There are billions of miles of copper wire strung across the globe, buried beneath cities, spanning even the most remote landscapes, winding through our homes, our computers, and our cell phones. Although some of this global tangle of wires has lately been replaced by fiber-optic cable and wireless signals, we still depend on copper and its ‘wandering’ S electron to light our cities, power our appliances, and transmit the electrical signals we use to communicate. While the importance of copper today is sometimes overshadowed by the ubiquity and strength of modern steel, for thousands of years copper was the only practical metal known to humans.
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ABRAHAM, M. (2004) Ion beam analysis in art and archaeology: attacking the power precisions paradigm. Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms, 1-6. DOI: 10.1016/j.nimb.2004.01.018
Body odor is closely associated with diet. Deciphering the chemistry of human odor is not an easy task. Fortunately for some (and not so fortunately for others), the human nose can capture and discriminate many smell signatures. Could this discrimination be used to connect the dots between diet and body odor? MEBO Research has just started an anonymous study using the Aurametrix health analysis tool to find out.... Read more »
Bolton B, & Halpern BP. (2010) Orthonasal and retronasal but not oral-cavity-only discrimination of vapor-phase fatty acids. Chemical senses, 35(3), 229-38. PMID: 20100787
What’s in that “Spice” packet?
They first turned up in Europe and the U.K.; those neon-colored foil packets labeled “Spice,” sold in small stores and novelty shops, next to the 2 oz. power drinks and the caffeine pills. Unlike the stimulants known as mephedrone or M-Cat, or the several variations on the formula for MDMA—both of which have also been marketed as Spice and “bath salts”—the bulk of the new products in the Spice line were synthetic versions of cannabis.
The new forms of synthetic cannabis tickle the same brain receptors as THC does, and are sometimes capable of producing feelings of well-being, empathy, and euphoria—in other words, pretty much the same effects that draw people to pot. But along the way, users began turning up in the emergency room, something that very rarely happens in the case of smoked marijuana. The symptoms were similar to adverse effects some people experience with marijuana, but greatly exaggerated: extreme anxiety and paranoia, and heart palpitations.
As it turns out, there is a very real difference between smoking Purple Kush and snorting “Banana Cream Nuke” out of a metallic packet. The difference lies in the manner in which the brain’s receptors for cannabinoids are stimulated by the new cannabis compounds. When things goes wrong at the CB1 and CB2 receptors, and the mix isn’t right, the results may not be euphoria, giggles, short-term memory loss, and the munchies, but rather “nausea, anxiety, agitation/panic attacks, tachycardia, paranoid ideation, and hallucinations.” Furthermore, the Spice variants do not contain cannabidiol, a cannabis ingredient that has been shown to reduce anxiety in animal models, and reduces THC-induced anxiety in human volunteers. The authors of a recent study suggest that the “lack of this cannabinoid in Spice drugs may exacerbate the detrimental effects of these herbal mixtures on emotion and sociability.”
What concerned the researchers was that, in addition to reports of cognitive deficits and emotional alterations and gastrointestinal effects, emergency room physicians were reporting wildly elevated heart rates, extremely high blood pressure, chest pains, and fever. Fattore and Fratta report that “two adolescents died in the USA after ingestion of a Spice product called ‘K2,’” one due to a coronary ischemic event, and the other due to suicide. What’s going on?
In a paper for Frontiers in Behavioral Neuroscience called “Beyond THC: the new generation of cannabinoid designer drugs,” Liana Fattore and Walter Fratta of the University Of Cagliari in Monserrato, Italy, identified more than 140 different products marketed as Spice, and laid out the extreme variability found in composition and potency. Like a mutating virus, they came to the U.S., starting in early 2009, a new strain seemingly every week: Spice, K2, Spice Gold, Silver, Arctic Spice, Genie, Dream, and dozens of others, the naming and renaming suggesting nothing so much as the proliferating strains of high-end marijuana: Skunk, Haze, Silver Haze, Amnesia, AK-47. Synthetic marijuana comes mainly from manufacturers in Asia, and second generation chemicals have already been put on a to-be-banned list by the DEA. States have jumped all over the problem with duplicate legislation, despite the fact that experts believe a majority of sales take place over the Internet. A third generation of synthetic cannabis variants, which are sprinkled on an herbal base and meant to be snorted, are openly sold and touted as legal. And they are legal, depending upon which one you buy, and where you buy it. Synthetic cannabis is still readily available, affordably packaged, and right on the shelf, or ready for purchase online—unlike the frequently vague and sometimes shady process of scoring a bag of weed. In the beginning, at least, the new drugs were perceived by youthful users as safer than other drugs.
But the most crucial attribute of Spice and related products is that they are not detectable in urine and blood samples. You can cruise all night on Spice, and test clean the next day at work. The kind of cannabis in Spice doesn’t read out on anybody’s drug tests as marijuana. That requires the presence of THC—and the new synthetics don’t have any.
There are four different categories of chemicals used in the manufacture of “cannabimimetic” drugs. The first and best known is the so-called JWH series of “novel cannabinoids” synthesized by John W. Huffman at Clemson University in the 1980s. The most widely used variant is an extremely potent version known as JWH-018. While JWH-018 is, chemically speaking, not structurally like THC at all, it snaps onto CB1 and CB2 receptors more fiercely than THC itself The CP-compounds, the second class of synthetic compounds, were developed back in the 1970s by Pfizer, when that firm was actively engaged in testing cannabis-like compounds for commercial potential, a program they later dropped. The best-known example is CP-47,497. While CP-47,497, the most common variant, lacks the chemical structure of classic cannabinoids, it is anywhere from 3 to 28 times more potent than THC, and shows classic THC-like effects in animal studies. The next group is known as HU-compounds, because they originated at Hebrew University, where much of the early work on the mechanisms of THC took place. The last category consists of chemicals in the family of benzoylindoles, which also show an affinity for cannabinoid receptors.
JWH-018, the most common form of synthetic cannabis, and now widely illegal, is considerably more potent than THC—4 times stronger at the CB1 receptor, and 10 times stronger at the less familiar CB2 receptor. The CB2 receptor seems to have a lot to do with pain perception and inflammation, which is why researchers continue to investigate it. But CB2 receptors contribute only indirectly to the classic marijuana high, which is all about THC’s affinity for CB1 receptors, and the effects of using drugs with a very strong affinity for CB2 receptors is not well documented. And therein might lie the source of the problem—or, as Fattore and Fratta describe it, “the greater prevalence of adverse effects observed with JWH-018-containing products relative to marijuana.” A popular compound of the second kind, HU-210, has frequently been found in herbal mixtures available in the U.S. and U.K. According to the study, “the pharmacological effects of HU-210 in vivo are also exceptionally long lasting, and in animal models it has been shown to negatively affect learning and memory processes as well as sexual behavior.”
That, in a nutshell, is what the kids are smoking these days. But wait, there’s more: Besides synthetic cannabinoids, herbs and vitamins, researchers have found opioids like tramadol, opioid receptor-active compounds like Kratom (Mitragyna speciosa), and oleamide, a fatty acid derivative with psychoactive properties. (A combination of oleamide and JWH-018 has been sold as “Aroma.”) Indentifying which of these active ingredients is part of any particular packet of “legal highs” is further complicated by manufacturers’ tendency to mix the ingredients together with up to 15 organic compounds—everything from nicotine to masking agents like vitamin E. In fact, almost anything that might make it more difficult for forensic labs to pry it all apart: alfalfa, comfrey leaf, passionflower, horehound, etc. Banana Cream Nuke, which was purchased in an American smoke shop, and made two young girls very sick, contained 15 varieties of synthetic cannabis—but none of the herbal ingredients actually listed on the label.
Unlike to the partial activation of CB1 receptors by THC, which takes place when people smoke marijuana, “synthetic cannabinoids identified so far in Spice products have been shown to act as full agonists with increased potency, thus leading to longer durations of action and an increased likelihood of adverse effects.” When it comes to cannabis, users are far better off smoking the ... Read more »
Fattore, L., & Fratta, W. (2011) Beyond THC: The New Generation of Cannabinoid Designer Drugs. Frontiers in Behavioral Neuroscience. DOI: 10.3389/fnbeh.2011.00060
It’s probably just the human brain’s ability to connect dots & find patterns, but it can be interesting how many “unrelated” events and information bits accumulate in my head & eventually get mulled into an idea or theory. Take, for example, a recent biotech mixer, bits from an education leadership series & a past Nature [...]... Read more »
Sierpinski P, Garrett J, Ma J, Apel P, Klorig D, Smith T, Koman LA, Atala A, & Van Dyke M. (2008) The use of keratin biomaterials derived from human hair for the promotion of rapid regeneration of peripheral nerves. Biomaterials, 29(1), 118-28. PMID: 17919720
One of the most fun things about chemistry is that for every laundry list of examples, there is always a counterexample. The counterexample does not really violate any general principles, but it enriches our understanding of the principle by demonstrating its richness and complexity. And it keeps chemists busy.One such key principle is the hydrophobic effect, an effect with an astounding range of applicability, from the origin of life to cake baking to drug design. Textbook definitions will tell you that the signature of the "classical" hydrophobic effect is a negative heat capacity change resulting from the union of two unfavorably solvated molecular entities. The nonpolar surface area of the solute is usually proportional to the change in heat capacity. The textbooks will also tell you that the hydrophobic effect is favorable principally because of entropy; the displacement of "unhappy" water molecules that are otherwise uncomfortably bound up in solvating a solute contributes to a net favorable change in free energy. Remember, free energy is composed of both enthalpy and entropy (∆G = ∆H - T∆S) and it's the latter term that's thought to lead to hydrophobic heaven.But not always. Here's a nice example of a protein-ligand interaction where the improvements in free energy across a series of similar molecules comes not from entropy but from improved enthalpy with the entropy actually being unfavorable. A group from the University of Texas tested the binding of a series of tripeptides against the Grb2 protein SH2 domain. The exact details of the protein are not important; what's important is that the molecules only differed in the size of the cycloalkane ring in the central residue of the peptide- going from a cyclopropane to a cyclohexane. They found that the free energy of binding improves as you go from a 3-membered to a 5-membered ring but not for the reason you expect, namely a greater hydrophobic effect and entropic gain from the larger and more lipophilic rings.Instead, when they experimentally break down the free energy into enthalpy and entropy using isothermal titration calorimetry (ITC), they find that all the gain in free energy is from enthalpy. They find that every extra methylene group contributes about 0.7 kcal/mol to the interaction. In fact the entropy becomes unfavorable, not favorable as you move up the series. There's another surprise waiting in the crystal structures of the complexes. There are a couple of ordered water molecules stuck in some of the complexes. Ordered water molecules are fixed in one place and are "unhappy", so you would expect these complexes to display unfavorable free energy. Again, you would be surprised. It's the ones without ordered water molecules that have worse free energy. The nail in the coffin of conventional hydrophobic thinking is driven by the observation that the free energy does not even correlate with decreased heat capacity, something that's supposed to be a hallmark of the "classical" hydrophobic effect.Now it's probably not too surprising to find the enthalpy being favorable; after all as they note, you are making more Van der Waals contacts with the protein with larger rings and greater nonpolar surface area. But in most general cases this value is small, and the dominant contribution to the free energy is supposed to come from the "classical" hydrophobic effect with attendant displacement of waters. Not in this case where enthalpy dominates and entropy worsens. They don't really speculate much on why this may be happening. One factor that comes to my mind is the flexibility of the protein. The improved contacts between the larger rings and the protein may well be enforcing rigidity in the protein, leading to a sort of "ligand enthalpy - protein entropy" compensation. Unfortunately a comparison between bound and unbound protein is precluded by the fact that the free protein forms not a monomer but a domain-swapped dimer. In this case I think that molecular dynamics simulations might be able to shed some light on the flexibility of the free protein compared to the bound structures; it might especially be worthwhile to do this exercise in the absence of the apo structureNonetheless, this study provides a nice counterexample to the conventional thermodynamic signature of the hydrophobic effect. The textbooks probably don't need to be rewritten anytime soon, but chemists will continue to be frustrated, busy and amused as they keep trying to tame these unruly creatures, the annoying wrinkles in the data, into an organized whole.Myslinski, J., DeLorbe, J., Clements, J., & Martin, S. (2011). Protein–Ligand Interactions: Thermodynamic Effects Associated with Increasing Nonpolar Surface Area Journal of the American Chemical Society DOI: 10.1021/ja2068752... Read more »
Myslinski, J., DeLorbe, J., Clements, J., & Martin, S. (2011) Protein–Ligand Interactions: Thermodynamic Effects Associated with Increasing Nonpolar Surface Area. Journal of the American Chemical Society, 2147483647. DOI: 10.1021/ja2068752
If you can't bear to face your inbox before your first cup of coffee, you'll sympathize with cells in your body that are better equipped to face some challenges at certain times of day. Carcinogens, such as ultraviolet radiation, may be one such challenge. Can we lower our cancer risk by limiting our carcinogen exposure to certain hours of the day?
Circadian rhythms are day-long cycles that ebb and flow like tides within our bodies. We use the sun to keep our internal clocks calibrated. But even if left in a dark room for days on end, our bodies maintain their rhythms. Our internal temperatures, levels of circulating hormones, and activity of various genes within our cells all rise and fall throughout the day.
One of the genes that follows a daily cycle is responsible for making a DNA-repair protein called XPA. When your DNA is damaged, a molecular task force within the cell identifies the bad spot, snips it out, and fills in the gap with fresh nucleotides. XPA is a crucial member of this task force. Researchers in North Carolina wanted to know how the cycling of XPA affects skin cancer. When XPA is off-duty--when its daily cycle reaches its lowest point--are skin cells more vulnerable to cancer-causing sun damage?
To find out, the researchers used hairless mice that are bred to develop humanlike skin cancer. Mice have an internal clock that's nearly identical to that of humans, and repair their DNA in the same way. The researchers exposed one group of mice to UV radiation at 4 AM, the lowest point of their XPA cycle. Another group of mice was exposed at 4 PM, the high point, instead.
For the 12 hours following UV exposure, the researchers monitored the rate of DNA repair in mouse skin cells. They saw that in the afternoon group, repair happened quickly, thanks to the high amounts of XPA at work. But in the morning-exposure group, DNA repair was delayed significantly.
Does this delay in fixing DNA errors add up to cancer? The researchers again divided the mice into groups. One group was exposed to UV radiation at 4 AM, three days a week, for 25 weeks. The second group was again exposed to UV at 4 PM, and a third group was left alone.
Both groups of mice exposed to UV developed skin tumors. But the group that got its UV radiation in the early morning grew tumors sooner. Those mice also had twice as many tumors as the afternoon UV group, and their tumors were nearly twice as wide. (All this evidence was easily, and disgustingly, visible due to their hairlessness.)
In humans, damage and repair likely follow the same rhythm. But there's one major difference: Since mice are nocturnal, their clock is opposite to ours. Hormones that are needed during waking hours, for instance, would peak during the night in mice and during the day in humans. In an earlier study, the researchers found that XPA follows a circadian rhythm in humans just as it does in mice--but for us, production is highest in the early morning.
Our levels of XPA peak around 7 AM. Based on this study, our ability to protect our skin from cancer-causing sun damage probably peaks at the same time. Adding to the danger is the fact that in both humans and mice, DNA replication follows a cycle opposite to XPA production. This means that when XPA is lowest, more DNA is being stitched together--making the risk of errors even higher.
The authors suggest that if we must expose ourselves to UV radiation, we do so in the morning. We should avoid the sun in afternoon and evening hours, when XPA is lowest and our skin cells are most vulnerable to carcinogenic damage. Of course, unless you live in the Arctic circle, you're not likely to get a lot of dangerous sun exposure at 7 PM. But for people who use tanning beds, sessions late in the day may be more harmful than those in the morning.
There may be other carcinogens whose danger varies throughout the day, depending on how hormones and other molecules are cycling through our affected organs. Is there an ideal time of day to smoke a cigarette? Eat a hot dog? Have an x-ray? If we can't remove risks from our lives, maybe we can at least reschedule them.
Gaddameedhi, S., Selby, C., Kaufmann, W., Smart, R., & Sancar, A. (2011). Control of skin cancer by the circadian rhythm Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.1115249108
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Video proof that siphons do not require atmospheric pressure to suck... Read more »
SUMMARY: Video proof that siphons do not require atmospheric pressure to suck ... Read more »
Ovarian cancer is the fifth leading cause of cancer related mortality among women. Like many diseases, there is a stark difference in survival rates depending on detection times. When ovarian cancer is detected at stage I, there is a 90% 5 year survival rate. Compare that with the 33% 5 year survival rate when the ovarian cancer is detected in stage III and IV. This disease is unfortunately asymptomatic at early stages, drastically eliminating the odds of discovery with enough time to make a difference.... Read more »
Wang, S., Zhao, X., Khimji, I., Akbas, R., Qiu, W., Edwards, D., Cramer, D., Ye, B., & Demirci, U. (2011) Integration of cell phone imaging with microchip ELISA to detect ovarian cancer HE4 biomarker in urine at the point-of-care. Lab on a Chip, 11(20), 3411. DOI: 10.1039/C1LC20479C
Understanding the properties of something chaotic like a bowl of spaghetti may seem a daunting task. But that’s what Garry Rumbles from the National Renewable Energy Laboratory in the USA, Natalie Stingelin from Imperial College London in the UK, and coworkers are trying to do. With success. They study polymers – long spaghetti-like molecules made of repeating atomic subunits [...]... Read more »
Reid, O., Malik, J., Latini, G., Dayal, S., Kopidakis, N., Silva, C., Stingelin, N., & Rumbles, G. (2011) The influence of solid-state microstructure on the origin and yield of long-lived photogenerated charge in neat semiconducting polymers. Journal of Polymer Science Part B: Polymer Physics. DOI: 10.1002/polb.22379
I guess reader of my blog already heard about it via other channels (e.g. via Noel's blog post), but our second Blue Obelisk paper is out. In the past five-ish years since Peter instantiated this initiative, it has created a solid set of shoulder on which to developed Open Source-based cheminformatics solutions. I created the following diagram for the paper, showing how various Blue Obelisk projects interoperate (image is CC-BY, from the paper):
It shows a number of Open Standards (diamonds), one Open Data set (rectangles), and Open Source projects (ovals). What does diagram is not showing, is the huge amount of further Open Source cheminformatics projects around, that use one or more of the components listed here, but which do not link themselves to the Blue Obelisk directly. And there are many indeed, both proprietary and Open.
I am proud of this diagram: it really shows that the interoperability we set out in the first paper worked out very well! This makes the Blue Obelisk an excellent set of shoulders to do translational cheminformatics.
Translational cheminformatics?? Well, I have been looking for a while for a good term for my research regarding all that hacking on the CDK, Bioclipse, etc. Now, that's the translation of my core molecular chemometrics research to other scientific fields, like metabolomics, toxicology, etc.
Guha, R., Howard, M., Hutchison, G., Murray-Rust, P., Rzepa, H., Steinbeck, C., Wegner, J., & Willighagen, E. (2006). The Blue Obelisk - Interoperability in Chemical Informatics Journal of Chemical Information and Modeling, 46 (3), 991-998 DOI: 10.1021/ci050400b
O'Boyle NM, Guha R, Willighagen EL, Adams SE, Alvarsson J, Bradley JC, Filippov IV, Hanson RM, Hanwell MD, Hutchison GR, James CA, Jeliazkova N, Lang AS, Langner KM, Lonie DC, Lowe DM, Pansanel J, Pavlov D, Spjuth O, Steinbeck C, Tenderholt AL, Theisen KJ, & Murray-Rust P (2011). Open Data, Open Source and Open Standards in chemistry: The Blue Obelisk five years on. Journal of cheminformatics, 3 (1) PMID: 21999342 DOI: 10.1186/1758-2946-3-37... Read more »
Guha, R., Howard, M., Hutchison, G., Murray-Rust, P., Rzepa, H., Steinbeck, C., Wegner, J., & Willighagen, E. (2006) The Blue ObeliskInteroperability in Chemical Informatics. Journal of Chemical Information and Modeling, 46(3), 991-998. DOI: 10.1021/ci050400b
O'Boyle NM, Guha R, Willighagen EL, Adams SE, Alvarsson J, Bradley JC, Filippov IV, Hanson RM, Hanwell MD, Hutchison GR.... (2011) Open Data, Open Source and Open Standards in chemistry: The Blue Obelisk five years on. Journal of cheminformatics, 3(1), 37. PMID: 21999342
"The courtship chamber was placed on top of an identical chamber, with the chambers separated by muslin gauze," reports geneticist Yael Grosjean in a Methods section fit for a paperback romance. Then the "perfumed" portion of the experiment began. An aphrodisiac scent was presented on the other side of the muslin gauze. Scientists watched to see whether the subject, a male fruit fly, would be compelled to start courting his partner. To ensure that the female wouldn't influence the results with her responses, she had been recently frozen to death.
(This may seem unromantic, but keep in mind that in another part of the study, the females were headless. It didn't deter the males.)
A male fruit fly displays a scripted set of actions when courting a female, beginning with a buzzy sort of love song and ending with the deposition of his extraordinarily long sperm. Many animals use pheromones, chemical messages wafting through the air, to attract partners. But, Grosjean says, scientists haven't yet found the hardware in a male fruit fly's brain that would respond to pheromones. So what other chemical signals might the fruit fly be sensing when it decides to court a female?
Grosjean's research team identified neurons in male Drosophila melanogaster that detect scent and extend into a part of the brain involved in sexual behaviors. They found that when these neurons weren't working properly, males failed to court (headless) females. Once they knew the neurons were important for courtship behaviors at the brain end, the researchers investigated what was happening at the "nose" end. They exposed the neurons to the smell of fly bodies, both up close and at a distance (as they would be if pheromones were involved). But the neurons didn't respond.
The researchers proceeded to test another 163 odors on the frigid cells until they found a couple of smells that turned them on: phenylacetic acid and phenylacetaldehyde. These aromatic compounds come not from flies, but from plants. (They also lend their honey-like scent to some of the perfumes manufactured by humans.)
These molecules are common in fruit and vegetable matter, including overripe bananas and prickly-pear cactus, two of Drosophila's preferred foods. To understand why mealtime puts fruit flies in the mood for mating, it helps to know that they lay their eggs in their food. (I guarantee this will occur to you the next time you see buzzing visitors inside the pastry display case at your favorite coffee shop.) To a fruit fly, vegetables and fruits are good places to eat, mate, and start a new generation.
It's a surprising evolutionary solution to the problem of helping tiny flying animals find each other and mate. Pheromones work for some other species, but for fruit flies, the smell of a good egg-laying environment might be enough.
The question of whether humans release or detect pheromones, tantalizing though it is, remains unresolved. Maybe scientists would have more luck if they looked for environmental cues humans respond to, rather than molecules released by other humans. I wouldn't expect prickly-pear cactus to be the next hot perfume, but you never know.
Grosjean, Y., Rytz, R., Farine, J., Abuin, L., Cortot, J., Jefferis, G., & Benton, R. (2011). An olfactory receptor for food-derived odours promotes male courtship in Drosophila Nature, 478 (7368), 236-240 DOI: 10.1038/nature10428
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Grosjean, Y., Rytz, R., Farine, J., Abuin, L., Cortot, J., Jefferis, G., & Benton, R. (2011) An olfactory receptor for food-derived odours promotes male courtship in Drosophila. Nature, 478(7368), 236-240. DOI: 10.1038/nature10428
We usually go to Chinatown for lunch since it’s just a 10-15 minute walk from campus. Not only are the restaurants reasonably priced compared to the other lunch options available nearby, but there is a lot of variety as well. … Continue reading →... Read more »
Jinap, S., & Hajeb, P. (2010) Glutamate. Its applications in food and contribution to health. Appetite, 55(1), 1-10. DOI: 10.1016/j.appet.2010.05.002
R.H.M Kwok. (1968) Chinese-restaurant syndrome. N. Engl. J. Med., 796. info:/
Geha RS, Beiser A, Ren C, Patterson R, Greenberger PA, Grammer LC, Ditto AM, Harris KE, Shaughnessy MA, Yarnold PR.... (2000) Review of alleged reaction to monosodium glutamate and outcome of a multicenter double-blind placebo-controlled study. The Journal of nutrition, 130(4S Suppl). PMID: 10736382
The last decade has been a bonanza decade for the elucidation of structures of G Protein-Coupled Receptors (GPCRs), culminating with the landmark structure of the first GPCR-G protein complex published a few weeks ago. With 30% of all drugs targeting these proteins and their involvement in virtually every key aspect of health and disease, GPCRs remain glowingly important targets for pure and applied science.Yet there are miles to go before we sleep. Although we now have more than a dozen structures of half a dozen GPCRs in various states (inactive, active, G-protein coupled), there are still hundreds of GPCRs whose structures are not known. The existing GPCRs all fall into the 'Class A' GPCRs. We still have to mine the vast body of Class B and C GPCRs which comprise a huge number of functionally relevant proteins. The crystal structures which we do have comprise an invaluable resource but from the point of view of drug discovery, we still don't have enough.In the absence of crystal structures, homology modeling wherein a protein of high sequence homology is used to build a computational model for an unknown structure has been the favorite tool of modelers and structural biologists. Homology modelers were recently provided an opportunity to pit their skills against nature when a contest asked them to predict the structures of the D3 and CXCR4 receptors just before the real x-ray structures came out. Both proteins are important targets involved in multiple processes like neurotransmission, depression, psychoses, cancer and HIV infection. The D3 structure prediction involved predicting the ligand-bound structure of the protein complexed with eticlopride, a D3 antagonist.The results of the contest have been published before, but in a recent Nature Chemical Biology paper, a team led by Brian Shoichet (UCSF) and Bryan Roth (UNC-Chapel Hill) perform another test of homology modeling, this time connected to the ability to virtually screen potential D3 receptor ligands and discover novel active molecules with interesting chemotypes.Two experiments provided the comparison. One protocol used the D3 homology model to screen about 3 million compounds by docking, out of which about 20 were picked and tested in assays based on docking scores and inspection. The homology model was built on the basis of the published structure of the ß2 adrenergic receptor which has been structurally heavily studied. Then, after the x-ray structure of the D3 was released, they repeated the virtual screening protocol with the crystal structure; again, 3 million compounds out of which roughly 20 were picked and tested.First the somewhat surprising and heartening result; both homology model and crystal structure demonstrated similar hit rates- about 20%. In both the cases the actual affinity of the ligands ranged from about 200 nM - 3 µM. In addition, the screen revealed some novel chemotypes that did not resemble known D3 antagonists (although not surprisingly, some hits were similar to eticlopride). As an added bonus, the top ranked ligands using the homology model did not measurably inhibit the template ß2 adrenergic receptor, which means that the homology model probably did not retain the "memory" of the original template.Now for the bee in the bonnet. The very fact that the homology model and the crystal structure produced different hits means that the two models were not identical (only one hit overlapped between the two). Of course, it's too much to expect a model of a protein with thousands of moving parts to be identical to the experimental structure, but it goes to show how careful homology modeling has to be performed and how it can still be imperfect. What is more disturbing is that the differences between the model and the crystal structure responsible for the different hits were small; in one case the difference between two carbons was only 1 Å between the two models. Other amino acids differed by less than that.And all this even after generating a stupendous number of models of unbound and ligand-bound protein. As the paper says, the team generated about 98 million initial ligand-bound homology models. Screening the top models among these involved generating multiple conformations and binding modes of the 3 million compounds; the total number of discrete protein-ligand complexes resulting from this exercise numbered about 2 trillion. That such kind of evaluation is possible is a tribute to the enormous computing power we have at our fingertips. But it's also a commentary on how relatively primitive our models are so that we are still at a loss to predict minute structural differences with significant consequences in finding new active molecules.So where does this lead us? I think it's really useful to be able to perform such comparisons between homology models and crystal structures and we can only hope more such comparisons will be possible by virtue of an increasing pipeline of GPCR structures. Yet these exercises demonstrate how challenging it is to generate a truly accurate homology model. A few years ago a similar study demonstrated that a difference in a single torsional angle of a phenylalanine residue (and that too resulting in a counter-intuitive gauche conformation) affected the binding of a ligand to a homology model of the ß2 adrenergic receptor. Our ability to pinpoint such tiny differences in homology models is still in its infancy. And this is just for Class A GPCRs for which relatively accurate templates are available. Get into Class B and Class C territory and you start looking for the proverbial black cat in the dark.Now throw in the fascinating phenomenon of functional selectivity and you have a real wrench in the works. Functional selectivity, whereby different conformations of a GPCR binding to the same ligand modulate different signal transduction pathways and cause the ligand to change its mode of action (agonist, inverse agonist etc.) takes modeling of GPCRs to unknown levels of difficulty. Most modeling currently being done does not even attempt to consider protein flexibility which is at the heart of functional selectivity. Routinely including protein flexibility in GPCR modeling has some way to go.That is why I think that, as much as we will continue to learn from GPCR homology modeling, it's not going to contribute massively to GPCR drug discovery anytime soon. Constructing accurate homology models of even a fraction of the GPCR universe will take a long time. Using such models would be like throwing darts at a board for which the center is unknown. Until we can locate the center and are plagued with the complexities of functional selectivity, we may be better off pursuing experimental approaches that that can map the effect of ligands on a particular GPCR using multifunctional assays. Fortunately, such approaches are definitely seeing the light of day.Carlsson, J., Coleman, R., Setola, V., Irwin, J., Fan, H., Schlessinger, A., Sali, A., Roth, B., & Shoichet, B. (2011). Ligand discovery from a dopamine D3 receptor homology model and crystal structure Nature Chemical Biology DOI: 10.1038/nchembio.662... Read more »
Carlsson, J., Coleman, R., Setola, V., Irwin, J., Fan, H., Schlessinger, A., Sali, A., Roth, B., & Shoichet, B. (2011) Ligand discovery from a dopamine D3 receptor homology model and crystal structure. Nature Chemical Biology. DOI: 10.1038/nchembio.662
QSAR and QSPR are the fields that statistically correlate chemical substance features with (biological) activities (QSAR) or properties (QSPR). The chemical substance can be molecular structures, drug (which are not uncommonly mixtures), and true mixture like nanomaterials (NanoQSAR). Readers of this blog know I have been working towards making these kind of studies more reproducible for many years now.
Parts of this full story include the Blue Obelisk Data Repository (BODR), QSAR-ML, the CDK for descriptor calculation, the Blue Obelisk Descriptor Ontology (BODO, doi:), still used by the CDK, and in the past by JOELib too, and much, much more. Really, I still feel that the statistics is by far the easiest bit in QSAR modeling.
New in this list of tools to make QSAR more reproducible, is the CHEMINF ontology, which further formalizes cheminformatics computation. In a collaboration with Janna and Christoph (EBI), Michel and Leonid (Carlton University), and Nico (formerly at Cambridge, now at CSIRO), we have cooked up an ontology, and the computational bits of it are captured by the below figure from the paper that just appeared in PLoS ONE.
Both the paper and the ontology have a Creative Commons license. The ontology has already been used by Leonid in other papers, and I have been using it already in the RDF-ed version of ChEMBL.
Next steps for me regarding this ontology is to convert to BODO to be based on CHEMINF, but highly interesting too is a reformulation of QSAR-ML to be based on CHEMINF. The QSAR markup language was long started before RDF came into the picture, so please forgive us for now using RDF from the start there.
One particularly interesting aspect this ontology captures is the difference between molecular entities and mixtures. Not uncommonly, QSAR studies correlate drugs to their binding affinities, even if those drugs are in fact mixtures of stereoisomers. While 0D, 1D, and 2D descriptors are not affected, geometrical descriptors most certainly are. Moveover, the modeled endpoint is very possibly the property of only one of the stereoisomers, most certainly for binding affinities. Yet, many QSAR study reports in literature do not record such details. The CHEMINF ontology defines the terms you need to publish such details.
Hastings, J., Chepelev, L., Willighagen, E., Adams, N., Steinbeck, C., & Dumontier, M. (2011). The Chemical Information Ontology: Provenance and Disambiguation for Chemical Data on the Biological Semantic Web PLoS ONE, 6 (10) DOI: 10.1371/journal.pone.0025513... Read more »
Hastings, J., Chepelev, L., Willighagen, E., Adams, N., Steinbeck, C., & Dumontier, M. (2011) The Chemical Information Ontology: Provenance and Disambiguation for Chemical Data on the Biological Semantic Web. PLoS ONE, 6(10). DOI: 10.1371/journal.pone.0025513
In today’s tip I am going to feature a resource that I found recently. I’ve been updating our dbSNP tutorial, which Mary & Trey will be presenting at workshops in Morocco, and also our free PDB tutorial, which is sponsored by the RCSB PDB team. I have therefore been thinking about protein structures and small [...]... Read more »
Yang, J., Oh, S., Ko, G., Park, S., Kim, W., Lee, B., & Lee, S. (2010) VnD: a structure-centric database of disease-related SNPs and drugs. Nucleic Acids Research, 39(Database). DOI: 10.1093/nar/gkq957
“I am flying home from Europe in late August with nothing but a notebook and the 2011 Goldschmidt conference Geology giveaway issue to keep me occupied. Using the old-fashioned method of reading and writing on paper, I will blog my way through the compilation of highlighted geochemistry papers as time allows. These will then be posted via time delay to keep the blog moving while preventing ... Read more »
Kharaka, Y., Cole, D., Hovorka, S., Gunter, W., Knauss, K., & Freifeld, B. (2006) Gas-water-rock interactions in Frio Formation following CO2 injection: Implications for the storage of greenhouse gases in sedimentary basins. Geology, 34(7), 577. DOI: 10.1130/G22357.1
Citizens of the Ancient World seem to have made a solid go at “going green.” Ongoing research by Harriet Foster and Caroline Jackson (2010) revealed hints of color deriving from previously blown glass in colorless glass, indicating that Romans often reused glass, adding batches of broken vessels into the raw material from which they fashioned [...]
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Foster, Harriet and Caroline Jackson. (2010) The Composition of Late Romano-British Colourless Vessel Glass: Glass Production and Consumption. Journal of Archaeological Science, 3068-3080. info:/10.1016/j.j.as.2010.07.007
Hey, how’s your biotin? What? No it’s not an organic metal, maybe you call it B7? You’re probably fine, but have you been depressed, lethargic or losing your hair lately? Biotin is pretty important; it’s necessary for metabolism within our cells, so I make sure I never leave home without it. It’s rare for someone to have a biotin deficiency, but if you want to know your levels, give me a drop of your blood, and I’ll have an answer from you in 10 minutes. How? Oh just my self-powered integrated microfluidic blood analysis system (but I like to call it SIMBAS for short)...... Read more »
Dimov, I., Basabe-Desmonts, L., Garcia-Cordero, J., Ross, B., Ricco, A., & Lee, L. (2011) Stand-alone self-powered integrated microfluidic blood analysis system (SIMBAS). Lab on a Chip, 11(5), 845. DOI: 10.1039/C0LC00403K
Scientists made the startling assertion this week that RNA from our food can survive digestion, sneak into our cells, and control our genes. Tiny molecular messengers made inside other species--even other kingdoms of species--work just fine in our bodies, latching onto our genetic material and causing system-wide change. Our understanding of diet and nutrition may be in for a shake-up.
A group of researchers in China has been studying microRNAs (abbreviated miRNAs). These stunted nucleotide chains, instead of carrying genetic material themselves, regulate how genes are expressed. MicroRNAs bind to our genes and affect their activity, usually dialing it down. Unlike non-micro DNA or RNA, miRNAs can leave the cell and circulate through the body with the blood.
Looking at a group of healthy Chinese men and women, the researchers identified about 30 miRNAs circulating in their blood that weren't human, or even mammalian, in origin: They came from plants. A structural difference confirmed that the tiny molecules were made in plants, and weren't just animal mimics. Checking the blood of other mammals including mice, horses, and cows, the researchers found more plant miRNAs.
Since a couple of the plant miRNAs that cropped up most often in subjects' bodies are also present in rice, the researchers guessed they were coming from the rice the subjects ate. They used mice to test their theory. The rice miRNA was already present in laboratory mouse chow--explaining its presence in mouse circulatory systems--but there's much more of it in rice. So the scientists fed fresh rice to mice and measured the miRNAs in their systems several hours afterward. Sure enough, higher levels of rice miRNAs appeared throughout the digestive systems of the mice.
The miRNAs seemed to be able to survive both cooking and digestion. Researchers tried leaving them in acid for six hours, simulating the effect of stomach acid, but the miRNAs still didn't break down.
Once intact plant miRNAs left the digestive system and passed into body tissues, were they doing anything? Looking at human cells, the researchers found that the miRNAs from rice latched onto a certain gene that's active in the liver. The gene is responsible for removing LDL ("bad cholesterol") from the circulatory system. When the miRNAs from rice bound to the gene, it was less active. In mice that had eaten rice, the same liver gene was less active--and a few days later, the mice had higher levels of LDL cholesterol in their systems. The liver genes had been dialed down by plant miRNAs, and circulating cholesterol had risen as a result.
The authors think cells in the small intestine take up miRNAs from our digestive tracts, package them into little bubbles called microvesicles, and send them into our circulatory systems. From there, miRNAs find the tissues and cell types they fit best with.
What's incredible is that RNA molecules from an entirely different kingdom of life can affect our genes. The last time we shared a common ancestor with a rice plant, it was single-celled. Almost nothing about us is the same. But their keys still fit in our locks. Plant miRNAs may do a different job in our bodies than in the plants they come from, but we've been evolving with these visitors all along. Our bodies must expect them, and even need them, to enter with our food.
If miRNAs from plants can function in our body, then any and every other food source could be passing us miRNAs that tweak the activity of our genes. "Food-derived miRNAs may serve as a novel essential nutrient," the authors say, as important to our diet as vitamins and minerals. MicroRNAs could be added to foods as fortification. Illnesses could be tied to miRNA deficiencies in our diets. We could take Flintstones chewable miRNAs to stay healthy.
MicroRNAs seem nearly indestructible--they apparently handle being cooked and digested with no problem. But it's possible that our treatment of certain foods destroys their miRNAs. When we eat highly processed foods, are we depriving our bodies of nutrients we never knew existed? And as genetically modified crops become more ubiquitous, we'll want to consider whether we're modifying those crops' miRNAs as well, and how those changes might help or harm us. Staple crops such as rice and corn aren't just foods on our plates; they're also old acquaintances that share responsibility for regulating our genes. Whatever we do to our food, it'll be best if we can still recognize each other.
Zhang, L., Hou, D., Chen, X., Li, D., Zhu, L., Zhang, Y., Li, J., Bian, Z., Liang, X., Cai, X., Yin, Y., Wang, C., Zhang, T., Zhu, D., Zhang, D., Xu, J., Chen, Q., Ba, Y., Liu, J., Wang, Q., Chen, J., Wang, J., Wang, M., Zhang, Q., Zhang, J., Zen, K., & Zhang, C. (2011). Exogenous plant MIR168a specifically targets mammalian LDLRAP1: evidence of cross-kingdom regulation by microRNA Cell Research DOI: 10.1038/cr.2011.158
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Zhang, L., Hou, D., Chen, X., Li, D., Zhu, L., Zhang, Y., Li, J., Bian, Z., Liang, X., Cai, X.... (2011) Exogenous plant MIR168a specifically targets mammalian LDLRAP1: evidence of cross-kingdom regulation by microRNA. Cell Research. DOI: 10.1038/cr.2011.158
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