Category → Ripped from the Pages
Today’s issue examines the surge of interest in rare disease drugs, which in the past few years have attracted significant interest from biotech firms, big pharma, and venture capitalists alike. In addition to exploring the business and policy drivers behind increased investment in orphan drugs, the multi-part story looks at the critical role patient organizations play in drawing attention to rare diseases. As such, it seemed worth highlighting advice from various stakeholders on what patient groups can do to entice drug developers to work on their disease:
–Organize yourselves. Find as many patients as possible, and establish a registry that will make it easy for a drug firm to begin a clinical trial. “Beginning to identify people, getting them into a registry, and collecting natural history data is one of the most valuable things a developer can have when they’re thinking about a program,” says Genzyme’s CEO David Meeker. “Among the most helful things that patient advocates can do is to help us to understand the natural history of disease,” agrees Kevin Lee, CSO of Pfizer’s rare disease unit. “Without that understanding of how the disease progresses, and what the endpoints can be, its almost impossible to do drug development.”
–Find a way to collaborate with one another. In even the smallest of diseases, patient groups tend to proliferate. And while its natural and understandable for advocates to want to do all they can to help their own child or family member, it can lead to duplicative efforts. The disparate groups can also make it tougher for drug developers to access. “We all need to give everybody a lot of space here to do what they think is best, but in an optimal world, there are tremendous advantages to being coordinated,” Meeker says.
–Be connectors. Patient organizations have the amazing ability to bring together academics who had previous not collaborated. “What I have found over and over again is that patient advocates know the investigators in their field far better than the investigators themselves do,” says Christopher Austin, director of NIH’s National Center for Advancing Translational Science (NCATS). “They can be instrumental there.”
–Get the right researchers interested. Often only a handful of academic researchers are working on a given rare disease, and drug developers say attracting new scientists into the field, while also giving careful consideration about who to fund is key. Patient groups should look for someone who can use advocacy funds to attract larger grants. “If they can get some grant support, you’ll get more done,” says Emil Kakkis, CEO of Ultragenyx. “If they can’t get any grant support, you’ll have to wonder if it was just because the disease is rare, or another reason.”
–Don’t cut corners. As more patient groups directly fund and organize natural history studies and early clinical trials, they need to make sure the work they support is of the same caliber as that done by biotechs or pharma. “Every data point they generate may some day be helpful in getting a drug approved,” says Philip Reilly, venture partner at Third Rock Ventures.
–Take the reins. With the passage of FDASIA last year, FDA committed to allowing patients more of a seat at the table during regulatory discussions. But the role patient groups will play—how they will be allowed to particulate and how much influence they have—is still to be determined. Ritu Baral, analyst at Canaccord Genuity, thinks there’s opportunity in that vagueness. “Give an inch, take a mile. If they’re going to define it, then we can define it as a patient group,” Baral, who also sits on the board of a disease foundation, says. “We can set the markers where we want to set them.”
–Help drug developers understand your needs. Drug companies are partnering with patient organizations earlier on in the drug process than in the past, convening patient advisory boards to understand how best to design a clinical trial, says Amy Waterhouse, vice president of regulatory affairs at Biomarin. That design ins’t just about regulatory practicalities, but about what families need out of the design in order to participate—a three day visit to a hospital instead of four, for example, can make all the difference. “We learn so much from discussions [with patient groups] that we wouldn’t get from the literature,” Waterhouse says.
Largely because of that drug discovery relevance, however, Heptares is choosing to keep its structure somewhat close to the vest. Officials presented views of the structure, of a GPCR called Corticotropin Releasing Factor (CRF-1) receptor, at conferences on Friday and Monday. But Heptares CEO Malcolm Weir says his team has no immediate plans to publish the structure or to deposit coordinates into the repository known as the Protein Data Bank.
The structure, Weir says, is another success for Heptares’ GPCR stabilizing technology, StaR. The technique involves targeted mutations that help to trap a GPCR in a single biologically-relevant state. In the case of CRF-1, Weir says, the stabilized receptor is captured in the “off” state.
The structure itself, which is at a resolution of 3 Ångstroms, has the 7-helix membrane-spanning structure typical of GPCRs. However, CRF-1′s architecture is rather different from receptors in Family A, the only GPCR family for which X-ray structures had been available until now, Weir says. “The overall shape of the receptor looks different, the orientation of the helices looks different, and there are detailed differences within helices that are at analogous positions in Family A receptors,” he says. He notes that there are differences in helices 6 and 7, which undergo important motions during GPCR activation.
“This is an important breakthrough, although fine details of the structure and release of coordinates may still be some time away,” says Monash University’s Patrick Sexton, an expert in Family B GPCRs who was at Friday’s talk. The structure, he says, confirmed researchers’ expectations that the major differences in membrane-spanning helices between Family A and Family B receptors would occur on the extracellular side. “There was a very open and relatively deep extracellular binding pocket, with the receptor having a ‘V’ shaped appearance,” he says. This open pocket likely contributes to medicinal chemists’ difficulties obtaining high affinity small molecule ligands for Family B receptors, he suggests.
That open pocket might be involved in another Family B GPCR mystery, according to Roger Sunahara, also in attendance Friday, who studies GPCRs’ molecular mechanisms at the University of Michigan, Ann Arbor. All Family B GPCRs, including CRF-1, have a large domain at their amino-terminus that contains large portions of their ligand binding sites. That domain was not included in this structure, he says, but “it would appear that deleted globular N-terminal domain would fit quite nicely into the open pocket.”
The CRF-1 receptor is a drug target for depression and anxiety, but at least one CRF antagonist failed to show benefit compared to placebo in a clinical trial. Weir says the impact of the CRF-1 structure for drug discovery will not necessarily be in CRF-1 drug discovery per se, but in the ability to develop relevant computer models of related targets.
It hasn’t been possible to make accurate models of Family B receptors with Family A information, explains Ryan G. Coleman, a postdoctoral fellow at UCSF who develops GPCR models, but who was not in attendance at the talks. Quality models could streamline small molecule drug discovery for the entire family, he explains. Most of the natural ligands for Family B receptors are long peptides, which are notoriously tough to replace with small molecule drugs.
Experts like Coleman will have to wait for some time to learn about the structure for themselves, unless they happened to have a friend in the audience at Heptares’ talks. It’s not unheard of for there to be a gap of several months to two years between a structure’s announcement and publication.
“We’re delighted to have such an informative structure,” Weir says. “It’s very exciting.” He adds says Heptares is progressing toward a structure of the biggest fish in family B, GLP-1, in the “on” state.
Virulent bacteria are growing increasingly resilient against our best antibiotics. Each day seems to bring a new story: MRSA outbreaks, resistant salmonella, or tough-to-treat tuberculosis. Just last week, World Health Organization director-general Dr. Margaret Chan delivered an address in Copenhagen, where she cautioned: “We are losing our first-line antimicrobials . . . in terms of replacement antibiotics, the pipeline is virtually dry. The cupboard is nearly bare.” (Click here for The Haystack’s past coverage of the development of new antibacterials).
Why have our drugs stopped working?
Recent research from St. Jude’s (Science, 2012, 1110) attempted to answer that question. Using X-ray crystallography, a technique used to see structures at the atomic level, the researchers were able to capture a critical moment when a drug binds to DHPS, its bacterial enzyme target. The scientists could then predict how bacteria evolve to dodge further biocidal bullets.
The antibacterial medicines caught in the act by the St. Jude’s researchers are the sulfa drugs (see right), former front-line treatments many doctors push to the bottom of treatment regimens, due to increasingly resistant bacterial strains. Researchers knew resistance had something to do with the drugs’ mechanism of action; sulfa drugs mimic the binding of PABA – para-aminobenzoic acid, a compound found in many sunscreens (Chemical Note: PABA occurs naturally as bacterial vitamin H1, and can also be found in yeast and plants. Chemists often borrow naturally-occurring compounds for industrial uses; two prominent examples are vanillin and Vitamin C).
Disruption of this PABA binding shuts down bacterial DNA replication, stopping reproduction. Before now, however, no one had succeeded in growing crystals of the active site that actually showed the drugs interacting with the enzymatic intermediate.
Let’s take one more step back: how does PABA attach itself? The enzyme we’re discussing, DHPS, catalyzes bond formation between PABA and intermediates known as pterins (see picture, left). Earlier researchers believed that this molecular hook-up operated by an SN2 mechanism, a reaction where the PABA kicks out a small piece of the pterin to form a new C-N bond. We chemists would say that SN2 means concerted bond formation, meaning that PABA would bind at the same time as the leaving group (OPPi), well, leaves.
Turns out that picture’s not quite right: it’s more SN1-like, which means that the pterin first forms a positively-charged, enzyme-stabilized species! As you can imagine, this is no small feat, since the reaction works at physiological pH, in water, which could hydrate the intermediate (but doesn’t). Nope – instead, this charged molecule sits around waiting for a PABA – or a sulfa drug – to bind to it. When PABA binds, the complex exits the enzyme, but when the drug binds, it locks up the active site.
So how do these models help us to understand resistance?
The group noticed something odd: sulfathiazole (STZ) and sulfamethoxazole (SMX), two standard sulfas, both bound in the normal PABA cavity of DHPS. Unlike PABA, however, they hang their heterocyclic rings “outside” the normal pocket. The researchers built upon earlier observations by another group (Proc. Natl. Acad. Sci. U.S.A., 2010, 20986), speculating that the resistance might not have to do with the active site at all: it’s the external region, where the heterocycle bumps into the protein. To cheat death, all the bacterium needs to do is mutate an amino acid from this “outside” region (nearby proline and phenylalanine residues, see picture), which shuts down drug binding.
Could we design better drugs based on this model? Sure, we could synthesize a complimentary heterocycle, one that binds to the “outside” of mutant
enzymes (more polar for certain mutations, less for others). Another option? Cut the drug down to size: sulfonilamide, the grandfather of the sulfa drugs, should fit almost as snugly in the cavity as PABA, which might function perfectly against resistant bugs.
On Monday, we highlighted outtakes from our interview with Michael Ehlers, Pfizer’s CSO for neuroscience research, for our story on the state of neuroscience R&D. Today, we wanted to offer a view from academia: Jeff Conn is head of the Vanderbilt Center for Neuroscience Drug Discovery, which in the past several years has generated a number of CNS drug candidates.
While Ehler is focused on the growing body of genetic information that could pave the way for new neuroscience targets, Conn’s lab is taking a somewhat different approach. By scouring the literature for evidence–in humans–of a molecule or target’s activity, the lab then sinks substantial resources into understanding the basic biology driving that activity and designing molecules to exploit it.
In depression, for example, R&D has been stalled by a lack of new targets. But Conn’s lab is intrigued by studies showing that ketamine, an animal tranquilizer (and club drug), swiftly and effectively reduces the symptoms of major depressive disorder. “When I talk to scientists at Vanderbilt, its an approach they’re using for their most refractory patients,” Conn says.
A laundry list of side effects makes wider use of ketamine improbable. As such, Conn’s lab is looking at ways to design molecules that produce the same kind of results on depression without the adverse effects.
Conn, a former Merck researcher, also discussed ways that discovery efforts inside academia can build a scientific case for CNS programs that pharma might otherwise overlook. Vanderbilt scientists spend “twice as much effort in basic science than for the drug discovery itself, and to me, that’s absolutely critical,” Conn says. When the team finds that molecules have different profiles in vitro, they spend a lot of time trying to understand how that will translate into adverse effects in vivo. “In pharma, you have to stay on such a narrow, direct path, that you have to ignore all that,” Conn says. In the academic lab, researchers take a longer, more methodical approach that entails optimizing many different molecules, then putting those in animals to understand what properties a final drug candidate needs to have.
That approach has enabled Vanderbilt scientists to tackle drug targets that have tripped up industry. “mGluR5 is a good example where, early on, we started seeing different properties of molecules in vitro,” he says. “Instead of putting blinders on and moving forward or ignoring it,” an avenue industry scientists are often forced to take, “we deliberately put a lot of effort into optimizing those properties.”
As a result, the Vanderbilt group and its collaborator, J&J, recently moved forward what Conn calls “very safe” schizophrenia drug candidates targeting mGlur5. “I don’t think we ever could have done that in my pharma days because its too far off the critical path,” he says.
In this week’s issue, I look at the perceived exodus by pharma companies from neuroscience R&D. Between AstraZeneca’s recent cutbacks, the closure of Novartis’ neuroscience research facility in Basel, and earlier moves by GSK and Merck, industry watchers are understandably worried that the neuroscience pipeline will dry up.
One person who isn’t worried is Michael Ehlers, Pfizer’s chief scientific officer for neuroscience research. Ehlers came to Pfizer a year and a half ago from Duke, with the explicit mission to revamp how the company finds and develops drugs for brain diseases. The scientist is convinced that the field is ripe for new and better drugs, and that by staying in the game, Pfizer will be in a good position to capitalize on what he believes will be a healthy flow of new discoveries.
Many drug companies argue that the risk in neuroscience simply doesn’t justify the investment. The overarching sentiment is that the brain is still a black box: good targets are few and far between; clinical trials are long and unpredictable; regulatory approval is tough; and generic competition is plentiful. For many big pharma firms, the math just doesn’t add up.
“I personally don’t find that calculus to give you the total picture,” Ehlers says. Shifting resources away from neuroscience to focus on areas like oncology, where the environment looks favorable—clear clinical trial endpoints, the opportunity for fast-track approval, an easier chance for reimbursement from payors—only makes sense in the short term, Ehlers says. But that thinking “is short sighted as to where the fundamental state of biology is in neuroscience,” he says.
Why is Ehlers so encouraged about a field that so many are walking away from? He believes that neuroscience is poised to benefit from the kind of genetic links that generated so many targets—and eventually so many targeted-drugs—in oncology. “There is going to be kind of a revolution in the next five years—it’s not going to be tomorrow…but you have to think about that inflection of opportunity over the five-to-ten year time horizon.”
To take advantage of each new genetic clue, Ehlers has revamped Pfizer’s approach to neuroscience R&D. As this week’s story explains:
In the past, big pharma often gave its scientists a mandate to work in areas such as Alzheimer’s or schizophrenia, regardless of tractable drug targets. Now at Pfizer, Ehlers says, his team is “indication agnostic.” Any program that Pfizer undertakes must have a critical mass of biological knowledge—for example, human genetics, human phenotyping, and evidence of dysfunctional neurocircuits—to convince Ehlers it’s worth pursuing. “We start there,” he says. “That hasn’t always been the case.”
Moreover, Pfizer no longer relies on mouse models as predictors for responses in humans. “We’ve for the most part stopped all rodent behavior as a model for disease and are much more about what’s happening in the brain,” he says. Scientists measure human responses to prove experimentally that a drug works.
Pfizer’s goal, according to Ehlers, is to tackle fewer projects but have more confidence in their potential for success. The result should be a drug pipeline “rooted in something more than optimism.”
He cites Huntington’s disease as one area that, even before coming to Pfizer, he saw as a prime scientific opportunity. “You know the gene, you know a fair bit about what’s going on, you have a wealth of data, tons of models, a clear clinical course, and an identifiable patient population,” he says. “If we can’t deal with that, we’re in trouble.”
Medicinal chemists strive to optimize molecules that fit snugly into their proposed targets. But in the quest for potency, we often overlook the local physics that govern drugs’ binding to these receptors. What if we could rationally predict which drugs bind well to their targets?
A new review, currently out on J. Med. Chem. ASAP, lays out all the computational backing behind this venture. Three computational chemists (David Huggins, Woody Sherman, and Bruce Tidor) break down five binding events from the point-of-view of the drug target: Shape Complementarity, Electrostatics, Protein Flexibility, Explicit Water Displacement, and Allosteric Modulation….whew!
Note: Before we dive into this article, let’s clarify a few terms computational drug-hunters use that bench chemists think of differently: ‘decoy’ – a test receptor used to perform virtual screens; ‘ligand’ – the drug docking into the protein; ‘affinity / selectivity’ – a balance of characteristics, or how tightly something binds vs. which proteins it binds to; ‘allosteric’ – binding of a drug molecule to a different site on an enzyme than the normal active site. Regular readers and fans of compu-centric chem blogs such as The Curious Wavefunction and Practical Fragments will feel right at home!
We’ll start at the top. Shape complementarity modeling uses small differences in a binding pocket, such as a methylene spacer in a residue (say, from a Val to Ile swap) to dial-in tighter binding between a target and its decoy. The authors point out that selectivity can often be enhanced by considering a drug that’s literally too big to fit into a related enzymatic cavity. They provide several other examples with a ROCK-1 or MAP kinase flavor, and consider software packages designed to dock drugs into the “biologically active” conformation of the protein.
Electrostatic considerations use polar surface maps, the “reds” and “blues” of a receptor’s electronic distribution, to show how
molecular contacts can help binding to overcome the desolvation penalty (the energy cost involved in moving water out and the drug molecule in). An extension of this basic tactic, charge optimization screening, can be used to test whole panels of drugs against dummy receptors to determine how mutations might influence drug binding.
Because target proteins move and shift constantly, protein flexibility, the ability of the protein to adapt to a binding event, is another factor worth considering. The authors point out that many kinases possess a “DFG loop” region that can shift and move to reveal a deeper binding cavity in the kinase, which can help when designing binders (for a collection of several receptors with notoriously shifty binding pockets – sialidase, MMPs, cholinesterase – see p. 534 of Teague’s NRDD review).
But these shifting proteins also swim in a sea of water and other cytoplasmic goodies. This means that drug designers, whether they like it or not, must account for explicit water molecules. The authors even suggest a sort of “on-off” switch for including the bound water molecules, but contend that more efforts should be directed to accurate modeling of water in these protein settings.
Finally, the authors weigh the effects of allosteric binding, the potential for a modeled molecule to be highly selective for a site apart from where the protein binds its native ligand. The authors consider the case of a PTP1B ligand that binds 20Å away from the normal active site, at the previously mentioned “DFG loop.” Since this binding hadn’t been seen for related phosphatases, it could then be used to control selectivity for PTP1B.
In each section, the authors provide examples of modeling studies that led to the design of a molecule. Two target classes recur often throughout the review: HIV protease inhibitors (saquinavir, lopinavir, darunavir) and COX-2 inhibitors (celecoxib), which have all been extensively modeled.
Two higher-level modeling problems are also introduced: the substrate-envelope hypothesis, which deals with rapidly mutating targets, and tailoring molecules to take rides in and out of the cell using influx and efflux pumps in the membrane. Since different cell types overexpress certain receptors, we can use this feature to our advantage. This strategy has been especially successful in the development of several cancer and CNS drugs.
Overall, the review feels quite thorough, though I suspect regular Haystack readers may experience the same learning curve I did when adapting to the field-specific language that permeates each section. Since pictures are worth a thousand words, I found that glancing through the docking graphics that accompany each section helped me gain a crucial foothold into the text.
In my story on how drugs get their generic names for this week’s issue of C&EN, I briefly discussed how the chronic myelogenous leukemia medication Sprycel (dasatinib), mentioned in this Haystack post by SeeArrOh, ended up being named after Bristol-Myers Squibb research fellow Jagabandhu Das. Even though Das, or Jag, as his coworkers call him, didn’t discover the molecule that bears his name, the program leader for Das’s team, Joel Barrish, says dasatinib wouldn’t have existed without him.
So how’d Das make a difference? About one and a half years into the search for a kinase inhibitor that might be able to treat chronic myelogenous leukemia, “we were hitting a wall,” Barrish, today vice-president of medicinal chemistry at BMS, recalls. “We couldn’t get past a certain level of potency.”
Early on, the team’s work suggested that a 4′-methyl thiazole was critical for potency. Replace the methyl with a hydrogen, and potency went out the window. But Das challenged that dogma, Barrish says. He thought the compound series had evolved to the point where it would be a good idea to go back and test those early assumptions. His hunch paid off– in the new, later kinase inhibitor series, it turned out that removing the methyl group from the thiazole actually boosted potency. Thanks in large part to that discovery, the team eventually was able to make kinase inhibitors with ten thousand fold higher activity.“Jag didn’t stop there,” Barrish says. After debunking the methyl dogma, Das found a way to replace an undesirable urea moiety in the team’s inhibitors with a pyrimidine group, which improved the inhibitors’ physical properties. With help from Das’s two insights combined, eventually BMS’s team came up with the molecule that became dasatinib (J. Med. Chem., DOI: 10.1021/jm060727j).
Generic naming requirements are extensive, but the committees involved in the naming process are willing to use inventors’ names as long as they fit the criteria.
But sometimes, Barrish says, “there’s luck involved in who makes the final compound.” In the dasatinib story, though, it was clear that Das’s discoveries were the keys to success.
When dasatinib was in clinical trials and it came time to put forward a set of possible generic names for consideration, Barrish didn’t have to think too hard about who was most responsible for his team’s success. “It was very clear in my mind that it was Jag,” he says. So he added dasatinib to the list.
“I admit, it was one of those things you do and you kind of forget about it, thinking, ‘oh, they’ll pick something else’,” Barrish says. When dasatinib ended up being the name of choice, he says, it made the entire team feel good. “And obviously, Jag was quite pleased with it.”
The “morning-after” pill, used to prevent conception when other planning methods fail, became a political lightning rod this week. Reports by Pharmalot, NPR, Reuters, and many others relate how the Secretary of the U.S. Department of Health and Human Services blocked an FDA recommendation to provide over-the-counter access to this treatment to a wider range of patients (currently, women under the age of 17 must have a prescription to obtain Plan B).
After the uproar generated by the announcement, I wondered what, exactly, was this contentious molecule, and what did it do?
In the US, hospitals administer Plan B as two small pills, each with a 750 μg dose of the synthetic hormone levonorgestrel. First approved by the FDA in 1999, levonorgestrel prompted several companies, among them generic manufacturers Barr, Watson, and Teva, to jump in as suppliers in the ensuing decade. According to a 2011 Teva patent, Plan B is most effective when taken within 72 hours of when a person’s first-line contraceptive fails. The FDA estimates its success rate at 80-90%.
Levonorgestrel binds to the same receptors as other sex hormones (think estradiol or progesterone), and prevents ovulation or impairs fertilization of egg cells. Some researchers believe that Plan B prohibits already-fertilized eggs from adhering to the endometrium (uterine inner wall), which might prevent further embryonic development leading to pregnancy. In fact, a large dose of 17-α-ethinylestradiol (EE) – the main ingredient in most birth control pills – can sometimes be used “off-label” to achieve the same effect.
The uncertainty over whether Plan B actually terminates pregnancies brings it onto similar ground with mifepristone (RU-486) and diethylstilbestrol (DES). These two drugs, previously popular options for emergency contraception, have mixed public perception today; many associate RU-486 with abortion, and DES with endocrine disorders and tumor formation in offspring.
Chemistry Note: It’s humbling to watch Mother Nature re-use the same chemical templates over and over, and that small changes in the overall steroid structure lead to huge biochemical consequences. Like Batman, with his never-ending supply of utility-belt gadgets, the steroid core structure can be tweaked in seemingly endless ways to produce biologically active molecules. I would have to devote (several) more posts to just how many modifications, but think about the effects simple oxidation (bile acids), ring expansion (cortistatins), or conjugation (sulfonated sterols) have on biological processes.
The sex hormones have been puzzling synthetic chemists for nearly 100 years; in fact, two prominent chemists spent large portions of their careers perfecting the introduction of a single methyl group into the steroid core! Levonorgestrel claims “second-generation” hormone status; next-gen progestins, such as desogestrel, do away completely with C-3 oxygenation, and sport a new alkene at C-11. These new atomic decorations lead to improved side-effect profiles and lower the overall EE dose in combined pill formulations.
Update (6:05PM, Dec 9, 2011) – Changed “mg” to “μg” (Thanks, Ed!)
Takeda Pharmaceutical today announced it has begun Phase III clinical trials of TAK-875, a first-in-class drug candidate for treating type 2 diabetes. The experimental therapy activates GPR40, a G-protein-coupled receptor that resides in pacreatic islet cells.
The TAK-875 story is as much about the biology of the target as it is about the molecule itself. And it’s a story that owes much to the company’s willingness to delve into uncharted territory.
In the early 2000s, scientists knew GPR40 existed, but didn’t know what GPR40′s purpose was in the body. Plenty of proteins fit this description– they’re called “orphan receptors” in the industry parlance. Much of Takeda’s drug discovery strategy is based on figuring out what orphan receptors do.
In a 2003 paper in Nature (DOI: 10.1038/nature01478), Takeda laid out what it learned about GPR40. The receptor responds to a variety of long-chain fatty acids. In response to fatty acid binding, GPR40 activates and boosts insulin secretion from pancreatic beta cells.
GPR40 became a viable drug target for Takeda for several reasons. First, one of the hallmarks of type 2 diabetes is a reduction in insulin secretion from pancreatic beta cells, something GPR40 activation could help counter. Second, G-protein-coupled receptors are established drug targets– and GPR40 happens to be in the class of GPCRs for which researchers know the most about structure– the Class A, or rhodopsin-like, GPCRs. (Note: other GPR-type receptors are diabetes targets as well– C&EN contributing editor Aaron Rowe has written about Arena Pharmaceuticals’ activators of GPR119 as diabetes drug candidates.)
Takeda used structural knowledge to its advantage in the discovery of TAK-875 (ACS Med. Chem. Lett., DOI: 10.1021/ml1000855). Researchers were able to build a model of GPR40 based on its similarity to GPCRs of known structure, and dock potential drug candidates inside to see how well they could bind.
This is far from the only drug discovery story that has to do with “de-orphanizing” orphan receptors. In fact, as far back as 1997, pharmaceutical company researchers were writing about orphan receptors as a neglected drug discovery opportunity (Trends Pharmacol. Sci., DOI: 10.1016/S0165-6147(97)90676-3). And of course, just because researchers have “de-orphanized” a receptor doesn’t mean all of the complex biology is pinned down. Case in point: the PPAR receptors (J. Med. Chem., DOI: 10.1021/jm990554g). Despite these receptors’ promise as targets for obesity and diabetes, drugs designed to target them have tanked in development or had unexpected problems after arrival on the market (read: Avandia).
So as TAK-875 enters Phase III trials, the news might be about the drug candidate’s clinical performance, but you can be sure that Takeda’s researchers are still working hard to unravel as much of GPR40′s basic biology as they can behind the scenes.