila research community, and how did you ever guess?)
So overall, I'd say that this is a very solid example of how phenotypic screening is supposed to work. I recommend it to people who are interested in the topic - and to people who aren't, either, because hey, you never know when it might come in handy. This is how a lot of new biology gets found, through identifying useful chemical matter, and we can never have too much of it.
+ TrackBacks (0) | Category: Cancer | Chemical Biology | Drug Assays
November 8, 2012
We're getting closer to real-time X-ray structures of protein function, and I think I speak for a lot of chemists and biologists when I say that this has been a longstanding dream. X-ray structures, when they work well, can give you atomic-level structural data, but they've been limited to static time scales. In the old, old days, structures of small molecules were a lot of work, and structure of a protein took years of hard labor and was obvious Nobel Prize material. As time went on, brighter X-ray sources and much better detectors sped things up (since a lot of the X-rays deflected from a large compound are of very low intensity), and computing power came along to crunch through the piles of data thus generated. These days, x-ray structures are generated for systems of huge complexity and importance. Working at that level is no stroll through the garden, but more tractable protein structures are generated almost routinely (although growing good protein crystals is still something of a dark art, and is accomplished through what can accurately be called enlightened brute force).
But even with synchrotron X-ray sources blasting your crystals, you're still getting a static picture. And proteins are not static objects; the whole point of them is how they move (and for enzymes, how they get other molecules to move in their active sites). I've heard Barry Sharpless quoted to the effect that understanding an enzyme by studying its X-ray structures is like trying to get to know a person by visiting their corpse. I haven't heard him say that (although it sounds like him!), but whoever said it was correct.
Comes now this paper in PNAS, a multinational effort with the latest on the attempts to change that situation. The team is looking at photoactive yellow protein (PYP), a blue-light receptor protein from a purple sulfur bacterium. Those guys vigorously swim away from blue light, which they find harmful, and this seems to be the receptor that alerts them to its presence. And the inner workings of the protein are known, to some extent. There's a p-courmaric acid in there, bound to a Cys residue, and when blue light hits it, the double bond switches from trans to cis. The resulting conformational change is the signaling event.
But while knowing things at that level is fine (and took no small amount of work), there are still a lot of questions left unanswered. The actual isomerization is a single-photon event and happens in a picosecond or two. But the protein changes that happen after that, well, those are a mess. A lot of work has gone into trying to unravel what moves where, and when, and how that translates into a cellular signal. And although this is a mere purple sulfur bacterium (What's so mere? They've been on this planet a lot longer than we have), these questions are exactly the ones that get asked about protein conformational signaling all through living systems. The rods and cones in your eyes are doing something very similar as you read this blog post, as are the neurotransmitter receptors in your optic nerves, and so on.
This technique, variations of which have been coming on for some years now, uses multiple wavelengths of X-rays simultaneously, and scans them across large protein crystals. Adjusting the timing of the X-ray pulse compared to the light pulse that sets off the protein motion gives you time-resolved spectra - that is, if you have extremely good equipment, world-class technique, and vast amounts of patience. (For one thing, this has to be done over and over again from many different angles).
And here's what's happening: first off, the cis structure is quite weird. The carbonyl is 90 degrees out of the plane, making (among other things) a very transient hydrogen bond with a backbone nitrogen. Several dihedral angles have to be distorted to accommodate this, and it's a testament to the weirdness of protein active sites that it exists at all. It then twangs back to a planar conformation, but at the cost of breaking another hydrogen bond back at the phenolate end of things. That leaves another kind of strain in the system, which is relieved by a shift to yet another intermediate structure through a dihedral rotation, and that one in turn goes through a truly messy transition to a blue-shifted intermediate. That involves four hydrogen bonds and a 180-degree rotation in a dihedral angle, and seems to be the weak link in the whole process - about half the transitions fail and flop back to the ground state at that point. That also lets a crucial water molecule into the mix, which sets up the transition to the actual signaling state of the protein.
If you want more details, the paper is open-access, and includes movie files of these transitions and much more detail on what's going on. What we're seeing is light energy being converted (and channeled) into structural strain energy. I find this sort of thing fascinating, and I hope that the technique can be extended in the way the authors describe:
The time-resolved methodol- ogy developed for this study of PYP is, in principle, applicable to any other crystallizable protein whose function can be directly or indirectly triggered with a pulse of light. Indeed, it may prove possible to extend this capability to the study of enzymes, and literally watch an enzyme as it functions in real time with near- atomic spatial resolution. By capturing the structure and temporal evolution of key reaction intermediates, picosecond time-resolved Laue crystallography can provide an unprecedented view into the relations between protein structure, dynamics, and function. Such detailed information is crucial to properly assess the validity of theoretical and computational approaches in biophysics. By com- bining incisive experiments and theory, we move closer to resolving reaction pathways that are at the heart of biological functions.
Speed the day. That's the sort of thing we chemists need to really understand what's going on at the molecular level, and to start making our own enzymes to do things that Nature never dreamed of.
+ TrackBacks (0) | Category: Analytical Chemistry | Biological News | Chemical Biology | Chemical News
October 30, 2012
The Atlantic is out with a list of "Brave Thinkers", and one of them is Jay Bradner at Harvard Medical School. He's on there for JQ1, a small-molecule bromodomain ligand that was reported in 2010. (I note, in passing, that once again nomenclature has come to the opposite of our rescue, since bromodomains have absolutely nothing to do with bromine, in contrast to 98% of all the other words that begin with "bromo-")
These sorts of compounds have been very much in the news recently, as part of the whole multiyear surge in epigenetic research. Drug companies, naturally, are looking to the epigenetic targets that might be amenable to small-molecule intervention, and bromodomains seem to qualify (well, some of them do, anyway).
At any rate, JQ1 is a perfectly reasonable probe compound for bromodomain studies, but it got a lot of press a couple of months ago as a potential male contraceptive. I found all that wildly premature - a compound like this one surely sets off all kinds of effects in vivo, and disruption of spermatogenesis is only one of them. Note (PDF) that it hits a variety of bromodomain subtypes, and we only have the foggiest notion of what most of these are doing in real living systems.
The Atlantic, for its part, makes much of Bradner's publishing JQ1 instead of patenting it:
The monopoly on developing the molecule that Bradner walked away from would likely have been worth a fortune (last year, the median value for U.S.-based biotech companies was $370 million). Now four companies are building on his discovery—which delights Bradner, who this year released four new molecules. “For years, drug discovery has been a dark art performed behind closed doors with the shades pulled,” he says. “I would be greatly satisfied if the example of this research contributed to a change in the culture of drug discovery.”
But as Chemjobber rightly says, the idea that Bradner walked away from a fortune is ridiculous. JQ1 is not a drug, nor is it ever likely to become a drug. It has inspired research programs to find drugs, but they likely won't look much (or anything) like JQ1, and they'll do different things (for one, they'll almost surely be more selective). In fact, chasing after that sort of selectivity is one of the things that Bradner's own research group appears to be doing - and quite rightly - while his employer (Dana-Farber) is filing patent applications on JQ1 derivatives. Quite rightly.
Patents work differently in small-molecule drug research than most people seem to think. (You can argue, in fact, that it's one of the areas where the system works most like it was designed to, as opposed to often-abominable patent efforts in software, interface design, business methods, and the like). People who've never had to work with them have ideas about patents being dark, hidden boxes of secrets, but one of the key things about a patent is disclosure. You have to tell people what your invention is, what it's good for, and how to replicate it, or you don't have a valid patent.
Admittedly, there are patent applications that do not make all of these steps easy - a case in point would be the ones from Exelixis - I wrote here about my onetime attempts to figure out the structures of some of their lead compounds from their patent filings. Not long ago I had a chance to speak with someone who was there at the time, and he was happy to hear that I'd come up short, saying that this had been exactly the plan). But at the same time, all their molecules were in there, along with all the details of how to make them. And the claims of the patents detailed exactly why they were interested in such compounds, and what they planned to do with them as drugs. You could learn a lot about what Exelixis was up to; it was just that finding out the exact structure of the clinical candidate that was tricky. A patent application on JQ1 would have actually ended up disclosing most (or all) of what the publication did.
I'm not criticizing Prof. Bradner and his research group here. He's been doing excellent work in this area, and his papers are a pleasure to read. But the idea that Harvard Medical School and Dana-Farber would walk away from a pharma fortune is laughable.
+ TrackBacks (0) | Category: Cancer | Chemical Biology | Drug Development | Patents and IP
October 17, 2012
Zafgen is a startup in the Boston area that's working on a novel weight-loss drug called beloranib. Their initial idea was that they were inhibiting angiogenesis in adipose tissue, through inhibition of methionine aminopeptidase-2. But closer study showed that while the compound was indeed causing significant weight loss in animal models, it wasn't through that mechanism. Blood vessel formation wasn't affected, but the current thinking is that Met-AP2 inhibition is affecting fatty acid synthesis and causing more usage of lipid stores.
But when they say "novel", they do mean it. Behold one of the more unlikely-looking drugs to make it through Phase I:
Natural-product experts in the audience might experience a flash of recognition. That's a derivative of fumagillin, a compound from Aspergillus that's been kicking around for many years now. And its structure brings up a larger point about reactive groups in drug molecules, the kind that form covalent bonds with their targets.
I wrote about covalent drugs here a few years ago, and the entire concept has been making a comeback. (If anyone was unsure about that, Celgene's purchase of Avila was the convincer). Those links address the usual pros and cons of the idea: on the plus side, slow off rates are often beneficial in drug mechanisms, and you don't get much slower than covalency. On the minus side, you have to worry about selectivity even more, since you really don't want to go labeling across the living proteome. You have the mechanisms of the off-target proteins to worry about once you shut them down, and you also have the ever-present fear of setting off an immune response if the tagged protein ends up looking sufficiently alien.
I'm not aware of any published mechanistic studies of beloranib, but it is surely another one of this class, with those epoxides. (Looks like it's thought to go after a histidine residue, by analogy to fumagillin's activity against the same enzyme). But here's another thing to take in: epoxides are not as bad as most people think they are. We organic chemists see them and think that they're just vibrating with reactivity, but as electrophiles, they're not as hot as they look.
That's been demonstrated by several papers from the Cravatt labs at Scripps. (He still is at Scripps, right? You need a scorecard these days). In this work, they showed that some simple epoxides, when exposed to entire proteomes, really didn't label many targets at all compared to the other electrophiles on their list. And here, in an earlier paper, they looked at fumagillin-inspired spiroexpoxide probes specifically, and found an inhibitor of phosphoglycerate mutase 1. But a follow-up SAR study of that structure showed that it was very picky indeed - you had to have everything lined up right for the epoxide to react, and very close analogs had no effect. Taken together, the strong implication is that epoxides can be quite selective, and thus can be drugs. You still want to be careful, because the toxicology literature is still rather vocal on the subject, but if you're in the less reactive/more structurally complex/more selective part of that compound space, you might be OK. We'll see if Zafgen is.
+ TrackBacks (0) | Category: Chemical Biology | Diabetes and Obesity | Drug Development
September 28, 2012
This evening's EMBL speaker is Paul Workman on new cancer targets and drug development. He's pointed out that treating cancer (and classifying cancer) by where it's located in the body is actually fairly primitive. Tumor cells in, say, breast cancer surely have more in common with various other type of tumor cells than they do with the normal cells surrounding them.
He claims that we're starting to see attrition rates come down in oncology, and I hope he's right. I see, though, that he's reified the "Valley of Death", which I'm not so sure about. There surely are some ideas in academia that should be moved along to development, but not all of them are worthy. (That's no slur - not all the targets inside the drug companies are worthy either, believe me). I worry that constant referral to a Valley of Death makes it sound as if there's something mysterious going on, when it really doesn't seem that strange to me. This Valley is mostly a gap between what works and what doesn't, rather than between academia and industry.
He also has a good slide on probe compounds versus drugs (here are the details). Probes, he says, need to meet even more stringent criteria for selectivity and potency than drugs do if their purpose is going to be to uncover new biology. Selectivity is usually the hardest barrier. That said, probes have to evolve. You don't find compounds like this right out of an HTS screen, and they're going to need some cycles of med-chem before they're truly ready for use. A less-than-optimal probe shouldn't be seen as a failure, but as an intermediate step.
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John Overington from the EMBL is talking about the ChEMBL database, which is an impressive collection. One thing that I appreciate is that he's being upfront about the error rates in the data. He takes the reports of trouble seriously, but feels (overall) that considering the amount of data they have, and the amount of annotation associated with it, that they've done well.
There are an awful lot of ways that you can work the numbers from their web site, which is both good and bad. If you know what you're doing, you can get some very interesting and potentially useful results, but if you don't, you can mislead yourself more quickly and thoroughly than you ever could by hand. That's common to all powerful tools, naturally.
My talk is right after the next speaker, so I won't be posting for a bit. And no, I will not be writing a critique of my own talk while I'm giving it; that would be a Blog Singularity of some sort.
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September 27, 2012
Now the conference day is winding up with a big talk by George Whitesides. He's talking about his thoughts on enzyme function, with reference to his group's work using carbonic anhydrase as a model. He praises its stability ("a ceramic brick") and other characteristics, as you might expect from someone who's published an entire review on its use in biophysical studies.
So what makes compounds bind to enzyme sites? His take on the hydrophobic effect is that he thinks it's due as much (or more) to changes in networks of water molecules, rather than just the release of structured water at the protein-ligand contact. The latter is important, for sure, but not the whole story. "There is no one hydrophobic effect", he says, "there are many hydrophobic effects".
Another quote: "There ain't nothin' like water", and I definitely agree. We're used to water, since it's the most common chemical substance that we deal with in our lives, but water is weird.
And there's a lot we don't know about it still. For example, Whitesides has just pointed out that we have a reasonable understanding of surface tension in the bulk phase - but not at all for molecular-sized holes. This is crucial for understanding ligand behavior. His view of protein-ligand binding, he says, is very water-centric. . .
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Just to emphasize how careful you have to be with all these probes and labels, consider what I'm hearing now from Remigiusz Serwa of the Tate group at Imperial College. His group is looking at farnesylation. People have tried making azido-containing substrates, for later "click" fluorescent labeling of proteins that pick up the label, but the azido group turns out to be a loser here. It's too polar in the greasy world of prenyl groups, and things go haywire.
You'd think that switching the click reaction around would be the answer here - make an alkyne group to be picked up by farnesyltransferase and you're in. But the ones that have been tried so far are terrible substrates for the enzymes. He seems to be on the way to solving that problem, but (interestingly) isn't revealing the structure (yet) of his probe. Must be a manuscript on the way - probably with a patent on the way before that?
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The latest talk is from Alanna Schepartz of Yale. I had a chance to ride in from the airport with her yesterday, and she gave me a brief preview of her talk, which is on transport of both molecules and information through the plasma membrane of cells. "Some molecules weren't paying attention when Lipinski's rules came down", she says (Lipinski himself was supposed to be here, but had to cancel at the last minute, BTW).
The example here is the EGF receptor. We know a fair amount about the extracellular domain of this protein, and some about the intracellular part. But the "juxtamembrane" portion connecting the two is more of a mystery, although it's clearly crucial for receptor signaling. Her lab has been using a fluorescent marker for particular protein coil structures. What this work seems to show is that different ligands for EGFR (EGF versus TGF-alpha), which are known to produce different downstream signaling, do so through different structures of the protein. Subtle variations of the coiled-coil helical protein on the intracellular face are meaningful and provide yet another way for these receptors to vary their function.
You'd think that there would have to be some such structural difference, since the two "agonists" do act differently. But actually getting a look at it in action is something else again. This is, to me, another example of "treat the protein as a big molecule" thinking. People who do structure-based drug discovery are used to that viewpoint, but not all molecular and cell biologists are. They'll find chemistry infiltrating their worldview, is my prediction. . .
+ TrackBacks (0) | Category: Chemical Biology
Now I'm listening to David Tirrell of Cal Tech, talking about his lab's work on labeling proteins with azidohomoalanine (Aha) as a marker. He's done a good job showing that (if you don't go wild) that replacement of methionine with this amino acid doesn't perturb things very much at all, and there's a recent paper showing how well the technique works (when combined with stable isotope labeling) for analyzing mixtures of low-abundance proteins. You can now buy all the reagents you need to do this.
The Aha can be activated by wild-type Met tRNA synthetase (MetRS), but he's also working with weirder amino acids that require a mutant RS enzyme. This is useful for even finer-grained experiments; the example shown is for monitoring host-pathogen interactions. Using a Yersinia species, he's showing all sorts of complex results, most of which fall into the category of "Must be important, but we don't know what they mean yet". The bacteria inject a number of as-yet-uncharacterized proteins into mammalian cells, for example, and without techniques like these, you'd never find them.
They've gone as far as doing this in whole living nematodes - it looks like this has been disclosed at meetings, but there doesn't appear to be a full paper on this yet.
A nice quote from the talk: "We did a computational search, which didn't help us out very much, but the experiment was great". Words to live by!
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Right now, there's a talk going on from Helma Wennemers of the ETH. She's working on small peptidic catalysts for organic reactions, what one might think of as "mini-enzymes". They're certainly not as wildly effective as real enzymes, but they're a lot easier to find and modify. Here's an example, which has been extended to solid-supported catalysts here. And whenever I see a solid-supported catalyst, I think "Can you use that for flow chemistry?" I was glad to see that they're done just that - I don't think that work has been published yet, but it seems to work pretty well.
Chemistry like this is a good reminder of just how many catalysts remain to be found. I don't see any reason, a priori, for any reaction to be out of bounds for enzymatic-type catalysis. You have functional groups that can participate in some reaction mechanisms (as is the case for the proline nitrogen in the above work), you have stabilization of transition states, you have sheer physical proximity/effective molarity, and probably other effects that people are still arguing about. Eventually we'll get good enough to design such things, but for now, a combination of design and what I might call "enlightened brute force" looks like the way to go. I'd like to see someone pick some reaction types that are not catalyzed enzymatically and apply these techniques to make something we've never seen before. If we could figure out how to get new metallic centers into these this things (imagine an enzymatic palladium catalyst!), we could really do some wild chemistry. Mind you, I'm not the one who would be trying to get that funded.
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Jason Chin of the MRC Molecular Biology lab in the UK has been talking here about protein labeling and genetic code expansion, an overview of the numerous papers his group has been publishing in this area over the last few years.
And he's just made what I think is a very worthwhile point. While talking about labeling proteins with very reactive alkyne-containing amino acids (for fluorescent "click" applications), he said that some people would look at this and say "Why bother - you can already label these things with GFP". But sticking an entire Green Fluorescent Protein onto an existing one is hardly a silent event. If you're going to think about these things the way a chemist would, you need to come in with something as small and unobtrusive as possible. And it also needs to be something that you can localize, which doesn't just mean "I know what protein it's on".
Chemists think - or had better think - at a higher magnification. What exact surface of the protein is this label on? What residues are next to it? What sort of binding pockets might it be interrogating? We need to treat proteins as molecules, and as molecules they have a lot of detail in them.
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September 26, 2012
Chris Walsh of Harvard is talking about the trithiazolylpeptide antibiotics and related compounds. If you thought that only we synthetic organic chemists were crazy enough to link three more heterocycles onto a central pyridine, leading to compounds which "have the solubility of sand" (a direct quote from Walsh), then think again. And they weren't even made by palladium-catalyzed couplings! Since we were talking about macrocycles here the other day, it's worth noting that these are also 29-membered rings and the like.
Here's one of them for you, if you haven't seen these beasts before. Who's synthesized it? Funny you should ask. . .
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A short talk from Steven Verhelst of Munich went into detail on some covalent probes for rhomboid proteases. I've been interested for a while about what happens when you run small electrophilic compounds over proteins - do they stick to everything, or can they show selectivity? The canonical paper on this topic is from the Cravatt group, which I'd recommend to anyone who finds this topic worthy. (Update: the Liebler group at Vanderbilt has also published some excellent work in this area, concentrating on Cys modification). Verhelst had one variety of electrophile that was selective in the active site, and another class that inhibited by sticking all over the place. So the answer is probably "Depends on your protein, and on your electrophile. Try it and see".
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Now I'm listening to Jim Wells (UCSF) talk about (among other things) this work, where they found a compound aggregating and causing activity in their assays. But this one wasn't doing the standard globular gunk that the usual aggregation gives you. Instead, the compound formed nanofibrils - microns long. And the enzyme that the compound showed activity against turns out to bind to the surface of the fribrils. Wells likens the effect to the way that Brussel sprouts grow, and his electron micrograph does indeed look pretty close. The question is, does this mimic something that happens "in real life", or is it a complete artifact? There's a paper in press in JBC going into some of the details. Just goes to show you that compounds are capable of doing things that you'd never have been able to guess.
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I'm listening to Paul Hergenrother (of Illinois) talk about using natural products as starting materials for compound screening libraries. It's a good idea - he takes readily available complex structures and does a range of organic chemistry on each of them, to make non-natural structures that have the complexity and functionality of natural products. I note that he's taken adrenosterone and made azasteroid derivatives (among many others), very similar to what I talked about here. He's also used quinine, gibbererlic acid, and others.
He's taken the collection thus produced and run them through phenotypic cell screens, with what look like interesting preliminary results. The idea is to look for unusual phenotypes and work backwards to new targets from them, so having a pile of unusual compounds is probably a good starting point. Of course, I have a weakness for phenotypic screens in general, and I suspect I'm going to be hearing a lot about them here over the next few days.
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August 21, 2012
This paper from GlaxoSmithKline uses a technology that I find very interesting, but it's one that I still have many questions about. It's applied in this case to ADAMTS-5, a metalloprotease enzyme, but I'm not going to talk about the target at all, but rather, the techniques used to screen it. The paper's acronym for it is ELT, Encoded Library Technology, but that "E" could just as well stand for "Enormous".
That's because they screened a four billion member library against the enzyme. That is many times the number of discrete chemical species that have been described in the entire scientific literature, in case you're wondering. This is done, as some of you may have already guessed, by DNA encoding. There's really no other way; no one has a multibillion-member library formatted in screening plates and ready to go.
So what's DNA encoding? What you do, roughly, is produce a combinatorial diversity set of compounds while they're attached to a length of DNA. Each synthetic step along the way is marked by adding another DNA sequence to the tag, so (in theory) every compound in the collection ends up with a unique oligonucleotide "bar code" attached to it. You screen this collection, narrow down on which compound (or compounds) are hits, and then use PCR and sequencing to figure out what their structures must have been.
As you can see, the only way this can work is through the magic of molecular biology. There are so many enzymatic methods for manipulating DNA sequences, and they work so well compared with standard organic chemistry, that ridiculously small amounts of DNA can be detected, amplified, sequenced, and worked with. And that's what lets you make a billion member library; none of the components can be present in very much quantity (!)
This particular library comes off of a 1,3,5-triazine, which is not exactly the most cutting-edge chemical scaffold out there (I well recall people making collections of such things back in about 1992). But here's where one of the big questions comes up: what if you have four billion of the things? What sort of low hit rate can you not overcome by that kind of brute force? My thought whenever I see these gigantic encoded libraries is that the whole field might as well be called "Return of Combichem: This Time It Works", and that's what I'd like to know: does it?
There are other questions. I've always wondered about the behavior of these tagged molecules in screening assays, since I picture the organic molecule itself as about the size of a window air conditioner poking out from the side of a two-story house of DNA. It seems strange to me that these beasts can interact with protein targets in ways that can be reliably reproduced once the huge wad of DNA is no longer present, but I've been assured by several people that this is indeed the case.
In this example, two particular lineages of compounds stood out as hits, which makes you much happier than a collection of random singletons. When the team prepared a selection of these as off-DNA "real organic compounds", many of them were indeed nanomolar hits, although a few dropped out. Interestingly, none of the compounds had the sorts of zinc-binding groups that you'd expect against the metalloprotease target. The rest of the paper is a more traditional SAR exploration of these, leading to what one has to infer are more tool/target validation compounds rather than drug candidates per se.
I know that GSK has been doing this sort of thing for a while, and from the looks of it, this work itself was done a while ago. For one thing, it's in J. Med. Chem., which is not where anything hot off the lab bench appears. For another, several of the authors of the paper appear with "Present Address" footnotes, so there has been time for a number of people on this project to have moved on completely. And that brings up the last set of questions, for now: has this been a worthwhile effort for GSK? Are they still doing it? Are we just seeing the tip of a large and interesting iceberg, or are we seeing the best that they've been able to do? That's the drug industry for you; you never know how many cards have been turned over, or why.
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August 16, 2011
Here's another paper at the intersection of biology and chemistry: a way to check the activity of a huge number of mutated esterase enzymes, all at the same time.
Protein engineering is a hot field, as well it should be, since enzymes do things in ways that we lowly organic chemists can only envy. Instead of crudely bashing and beating on the molecules out in solution, an enzyme grabs each of them, one at a time, and breaks just the bond it wants to, in the direction it wants to do it, and then does it again and again. If you're looking for molecular-scale nanotechnology, there it is, and it's been right in front of us the whole time.
Problem is, enzymes get that way through billions of years of evolution and selection, and those selection pressures don't necessarily have anything to do with the industrial reactions we're thinking of these days. And since we don't have a billion years to wait, we have to speed things up. Thus the work at places like Codexis on engineered mutant enzymes, and thus a number of very interesting takes on directed evolution. (Well, interesting to me, at any rate - I have a pronounced weakness for this sort of thing).
This latest paper, from the University of Greifswald in Germany, builds on the work of Manfred Reetz at the Max-Planck Institute, who's been very influential in the field. Specifically, it follows up on the idea in this paper from his group and this one from the Quax group at Groningen in the Netherlands. That technique involved selecting for specificity in esterase enzymes by giving organisms a choice of two substrates: if they hydrolyze the right chiral starting material, the cleaved ester furnishes them with a nutrient. If they hydrolyze the wrong one, though, they produce a poison. Rather direct, but with bacteria there's no other way to get their attention - survival's really all they care much about.
And that technique worked, but it was a bit laborious. The largest number of different variations tested was about 2500, which seems like a lot until you do the math on protein mutations. It gets out of control very, very quickly when you have twenty variations per amino acid residue. Naturally, some of the residues shouldn't ever be touched, while others will have only minimal effects, and others are the hot spots you should be concentrating on. But which ones are which? And since you absolutely can't assume that they're all acting independently of each other, you have your work cut out for you. (Navigation through this thicket is what Codexis is selling, actually).
This latest paper adds flow cytometry, cell sorting, to the mix. Using dye systems and one of these machines to distinguish viable bacteria from dead or dying ones lets you take a culture and pull out only the survivors. When the authors expressed different esterases (with known preferences for the two substrates) in E. coli, they got the expected results - the ones with an enzyme that could cleave the nutrient-giving substrate grew, while the ones that unveiled the poison (2,3-dibromopropanol) halted in their tracks.
They then took another esterase with very modest selectivity and created a library of mutant variations - about ten million mutant variations - and expressed the whole shebang in a single liquid colony of E. coli. This was then exposed to the mixture of substrates, and anything that grew was pulled out by the cell sorter and plated out on agar (also containing the selection mixture of substrates). They got 28 clones to grow in the end, and characterized three of these more fully as purified enzymes. Of those, two of them were, in fact, much more selective than the starting enzyme (giving E values, enantiomeric ratios, of 80 to 100 as opposed to 3). Another, interestingly, was not selective at all.
And when you look at the sequences and the mutations that were picked out, you can see how tricky a business this is. One of the two selective enzymes had its valine-121 residues mutated to isoleucine (V128I) its phenylalanine-198 residue mutated to cysteine (F198C). The other was broadly similar, with one added mutation: that valine-121 was changed in this case to serine (V121S), the F198 was mutated to glycine (F198G), and also valine-225 was changed to alanine (V225A). Now, some of those aren't very big mutations (V to I, V to A), but what's even more interesting is the sequence of the unselective clone that they characterized: that one had V121I, F198G, V225A. So it had a mix of the exact mutations found in the two selective enzymes, but was itself a dud.
I'm glad to see that this worked, although you have to wonder how efficiently it moves in on a target when you get two decent hits out of ten million starting mutations. (The relative ease of screening goes a long way towards making up for that). But what I'd like to see is a mix of this technique with the one that I wrote about a few weeks ago, where a bacterium was evolved to use a chlorinated DNA base. That one used a particularly slick directed-evolution device, which would be quite interesting to apply to this food-versus-poison idea. You'd have to do some fine-tuning, especially at first, since the liberated poisonous substrate would be killing off the just and the unjust alike (which is the same problem that this current paper faced). But it seems like there should be a way to run things so that you're not just screening a big library of random mutations in the enzyme, but actually pushing the enzyme to evolve in the direction you want. Thoughts?
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July 6, 2011
There's been a real advance in the field of engineered "unnatural life", but it hasn't produced one-hundredth the headlines that the arsenic bacteria story did. This work is a lot more solid, although it's hard to summarize in a snappy way.
Everyone knows about the four bases of DNA (A, T, C, G). What this team has done is force bacteria to use a substitute for the T, thymine - 5-chlorouracil, which has a chlorine atom where thymine's methyl group is. From a med-chem perspective, that's a good switch. The two groups are about the same size, but they're different enough that the resulting compounds can have varying properties. And thymine is a good candidate for a swap, since it's not used in RNA, thus limiting the number of systems that have to change to accommodate the new base. (RNA, of course, uses uracil instead, the unsubstituted parent compound of both thymine and the 5-chloro derivative used here).
Over the years, chlorouracil has been studied in DNA for just that reason, and it's been found to make the proper base-pair hydrogen bonds, among other things. So incorporating it into living bacteria looks like an experiment in just the right spot - different enough to be a real challenge, but similar enough to be (probably) doable. People have taken a crack at similar experiments before, with mixed success. In the 1970s, mutant hamster cells were grown in the presence of the bromo analog, and apparently generated DNA which was strongly enriched with that unnatural base. But there were a number of other variables that complicated the experiment, and molecular biology techniques were in their infancy at the time. Then in 1992, a group tried replacing the thymine in E. coli with uracil, with multiple mutations that shut down the T-handling pathways. They got up to about 90% uracil in the DNA, but this stopped the bacteria from growing - they just seemed to be hanging on under those T-deprived conditions, but couldn't do much else. (In general, withholding thymine from bacterial cultures and other cells is a good way to kill them off).
This time, things were done in a more controlled manner. The feat was accomplished by good old evolutionary selection pressure, using an ingenious automated system. An E. coli strain was produced with several mutations in its thymine pathways to allow it to survive under near-thymine-starvation conditions. These bacteria were then grown in a chamber where their population density was being constantly measured (by turbidity). Every ten minutes a nutrient pulse went in: if the population density was above a set limit, the cells were given a fixed amount of chlorouracil solution to use. If the population had falled below a set level, the cells received a dose of thymine-containing solution to keep them alive. A key feature of the device was the use of two culture chambers, with the bacteria being periodically swapped from one to the other (which the first chamber undergoes sterilization with 5M sodium hydroxide!) That's to keep biofilm formation from giving the bacteria an escape route from the selection pressure, which is apparently just what they'll do, given the chance. One "culture machine" was set for a generation time of about two hours, and another for a 4-hour cycle (by cutting in half the nutrient amounts). This cycle selected for mutations that allowed the use of chlorouracil throughout the bacteria's biochemistry.
And that's what happened - the proportion of the chlorouracil solution that went in went up with time. The bacterial population had plenty of dramatic rises and dips, but the trend was clear. After 23 days, the experimenters cranked up the pressure - now the "rescue" solution was a lower concentration of thymine, mixed 1:1 with chlorouracil, and the other solution was a lower concentration of chlorouracil only. The proportion of the latter solution used still kept going up under these conditions as well. Both groups (the 2-hour cycle and the 4-hour cycle ones) were consuming only chlorouracil solution by the time the experiment went past 140 days or so.
Analysis of their DNA showed that it had incorporated about 90% chlorouracil in the place of thymine. The group identified a previously unknown pathway (U54 tRNA methyltransferase) that was bringing thymine back into the pathway, and disrupting this gene knocked the thymine content down to just above detection level (1.5%). Mass spec analysis of the DNA from these strains clearly showed the chlorouracil present in DNA fractions.
The resulting bacteria from each group, it turned out, could still grow on thymine, albeit with a lag time in their culture. If they were switched to thymine media and grown there, though, they could immediately make the transition back to growing on chlorouracil, which shows that their ability to do so was now coded in their genomes. (The re-thymined bacteria, by the way, could be assayed by mass spec as well for the disappearance of their chlorouracil).
These re-thymined bacteria were sequenced (since the chloruracil mutants wouldn't have matched up too well with sequencing technology!) and they showed over 1500 base substitutions. Interestingly, there were twice as many in the A-T to G-C direction as the opposite, which suggests that chlorouracil tends to mispair a bit with guanine. The four-hour-cycle strain had not only these sorts of base swaps, but also some whole chromosome rearrangements. As the authors put it, and boy are they right, "It would have been impossible to predict the genetic alterations underlying these adaptations from current biological knowledge. . ."
These bacteria are already way over to the side of all the life on Earth. But the next step would be to produce bacteria that have to live on chlorouracil and just ignore thymine. If that can be realized, the resulting organisms will be the first representatives of a new biology - no cellular life form has ever been discovered that completely switches out one of the DNA bases. These sorts of experiments open the door to organisms with expanded genetic codes, new and unnatural proteins and enzymes, and who knows what else besides. And they'll be essentially firewalled from all other living creatures.
Postscript: and yes, it's occurred to me as well that this sort of system would be a good way to evolve arsenate-using bacteria, if they do really exist. The problem (as it is with the current work) is getting truly phosphate-free media. But if you had such, and ran the experiment, I'd suggest isolating small samples along the way and starting them fresh in new apparatus, in order to keep the culture from living off the phosphate from previous generations. Trying to get rid of one organic molecule is hard enough; trying to clear out a whole element is a much harder proposition).
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October 6, 2010
I mentioned directed evolution of enzymes the other day as an example of chemical biology that’s really having an industrial impact. A recent paper in Science from groups at Merck and Codexis really highlights this. The story they tell had been presented at conferences, and had impressed plenty of listeners, so it’s good to have it all in print.
It centers on a reaction that’s used to produce the diabetes therapy Januvia (sitagliptin). There’s a key chiral amine in the molecule, which had been produced by asymmetric hydrogenation of an enamine. On scale, though, that’s not such a great reaction. Hydrogenation itself isn’t the biggest problem, although if you could ditch a pressurized hydrogen step for something that can’t explode, that would be a plus. No, the real problem was that the selectivity wasn’t quite what it should be, and the downstream material was contaminated with traces of rhodium from the catalyst.
So they looked at using a transaminase enzyme instead. That’s a good idea, because transaminases are one of those enzyme classes that do something that we organic chemists generally can’t usually do very well – in this case, change a ketone to a chiral amino group in one step. (It takes another amine and oxidizes that on the other side of the reaction). We’ve got chiral reductions of imines and enamines, true, but those almost always need a lot of fiddling around for catalysts and conditions (and, as in this case, can cause their own problems even when they work). And going straight to a primary amine can be, in any case, one of the more difficult transformations. Ammonia itself isn’t too reactive, and you don’t have much of a steric handle to work with.
But transaminases have their idiosyncracies (all enzymes do). They generally only will accept methyl ketones as substrates, and that’s what these folks found when they screened all the commercially available enzymes. Looking over the structure (well, a homology model of the structure) of one of these (ATA-117), which would be expected to give the right stereochemistry if it could be made to give anything whatsoever, gave some clues. There’s a large binding pocket on one side of the ketone, which still wasn’t quite large enough for the sitagliptin intermediate, and a small site on the other side, which definitely wasn’t going to take much more than a methyl group.
They went after the large binding pocket first. A less bulky version of the desired substrate (which had been turned, for now, into a methyl ketone) showed only 4% conversion with the starting enzymes. Mutating the various amino acids that looked important for large-pocket binding gave some hope. Changing a serine to phenylalanine, for example, cranked up the activity by 11-fold. The other four positions were, as the paper said, “subjected to saturation mutagenesis”, and they also produced a combinatorial library of 216 multi-mutant variations.
Therein lies a tale. Think about the numbers here: according to the supplementary material for the paper, they varied twelve residues in the large binding pocket, with (say) twenty amino acid possibilities per. So you’ve got 240 enzyme variants to make and test. Not fun, but it’s doable if you really want to. But if you’re going to cover all the multi-mutant space, that’s twenty to the 12th, or over four quadrillion enzyme candidates. That’s not going to happen with any technology that I can easily picture right now. And you’re going to want to sample this space, because enzyme amino acid residues most certainly do affect each other. Note, too, that we haven’t even discussed the small pocket, which is going to have to be mutated, too .
So there’s got to be some way to cut this problem down to size, and that (to my mind) is one of the things that Codexis is selling. They didn’t, for example, get a darn thing out of the single-point-mutation experiments. But one member of a library of 216 multi-mutant enzymes showed the first activity toward the real sitagliptin ketone precursor. This one had three changes in the small pocket and that one P-for-S in the large, and identifying where to start looking for these is truly the hard part. It appears to have been done through first ruling out the things that were least likely to work at any given residue, followed by an awful lot of computational docking.
It’s not like they had the Wonder Enzyme just yet, although just getting anything to happen at all must have been quite a reason to celebrate. If you loaded two grams/liter of ketone, and put in enzyme at 10 grams/liter (yep, ten grams per liter, holy cow), you got a whopping 0.7% conversion in 24 hours. But as tiny as that is, it’s a huge step up from flat zero.
Next up was a program of several rounds of directed evolution. All the variants that had shown something useful were taken through a round of changes at other residues, and the best of these combinations were taken on further. That statement, while true, gives you no feel at all for what this stuff is like, though. There are passages like this in the experimental details:
At this point in evolution, numerous library strategies were employed and as beneficial mutations were identified they were added into combinatorial libraries. The entire binding pocket was subjected to saturation mutagenesis in round 3. At position 69, mutations TAS and C were improved over G. This is interesting in two aspects. First, V69A was an option in the small pocket combinatorial library, but was less beneficial than V69G. Second, G69T was improved (and found to be the most beneficial in the next
round) suggesting that something other than sterics is involved at this position as it was a Val in the starting enzyme. At position 137, Thr was found to be preferred over Ile. Random mutagenesis generated two of the mutations in the round 3 variant: S8P and G215C. S8P was shown to increase expression and G215C is a surface exposed mutation which may be important for stability. Mutations identified from homologous enzymes identified M94I in the dimer interface as a beneficial mutation. In subsequent rounds of evolution the same library strategies were repeated and expanded. Saturation mutagenesis of the secondary sphere identified L61Y, also at the dimer interface, as being beneficial. The repeated saturation mutagenesis of 136 and 137 identified Y136F and T137E as being improved.
There, that wasn’t so easy, was it? This should give you some idea of what it’s like to engineer an enzyme, and what it’s like to go up against a billion years of random mutation. And that’s just the beginning – they ended up doing ten rounds of mutations, and had to backtrack some along the way when some things that looked good turned out to dead-end later on. Changes were taken on to further rounds not only on the basis of increased turnover, but for improved temperature and pH stability, tolerance to DMSO co-solvent, and so on. They ended up, over the entire process, screening a total of 36,480 variations, which is a hell of a lot, but is absolutely infinitesmal compared to the total number of possibilities. Narrowing that down to something feasible is, as I say, what Codexis is selling here.
And what came out the other end? Well, recall that the known enzymes all had zero activity, so it’s kind of hard to calculate improvement from that. Comparing to the first mutant that showed anything at all, they ended up with something that was about 27,000 times better. This has 27 mutations from the original known enzyme, so it’s a rather different beast. The final enzyme runs in DMSO/water, at loadings up of to 250g/liter of starting material at 3 weight per cent enzyme loading, and turns isopropylamine into acetone while it’s converting the prositagliptin ketone to product. It is completely stereoselective (they’ve never seen the other amine), and needless to say involves no hydrogen tanks and furnishes material that is not laced with rhodium metal.
This is impressive stuff. You'll note, though, the rather large amount of grunt work that had to go into it, although keep in mind, the potential amount of grunt work would be more than the output of the entire human race. To date. Just for laughs, an exhaustive mutational analysis of twenty-seven positions would give you 1.3 times ten to the thirty-fifth possibilities to screen, and that's if you know already which twenty-seven positions you're going to want to look at. One microgram of each of them would give you the mass of about a hundred Earths, not counting the vials. Not happening.
Also note that this is the sort of thing that would only be done industrially, in an applied research project. Think about it: why else would anyone go to this amount of trouble? The principle would have been proven a lot earlier in the process, and the improvements even part of the way through still would have been startling enough to get your work published in any journal in the world and all your grants renewed. Academically, you'd have to be out of your mind to carry things to this extreme. But Merck needs to make sitagliptin, and needs a better way to do that, and is willing to pay a lot of money to accomplish that goal. This is the kind of research that can get done in this industry. More of this, please!
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October 5, 2010
Here's an interesting example of a way that synthetic chemistry is creeping into the provinces of molecular biology. There have been a lot of interesting ideas over the years around the idea of polymers made to recognize other molecules. These appear in the literature as "molecularly imprinted polymers", among other names, and have found some uses, although it's still something of a black art. A group at Cal-Irvine has produced something that might move the field forward significantly, though.
In 2008, they reported that they'd made polymer particles that recognized the bee-sting protein melittin. Several combinations of monomers were looked at, and the best seemed to be a crosslinked copolymer with both acrylic acid and an N-alkylacrylamide (giving you both polar and hydrophobic possibilities). But despite some good binding behavior, there are limits to what these polymers can do. They seem to be selective for melittin, but they can't pull it out of straight water, which is a pretty stringent test. (If you can compete with the hydrogen-bonding network of bulk water that's holding the hydrophilic parts of your target, as opposed to relying on just the hydrophobic interactions with the other parts, you've got something impressive).
Another problem, which is shared by all polymer-recognition ideas, is that the materials you produce aren't very well defined. You're polymerizing a load of monomers in the presence of your target molecule, and they can (and will) link up in all sorts of ways. So there are plenty of different binding sites on the particles that get produced, with all sorts of affinities. How do you sort things out?
Now the Irvine group has extended their idea, and found some clever ways around these problems. The first is to use good old affinity chromatography to clean up the mixed pile of polymer nanoparticles that you get at first. Immobilizing melittin onto agarose beads and running the nanoparticles over them washes out the ones with lousy affinity - they don't hold up on the column. (Still, they had to do this under fairly high-salt conditions, since trying this in plain water didn't allow much of anything to stick at all). Washing the column at this point with plain water releases a load of particles that do a noticeably better job of recognizing melittin in buffer solutions.
The key part is coming up, though. The polymer particles they've made show a temperature-dependent change in structure. At RT, they're collapsed polymer bundles, but in the cold, they tend to open up and swell with solvent. As it happens, that process makes them lose their melittin-recognizing abilities. Incubating the bound nanoparticles in ice-cold water seems to only release the ones that were using their specific melittin-binding sites (as opposed to more nonspecific interactions with the agarose and the like). The particles eluted in the cold turned out to be the best of all: they show single-digit nanomolar affinity even in water! They're only a few per cent of the total, but they're the elite.
Now several questions arise: how general is this technique? That is, is melittin an outlier as a peptide, with structural features that make it easy to recognize? If it's general, then how small can a recognition target be? After all, enzymes and receptors can do well with ridiculously small molecules: can we approach that? It could be that it can't be done with such a simple polymer system - but if more complex ones can also be run through such temperature-transition purification cycles, then all sorts of things might be realized. More questions: What if you do the initial polymerization in weird solvents or mixtures? Can you make receptor-blocking "caps" out of these things if you use overexpressed membranes as the templates? If you can get the particles to the right size, what would happen to them in vivo? There are a lot of possibilities. . .
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