A step towards incorporating dynamics data into drug design

My field-cycling article (previous post) is part of a dynamics-focused topical issue of JBNMR. In my next few science posts I'll describe some of the other contributions.

Research into the interplay between protein structural dynamics and function is a window into important fundamental knowledge about biochemistry, but the general justification for public funding of these studies by medical agencies is that they will have the ultimate effect of improving our ability to design and optimize drugs. However, even though our ability to characterize macromolecular dynamics has increased dramatically in the past few decades, there are few, if any, cases in which this knowledge has been applied successfully to the design of therapeutic agents. In part this is because incorporating data on fluctuations into the design algorithms poses a significant challenge. It's also true, though, that we understand only part of each system, i.e. the dynamics of the protein target, not the small molecules it binds. If dynamics studies are to make the maximum possible contribution to pharmaceutical sciences, the motions of the ligand must be characterized. In their article in Journal of Biomolecular NMR, Jeffrey Peng and students from Notre Dame attempt to address this shortcoming in the case of a substrate for the phosphorylation-directed prolyl isomerase Pin1.

Pin1 is implicated in a number of regulatory and signaling pathways, which seems strange because it doesn't possess any intrinsic transcriptional regulation ability, nor does it covalently add or remove phosphate groups. Instead, Pin1 has an enzymatic activity that accelerates, generally without altering the relative populations, the conversion of prolines from their cis- to trans- state and vice versa. This activity is specifically targeted to prolines that are adjacent to phosphorylated serines or threonines. In addition to the catalytic domain that does this work, Pin1 possesses a WW domain that has identical specificity. Because Pin1 does not alter the balance between cis- and trans- Pro, only the rate at which one changes to the other, its role in signaling has been difficult to ascertain, although there is intense interest in this area.

You don't need to understand an entire pathway to design an effective inhibitor. What you do need to understand is the relationship between specific chemical groups and binding affinity. Getting that knowledge can be very difficult if the proposed drug is flexible. In that case, refinement methods that focus only on the particular chemical groups rather than their dynamic properties could go badly astray. Unfortunately, the dynamics of protein-bound drug molecules are difficult to measure. Their proton signals are likely to be swamped by the protein, and small molecules are often difficult to label with isotopes convenient for NMR. Peng et al. propose to address this by studying ¹³C relaxation at natural abundance.

A little less than 99% of the world's carbon is in the form of NMR-inactive ¹²C, which is a problem for NMR because carbon is very abundant in proteins and drugs. Of the rest, most (about 1% of all carbon) is dipolar, NMR-detectable ¹³C, which is usually not enough to accomplish anything in terms of protein NMR. As a result, NMR researchers typically adopt the strategy of expressing their proteins using bacteria grown in media containing ¹³C₆ D-glucose. Such enrichment of drug molecules probably could not be carried out for pharmaceutical research due to the cost and the limited availability of properly labeled reagents. Fortunately, advances such as magnets stronger than 17 T and cryoprobes make sensitive detection of natural-abundance ¹³C a plausible approach. Because natural-abundance measurements also simplify the experiments and analysis considerably, Peng et al. adopt this approach in their study.

Peng et al. measure μs-ms fluctuations in a 10-residue peptide in the presence and absence of Pin1. Keeping in mind that such motions can only be detected when they are associated with a change of chemical shift, it is reasonable that no such motions are detected when the peptide is all by itself. In the presence of Pin1, however, methyl groups on phospho-Thr 5 and Val 7 experience some kind of chemical exchange process on the order of several 100 /s (at 278 K), as does a methylene group in Pro 6.

Peng et al. rationalize their observations with reference to a previously-determined structure of the Pin1 WW domain in complex with this peptide (explore it at the PDB). As you can see from the lowest-energy member of this NMR ensemble (left), the residues where they detect these fluctuations in the methyls and methylenes are those that are most involved in the binding interaction. The WW domain is represented as blue ribbons, while the peptide is shown as sticks down at the bottom. That the Pro and pThr form part of the interface is unsurprising, as they constitute the specific binding sequence, while the Val side chain appears to be in position to make some hydrophobic contacts. Everything makes sense, but that doesn't mean it's telling us what we want to know.

The structure above shows us the interaction of the peptide with the WW domain, while what we're really interested in getting at is the catalytic domain. Using an exchange spectroscopy experiment, Peng et al. determined that the ms dynamics they were observing probably reflected the binding of the peptide to the WW domain. To avoid this interaction, they created an artificial Pin1 that contained only the catalytic domain, and found that this also caused chemical exchange in the methyls and methylenes. Cross-checking against the exchange spectroscopy rates suggested that the ms dynamics in this case reflect the result of Pin1 catalytic activity, namely the interconversion from cis to trans and vice versa.

Unfortunately, this experiment did not report the most desired data, i.e. the dynamics of the ligand on the enzyme. On-enzyme fluctuations certainly contribute to the exchange experienced by the ligand, but because the on-enzyme population is so small (at most 2.5% of ligand) this would only be detectable in the case of an extremely large change in chemical shift. In principle one could deconvolute the dynamics from a partial-occupancy system where 50% or more of the ligand is bound to enzyme, but reliably fitting all the parameters for a two-state chemical exchange system from CPMG data is an already-dicey proposition. Fitting a four-state process from data like these is unlikely to be practical. So, in order to observe on-enzyme dynamics the drug of interest will need be saturated with its target protein, which would require millimolar protein concentrations for most ligands. Under those conditions, the spectra will also contain significant signal from the protein. The 70% deuteration used in this experiment, combined with ¹³C depletion, will probably be enough to suppress this, although these isotopes will increase the cost of the technique (and diminish protein yields).

Nevertheless, this paper establishes that the natural-abundance approach to measuring ligand dynamics on the µs-ms timescale is feasible. Because methylenes and methyls are common moieties in drugs and small molecules this technique may have broad applicability. Investigating the motions of small molecules bound to large proteins poses a unique problem because these systems don't have the advantages of either small molecules (low R₂) or proteins (exotic labeling schemes). The ongoing work of Peng et al. suggests that this problem is tractable, which may have positive consequences for our ability to design and optimize drugs.

Peng, J., Wilson, B., & Namanja, A. (2009). Mapping the dynamics of ligand reorganization via ¹³CH₃ and ¹³CH₂ relaxation dispersion at natural abundance Journal of Biomolecular NMR DOI: 10.1007/s10858-009-9349-4

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NSAIDs vs. Alzheimer's: Multiple modes of action?

Loads of interesting stuff is going on in Alzheimer's research right now. While the hot news is about a trial showing significant benefits from going after tau tangles, a recent paper in PLoS ONE continues to investigate the pathology of the amyloid-β peptide. As I've mentioned in previous posts, cleavage of the amyloid precursor protein to a 42-residue peptide (called Aβ1-42 in this paper) initiates the formation of peptide oligomers and eventually plaques. Recent research has indicated that these oligomers are sufficient to cause the development of Alzheimer's disease, but the mechanism by which they do so remains uncertain. Sara Sanz-Blasco and colleagues show that Aβ oligomers disrupt calcium homeostasis in neurons, damaging the mitochondria and promoting apoptosis, and that certain NSAIDs can suppress these adverse mitochondrial effects (1). PLoS ONE is open access, so go ahead, open the article up in another window, and follow along.

Although the appearance of plaques and neuronal death are classic hallmarks of Alzheimer's pathology, the relationship between these features is not well understood. For instance, it is possible the plaques themselves kill neurons or impair neural function. However, it seems equally likely that the appearance of plaques and the death of neurons are two distinct effects with a single cause. This view is supported by the oligomer toxicity study, but that study fails to resolve the question of exactly how Aβ oligomers kill neurons. Previous work has associated Aβ with derangement of cellular calcium (Ca²⁺) management — a 2005 paper by Demuro et al. (2) showed that soluble Aβ induced an increase in intracellular Ca²⁺ in a neuroblastoma cell line. Sanz-Blasco et al. therefore decided to directly test whether Aβ oligomers were increasing Ca²⁺ levels in neurons, and specifically in mitochondria. In order to do this last bit they used a low-affinity aequorin targeted specifically to mitochondria.

Allow me digress... to many of my readers that probably sounds like a terrible idea. If you're trying to detect a particular chemical in the cell, it seems like the best thing to do would be to get a high-affinity binding partner. And if figuring out whether there is any calcium in the mitochondria is what you want to do, then a high-affinity detector makes sense. However, when you're using a small amount of a sensor to detect changes in the concentration of a large amount of ligand, a low-affinity sensor is what you want.

To see why, take a look at the graph on the right. This is just a rough calculation based on a situation where the detector is at a concentration of 100 µM and the concentration of its ligand (that you're trying to detect) changes from 10 mM to 100 mM. Note that the concentration of the detector is at most 1% that of the ligand. If the dissociation constant K_D of this complex is 1 mM (blue) (a lower K_D means higher affinity), then the detector is almost saturated when you start, and the percentage occupied doesn't change very much over the course of the experiment. This means that it will be very difficult to tell the difference between, say, 50 mM ligand and 100 mM ligand, because that amounts to a signal difference of 1% of the maximum response. The situation gets a little better if the K_D is 10 mM (green). The lowest affinity detector here (K_D = 50 mM, red) actually does the best job of distinguishing between 50 mM and 100 mM ligand, because the difference in response amounts to 17% of the total dynamic range. Ideally, you want to tune the K_D of your detector in such a way that its response to changes in ligand concentration is large and linear over the range you are likely to be observing. For the last detector, this range lies between 10 and 40 mM of ligand, so that would likely be the ideal range to investigate with it.

The precise numbers are different in the present paper, but the principle is the same. The affinity you want in your detector will depend on what you are trying to detect and the circumstances under which you are trying to detect it. In this case, the researchers are trying to measure changes in calcium ions over a fairly wide range, which have a pretty high concentration in mitochondria, and they're doing it using a luminescent protein, which isn't very concentrated. As a result, a relatively low-affinity detection system is best.

So, what did they find? The results in Figure 1 show that Aβ oligomers and fragments cause an influx of calcium into the cytoplasm of cultured neurons, but preparations of Aβ fibrils did not cause this effect. Moreover, exposure of the cells to Aβ oligomers caused a clear influx of calcium into the mitochondria (Figure 3). This is a problem for a cell because Ca²⁺ overload in mitochondria can cause programmed cell death, or apoptosis. Using the classic TUNEL assay, the authors of this study showed that the Aβ oligomers caused apoptosis. In addition, they showed that treatment with the oligomers caused the release of mitochondrial cytochrome c (a step in the apoptotic pathway) and that the addition of cyclosporin A, which inhibits the release of proteins from the mitochondrion, blocked cell death (Figure 4). Together, these pieces of evidence support the idea that Aβ-induced Ca²⁺ influx into the mitochondria activates the apoptotic cascade, leading to neuronal death. These results are consistent with a very cool study published this week in Neuron (3) showing that amyloid plaques correlated with high neuronal Ca²⁺ levels in vivo (in live mice).

On its own this is pretty interesting, but Sanz-Blasco et al. push it a bit further. Because they had shown previously that some NSAIDs prevent mitochondrial Ca²⁺ uptake in a cancer cell line, they decided to find out if they would work in this instance, too. As you can see from Figure 6, the three NSAIDs tested kept the mitochondria calcium-free, even if the cells were treated with Aβ oligomers. NSAIDs also prevented cytochrome c release and cell death (Figure 8).

Some readers may recall that Kukar et al. showed that certain NSAIDs prevent oligomerization of Aβ1-42, hinting at a possible explanation of these results. However, the controls performed by Sanz-Blasco et al. show that under the conditions of these experiments the NSAIDs they used have no effect on cytosolic Ca²⁺ concentrations (Figure 7). If it is amyloid oligomers that let Ca²⁺ through plasma membranes, then this would appear to rule out structural disruption as a mechanism. Instead, Sanz-Blasco et al. propose that these NSAIDs specifically alter the polarity of the mitochondrial membrane in such a way as to prevent Ca²⁺ uptake.

If this is true, then NSAIDs may be able to perform a double-whammy on Alzheimer's disease. On the one hand, they appear to be capable of altering Aβ cleavage patterns to reduce the formation of toxic oligomeric precursors. In addition, they appear to have an ability to block mitochondrial breakdown and subsequent apoptosis directly. While this is encouraging, and speaks to the value of pursuing refinements of existing NSAIDs as possible Alzheimer's treatments, this experiment doesn't necessarily prove any therapeutic value. Even if the neurons are saved from death, the calcium flood may impair their function to such a degree that their continued survival doesn't matter. Only clinical trials and further research can firmly establish whether current or optimized NSAIDs can provide significant protection against Alzheimer's disease.

1. Sara Sanz-Blasco, Ruth A. Valero, Ignacio Rodríguez-Crespo, Carlos Villalobos, Lucía Núñez (2008). Mitochondrial Ca2+ Overload Underlies Aβ Oligomers Neurotoxicity Providing an Unexpected Mechanism of Neuroprotection by NSAIDs PLoS ONE, 3 (7), 0-0 DOI: 10.1371/journal.pone.0002718 OPEN ACCESS

2. A. Demuro, E. Mina, R. Kayed, S.C. Milton, I. Parker, C.G. Glabe (2005). Calcium Dysregulation and Membrane Disruption as a Ubiquitous Neurotoxic Mechanism of Soluble Amyloid Oligomers Journal of Biological Chemistry, 280 (17), 17294-17300 DOI: 10.1074/jbc.M500997200 OPEN ACCESS

3. K Kuchibotla, S Goldman, C Lattarulo, H Wu, B Hyman, B Backsai (2008). Aβ Plaques Lead to Aberrant Regulation of Calcium Homeostasis In Vivo Resulting in Structural and Functional Disruption of Neuronal Networks Neuron, 59 (2), 214-225 DOI: 10.1016/j.neuron.2008.06.008

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NSAIDs bind to amyloid-β

One of the best-known features of Alzheimer's disease pathology is the formation of proteinaceous amyloid plaques in the brain. In Alzheimer's disease these plaques are primarily formed by the amyloid-β peptide (Aβ) derived from the amyloid precursor protein (APP) by the action of β- and γ-secretase. The length of the Aβ peptide varies, but the 42-residue form (Aβ42) is more likely to form plaques and fibrils. Although it remains uncertain whether plaques are a cause of Alzheimer's disease symptoms, or merely an effect of some underlying derangement, finding some way to prevent or reduce plaque formation is a major goal in the field. This week in Nature, a team of researchers from institutions all over the US and Europe show that non-steroidal anti-inflammatory drugs (NSAIDs) may be able to accomplish these goals by binding to APP and Aβ directly.

Previous research from the Koo lab indicated that some NSAIDs specifically reduced the production of the amyloidogenic Aβ42 fragment (1) both in cultured cells and in a mouse model of the disease. APP was still processed into peptides, but these were shorter and less likely to form amyloid plaques than Aβ42. Significantly, the cleavage of other γ-secretase targets was not affected, meaning that side-effects of NSAID treatment might be minimal. Although NSAIDs were expected to ameliorate Alzheimer's symptoms by reducing inflammation, Weggen et al. found that the beneficial effects were not the result of cyclooxygenase inhibition. In a follow-up paper (2), Weggen et al. used experiments on cultured cells to show that the drugs were directly modulating γ-secretase activity. These experiments also showed that mutations to presenilin-1, a core component of the γ-secretase complex, could either increase or decrease the effect of NSAIDs, suggesting that it was the protein directly affected by these drugs.

Kukar et al. set out to test this hypothesis using photaffinity labeling. They took a few compounds known to alter Aβ42 levels and added a functional group that would react with a protein in the presence of UV light. These covalently-labeled proteins could then be detected, and this would serve as a relatively easy way to determine which component of the γ-secretase complex was actually binding NSAIDs. Like many cleverly-designed experiments, this failed in an interesting way: no known components of the γ-secretase complex were labeled. Fortunately, the researchers realized that there was another component to the complex they hadn't tested yet: the substrate.

It turned out that the NSAIDs could label a 99-residue fragment of APP. Moreover, this labeling was reduced by other γ-secretase modulators (GSMs) and unaffected by non-GSM NSAIDs. Using a series of progressively shorter constructs, Kukar et al. localized the binding activity of GSMs to residues 28-36 of amyloid-β.

This on its own is a very useful finding because it provides a target for refinement of these compounds. Knowing where and to what protein a possible drug binds makes it easier to develop assays to test new potential drugs, as well as enabling structure-based design. However, the authors took the next step and asked whether these drugs, because they bind to a region of APP known to be involved in the formation of amyloid plaques, might inhibit plaque formation directly. In cultured cells, they found that treatment with certain substrate-targeting GSMs decreased the formation of Aβ dimers and trimers even under conditions where the overall concentration of Aβ42 was not altered.

This suggests that these GSMs may be able to fight the buildup of amyloid plaques in two ways. By altering where γ-secretase cleaves APP, they reduce the concentration of Aβ42. Moreover, by interfering with Aβ oligomerization they fight the formation of plaques directly. With luck, further work in medicinal chemistry will arrive at compounds that enhance both these activities. The development of compounds that significantly reduce or prevent the formation of amyloid plaques will be a great step forward for Alzheimer's research. Even if such drugs do not prove to be a cure, a clear indication that plaques don't cause Alzheimer's would be a critical insight.

I want to emphasize that although these results are quite promising, they do not prove the efficacy of NSAIDs in ameliorating actual Alzheimer's symptoms. Transforming these findings into a cure or even an effective treatment will require a great deal of additional research, if it is even possible. You should not attempt to treat Alzheimer's with NSAIDs, or begin a regimen of NSAIDs or any other kind of drug or supplement, unless you have first discussed the possible risks and benefits with your doctor. And no, Minnesota, I do not mean a naturopath.

1. Weggen, S., Eriksen, J.L., Das, P., Sagi, S.A., Wang, R., Pietrzik, C.U., Findlay, K.A., Smith, T.E., Murphy, M.P., Bulter, T., Kang, D.E., Marquez-Sterling, N., Golde, T.E., Koo, E.H. (2001). A subset of NSAIDs lower amyloidogenic Aβ42 independently of cyclooxygenase activity. Nature, 414(6860), 212-216. DOI: 10.1038/35102591

2. Weggen, S. (2003). Evidence That Nonsteroidal Anti-inflammatory Drugs Decrease Amyloid β42 Production by Direct Modulation of γ-Secretase Activity. Journal of Biological Chemistry, 278(34), 31831-31837. DOI: 10.1074/jbc.M303592200 OPEN ACCESS

3. Kukar, T.L., Ladd, T.B., Bann, M.A., Fraering, P.C., Narlawar, R., Maharvi, G.M., Healy, B., Chapman, R., Welzel, A.T., Price, R.W., Moore, B., Rangachari, V., Cusack, B., Eriksen, J., Jansen-West, K., Verbeeck, C., Yager, D., Eckman, C., Ye, W., Sagi, S., Cottrell, B.A., Torpey, J., Rosenberry, T.L., Fauq, A., Wolfe, M.S., Schmidt, B., Walsh, D.M., Koo, E.H., Golde, T.E. (2008). Substrate-targeting γ-secretase modulators. Nature, 453(7197), 925-929. DOI: 10.1038/nature07055

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Pharma's Funding Lie

With medical coverage emerging as a major domestic issue for this election cycle, the cost of drugs is likely to become a hot topic, especially given the array of pills many aging baby boomers must take. The industry line is best articulated by a GlaxoSmithKline campaign implying that high drug prices really fund R&D for future drugs ("Today's medicines finance tomorrow's miracles"). Activists counter that the pharmaceutical companies are actually marketing-focused, a view popularly reinforced by incrementalism and the highly-visible promotional campaigns for conditions that are primarily cosmetic, such as hair loss and erectile dysfunction. A new study in PLoS Medicine by Marc-André Gagnon, and Joel Lexchin (click the link, PLoS is free) suggests that the latter view is closer to reality: they find that companies spend in excess of $57 billion annually on marketing to doctors and consumers. This amounts to nearly twice as much being spent on promotion as on R&D (which receives ~$30 billion). While by no means the final say in the dispute, this paper and distortions of its findings (on both sides) may figure significantly in future debates.

The easiest criticism of this paper, and one that may often be repeated, is that the authors did no primary research. The paper is essentially a synthesis of research performed by two independent firms: IMS (its data is widely cited by industry groups such as PhRMA), and CAM. The article contains a single table, and a quick glance at it will inform the reader that whenever two numbers were available, the authors always took the larger. The authors explain this well in the case of detailing, and I agree with their decision there. I also agree with the principle, though I am not convinced of the magnitude, of the "other" category. When it comes to the cost of free samples, however, I disagree with the choice to use the retail price in the assessment.

The authors' justification on this point is rather feeble, and comes across as almost petulant in tone:

Using the wholesale value for samples, the CAM figure would be appropriate if we were arguing that the money spent on samples should go to another activity such as R&D. However, we have used the retail value of samples because this is consistent with companies' reporting of drugs they donate [19]. As these are both categories of products that are being distributed without a charge to the user, it is inconsistent for donations to be reported in terms of retail value and samples in terms of wholesale value.

It seems to me that there is no point to this assessment unless our ultimate intention is to compare money spent on promotions that could be spent on R&D to the actual money spent on research. Certainly that is the only comparison that actually speaks to the issues the authors raise in the introduction. Including money that could not be spent on research or anything else, because it is fictional money, is nonsense. If the aim is to define the actual costs of the promotion to the drug company then the wholesale price is more appropriate. If the authors have an objection to using the wholesale cost for one kind of handout and retail costs for another, then the correct response would have been to use the proper, intellectually honest number (wholesale cost) in their own analysis and argue that pharmaceutical companies ought to do likewise when reporting charitable contributions. Just because Eli Lilly misrepresents its costs doesn't mean you can, too.

However, there are other factors that make the CAM estimate questionable on this point, especially that any number of samples was reported as one. Most likely the actual cost of samples to the company lies somewhere between the CAM and IMS estimates; promotional costs therefore lie somewhere between $48 and $57 billion, or 160% to 190% of research expenditures.

Another key feature to note from the table is that direct-to-consumer advertising makes up a relatively small fraction of the total expenditure. This reflects a truth that anyone even tangentially related to the healthcare system has known for a long time: most of the actual marketing that pharmaceutical companies do is lobbying your doctor. Although they are pervasive, fundamentally uninformative, and frankly annoying, television and print advertisements for drugs constitute such a small percentage of the actual promotional costs that banning them again would not lead to a noticeable reduction in drug prices.

The findings of this paper should also be put in the context of a transformation underway in the pharmaceutical industry. The so-called "blockbuster" drugs that provided substantial profits over the past decade or so will soon lose (if they have not already lost) their patent protection, and some needed to be withdrawn due to failures of the clinical trial system. In order to adapt, many companies are shedding most or all of their R&D operations. The emerging model in the industry is to allow "small pharma"—tiny companies started by academics or entrepreneurs using venture capital—to do most of the legwork and then buy up or enter marketing partnerships with those companies once they have promising products that have passed phase I or II clinical trials. This model was promising and robust up to about two years ago, because plenty of capital was available. In the present economic climate the availability of capital is far less certain, however. In addition, the same issue that induced big pharma to shed R&D—poor ROI—will eventually act to inhibit the venture capital investments that small pharma requires.

Despite this increasing aura of uncertainty, the fact remains that many pharmaceutical companies appear to be undergoing a transition from being primarily research entities to being primarily production and marketing entities. In that light, the new estimate of the research-to-marketing ratio is hardly surprising, though it will doubtless be embarrassing to PhRMA and feed the rhetoric of populists such as John Edwards. Yet despite the vitriol that will surely be spewed, in reality there is little that can be done. As mentioned, the most visible marketing efforts of pharmaceutical companies constitute only a minor portion of actual promotional costs. While it would be wise and probably beneficial to public health to restrict these advertisements once again, it is unlikely that any reduction in medical costs or increases in R&D budgets would be achieved by such regulations.

Congress, if it desired, could take steps to reverse the current trend and strengthen FDA power to restrict off-label marketing of existing drugs, and of course a new President could make this an enforcement priority at FDA. However, enforcement of any such provision would be extremely difficult and subject to legal challenge on First Amendment grounds. Moreover, the FDA (and not coincidentally the USDA) are in need of a major overhaul and possible restructuring in order to achieve their existing missions; stapling on another major enforcement problem will not serve anyone. Regardless, off-label marketing does not constitute a majority of the promotional budget.

The First Amendment clearly protects on-label marketing, and at any rate promotions of proven drugs actually serve the public interest, up to a point, by making doctors aware of improved approaches for dealing with illness. The truth of this statement, however, is inversely related to the degree of incrementalism in drug discovery. "It's a bigger pill" is generally not a compelling rationale for new prescriptions or enormous marketing outlays. Nonetheless, the presence of a definite public interest in allowing marketing to doctors makes unclear what steps Congress should (or even can) take to regulate or diminish promotional spending.

The only tool readily available for public use against on-label marketing is shame. Either the companies themselves can be pressured to reduce their promotional budgets (unlikely), or activists can put pressure on professional societies and medical boards to implement ethical restrictions on what kinds of promotions their members can engage in (possible). Regulations against accepting expensive lunches and dinners or attending marketing "seminars" in exotic locales may be able to push back some spending. In this regard, the Gagnon and Lexchin study may prove a useful tool; the grandstanding of politicians most likely will not.

Fundamentally, however, this trend cannot be stopped, because marketing will always be a better—or at least more predictable—investment than research. Although this attitude is ultimately self-defeating, the safer course to higher profits in the near term is to aggressively market existing drugs and secure longer periods of exclusivity by lobbying for longer patent protection or incrementally improving medicines and delivery systems. The release of combination drugs such as Caduet reflects this sensibility. Most money spent on research never produces so much as a Phase I trial, and the discovery of a revolutionary medicine, though extremely profitable, is also extremely rare. For that reason, a conservative mind will always prefer promotion and production to research and development. This is the attitude that underlies the ongoing strategic shift in big Pharma's approach, as well as the findings, debatable though they may be, of Gagnon and Lexchin.

Gagnon MA, Lexchin J (2008) The Cost of Pushing Pills: A New Estimate of Pharmaceutical Promotion Expenditures in the United States. PLoS Med 5(1): e1 doi:10.1371/journal.pmed.0050001

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Resistance: Fall of Tamiflu

The past decade, and in particular the past five years, has seen a steadily increasing drumbeat of concern over the possibility of another influenza pandemic. Avian flu has been a topic of special concern, but the American health system's inability to deal effectively with even normal flu variants has led to significant efforts to upgrade capacity to manufacture the flu vaccine, as well as improve the supply and distribution of the neuraminidase inhibitor oseltamivir phosphate, better known as tamiflu. Because there are so few effective antiviral drugs, tamiflu is an essential line of defense in case vaccination fails. Unfortunately, it appears that the influenza virus can develop resistance to tamiflu treatment, which would be a serious blow to efforts to control the disease in an emergency. The wise course is to use tamiflu sparingly and at a high enough dosage that the infection does not have time to adapt. But will this be enough?

Tamiflu has the interesting property that the drug in the tablet is ineffective against the influenza virus. Tamiflu gains function inside the body due to chemical processing in the liver that reveals a reactive moiety. If you have an influenza infection, some proportion of the oseltamivir molecules will end up binding to neuraminidase, but the remainder will be excreted without further modification. This means that every time you are dosing a person with tamiflu you are also dosing the environment with it. That could be trouble, because some strains of influenza incubate in the wild, among ducks, for instance, who are likely to be swimming on the rivers or ponds where excreted tamiflu might be expected to end up. If these animals are constantly exposed to very low doses of tamiflu, it is quite conceivable that the viruses within them could evolve resistance to it without losing neuraminidase activity.

The question then becomes whether anything in the environment might degrade tamiflu before it reaches the ducks. We have one advantage in this regard: we generally treat our sewage before we let it go. In an experiment I do not envy one little bit, a Swedish team led by Jerker Fick tested actual sewage to see if oseltamivir carboxylate (the active form of the molecule) would break down in it (the article is open source on PLoS ONE). They took raw sewage, as well as samples of sewage at various stages of treatment, added oseltamivir, and incubated them with a similar temperature and duration to what they might experience in the treatment plant. The results were not encouraging: the amount of tamiflu they were able to recover from these samples was as much as or more than what they could recover from plain tap water incubated under the same conditions. Moreover, they found that the UV/visible light absorbance spectrum of tamiflu would not be conducive to photolysis in the environment. The conclusion from this is that we cannot expect any help from our water-treatment facilities in eliminating oseltamivir from water supplies that might eventually reach host organisms for influenza.

This puts us in a bit of a bind. It is impossible to use tamiflu without releasing it to the environment, even if it is used in accordance with rigorous guidelines designed to prevent resistance from arising in people. Yet, the more tamiflu that reaches the environment, the more likely it is that continued exposure among waterfowl will lead to the development of resistance. Although this is bad news for the future of tamiflu, it doesn't necessarily herald the inevitable onset of some kind of superflu. For one thing, some of the mutations that confer tamiflu resistance also diminish the ability of the influenza virus to infect hosts. Moreover, there's no guarantee that tamiflu in the environment will end up dosing avians — it might break down in their stomachs, even if it doesn't in the sewage plant.

Also, some mutations that confer this kind of resistance leave neuraminidase vulnerable to other inhibitors such as zanamivir (Relenza). Granted, Relenza does not appear to be as effective as Tamiflu, but the fact that resistance is not necessarily shared is an encouraging sign that it will be possible to continue developing improved inhibitors even if the worst happens.

However, the results of this paper and the fact that tamiflu-resistant strains can be transmitted to people who have never used tamiflu indicate that we should be making a greater effort to prepare ourselves for the appearance of resistance. Much has been made about efforts to stockpile tamiflu in case of a pandemic, and while there is nothing wrong with that idea per se, it is foolish to assume that tamiflu is some kind of panacea. If a pandemic does occur, with the attendant explosion of evolutionary possibilities for the influenza virus, the chances of a rapid development of resistance in humans may be quite high. At that point it will be too late to start developing alternatives. In the near term, we should do as has been suggested — use tamiflu sparingly and aggressively to minimize the chances of developing resistance in humans. But we should also provide incentives or a mandate to develop a back-up plan in case tamiflu fails.

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Allosteric inhibition in medicine

If you wanted to keep someone from driving off in their car, how would you do it? There are some obvious answers: you could put some kind of blockage in front of and behind it, or you could slash the tires, or you could damage the engine, or you could empty out the gas tank. All of these approaches directly interfere with the mechanisms that allow the car to move. Alternately, you could take a more indirect approach: you could break the doors so they don't open, or remove the steering wheel, or take out the brake and accelerator pedals, or remove the stickshift. None of these latter approaches make it impossible for the car to move — the engine and wheels still function — but by removing the means that allow human beings to control the car these approaches still manage to ensure that the vehicle cannot be driven.

The traditional approach in structure-based drug design is to attempt to block the active site of a protein or important interacting sites, analogous to the "direct" approaches I outlined above. By adding a lump of stuff that obstructs enzymatic activity, ion transport, or (more recently) binding interactions these drugs attempt to interfere directly with the biochemistry of the target protein. This approach has been pretty successful, and certainly no reasonable person would want to depart from it, but there are some weaknesses here. For one thing, many diseases don't originate from enzymes or ion channels, and developing drugs that obstruct binding interactions can be pretty tricky.

Imagine your disease arises in the following system. You have some kind of receptor (R in my little cartoon over to the side there) that can bind a ligand (L). Binding of L activates R in some way so that it can bind to a partner (P) and this causes some gene to be activated. This cartoon roughly represents the way in which hormone receptors (like for estrogen or testosterone) function. Now, suppose something has occurred to derange this system: perhaps too much of L is being made, or R and P have been aberrantly expressed in some tissue where the gene they activate is toxic or causes inappropriate cell proliferation.

If we come at this by the conventional approach of targeting the L-binding pocket, we have a problem, because any drug that has an affinity for R high enough to displace the natural ligand is likely to produce the same or similar conformational changes that cause P to bind. We could, of course, try to develop a drug that interferes with P's binding directly, but this approach has its own problems. For one thing, these binding surfaces are often quite large and highly structured, features that are often difficult to replicate with a small molecule. You can create a drug that inserts itself into the site somehow and gets in the way of P binding, but it's not always possible to design such an agent that specifically hits only your protein. A peptide mimic of R might work, but these are also difficult to deliver.

But there's another strategy that might work, too. Rather than try to block R from binding L or P directly, what if we could cause some other change in R that prevents P binding whether or not L is around? Just like removing the accelerator or stickshift from the car of my example, this doesn't directly block either function of the molecule. R can still bind L, and the binding surface P interacts with is still present. However, our drug (D) has caused a new change in R's conformation that prevents the binding of P. A simplified cartoon is at left.

This is precisely what seems to have happened in a study on the androgen receptor (AR) appearing the October 9 issue of PNAS and reported by Eva Estébanez-Perpiña and coworkers from UCSF and St. Jude's. Interestingly, this group of researchers was initially seeking to produce a direct inhibitor — in this case, a drug that would bind to the part of AR that interacts with its coregulators. This interaction is therapeutically interesting because aberrant AR activity plays a role in prostate cancer, among other things. Several promising compounds were found that produced substantial inhibition of AR activity at relatively low concentrations. The surprise was that only some of these preferred to bind the targeted site (AF-2). Instead, a number of them were found to locate preferentially to a previously unsuspected site at the top of the molecule, now called binding-function 3 (BF-3), which you can see in the figure I shamelessly stole on the right here.

The reason that this appears to work is that binding to BF-3 changes the structure of AF-2, via an allosteric interaction. Rather than directly getting in the way of the essential reaction, the drug acts at a distance to disrupt the binding surface. Although much still needs to be done to refine these lead compounds into usable drugs, this is a significant demonstration that such an approach has therapeutic potential. In this case, the discovery of allosteric inhibitors was made by accident, but as our understanding of protein structure and allostery improves, expect to see more efforts to approach drug design in this way.

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