by Carmen Drahl in The Haystack
As the race to discover a new obesity drug continues, it’s important to consider what makes a good obesity drug target. Before you bother putting a team of medicinal chemists on the job of making a small molecule that could be the next big diet pill, what do you need to know about the target [...]... Read more »
Han, Z., Niu, T., Chang, J., Lei, X., Zhao, M., Wang, Q., Cheng, W., Wang, J., Feng, Y., & Chai, J. (2010) Crystal structure of the FTO protein reveals basis for its substrate specificity. Nature. DOI: 10.1038/nature08921
by Michael Long in Phased
Tetsuo Nagano (University of Tokyo) and coworkers have developed an improved detection protocol for acrolein, a possible indicator of stroke and other medical conditions, which will facilitate rapid diagnosis and medical treatment. This news feature was written on April 11, 2010.... Read more »
Togashi, M., Urano, Y., Kojima, H., Terai, T., Hanaoka, K., Igarashi, K., Hirata, Y., & Nagano, T. (2010) Sensitive Detection of Acrolein in Serum Using Time-Resolved Luminescence. Organic Letters, 12(8), 1704-1707. DOI: 10.1021/ol1002219
by Duncan Hull in O'Really?
Chemical Entities of Biological Interest (ChEBI) release 67 is now available, containing 548,850 total entities, of which 20,565 are annotated entities and 720 were submitted via the ChEBI submission tool. New in this release, the ChEBI ontology is now available in Web Ontology Language (OWL), which is part of an ongoing research project to automate [...]... Read more »
Wishart, D., Knox, C., Guo, A., Eisner, R., Young, N., Gautam, B., Hau, D., Psychogios, N., Dong, E., Bouatra, S.... (2009) HMDB: a knowledgebase for the human metabolome. Nucleic Acids Research, 37(Database). DOI: 10.1093/nar/gkn810
Kuchino, Y., Mori, F., Kasai, H., Inoue, H., Iwai, S., Miura, K., Ohtsuka, E., & Nishimura, S. (1987) Misreading of DNA templates containing 8-hydroxydeoxyguanosine at the modified base and at adjacent residues. Nature, 327(6117), 77-79. DOI: 10.1038/327077a0
Wu LL, Chiou CC, Chang PY, & Wu JT. (2004) Urinary 8-OHdG: a marker of oxidative stress to DNA and a risk factor for cancer, atherosclerosis and diabetics. Clinica chimica acta; international journal of clinical chemistry, 339(1-2), 1-9. PMID: 14687888
Schriner, S. (2005) Extension of Murine Life Span by Overexpression of Catalase Targeted to Mitochondria. Science, 308(5730), 1909-1911. DOI: 10.1126/science.1106653
Sumida S, Doi T, Sakurai M, Yoshioka Y, & Okamura K. (1997) Effect of a single bout of exercise and beta-carotene supplementation on the urinary excretion of 8-hydroxy-deoxyguanosine in humans. Free radical research, 27(6), 607-18. PMID: 9455696
Tarng DC, Huang TP, Wei YH, Liu TY, Chen HW, Wen Chen T, & Yang WC. (2000) 8-hydroxy-2'-deoxyguanosine of leukocyte DNA as a marker of oxidative stress in chronic hemodialysis patients. American journal of kidney diseases : the official journal of the National Kidney Foundation, 36(5), 934-44. PMID: 11054349
Fujihara, J., Agusa, T., Tanaka, J., Fujii, Y., Moritani, T., Hasegawa, M., Iwata, H., Tanabe, S., & Takeshita, H. (2009) 8-Hydroxy-2′-deoxyguanosine (8-OHdG) as a possible marker of arsenic poisoning: a clinical case study on the relationship between concentrations of 8-OHdG and each arsenic compound in urine of an acute promyelocytic leukemia patient being treated with a. Forensic Toxicology, 27(1), 41-44. DOI: 10.1007/s11419-008-0062-x
by Callan Bentley in Mountain Beltway
Almost a year ago, on my old blog, I brought up the issue of the Suess effect. Go read that post if you don’t remember what the Suess effect is. If you want an executive summary, digest this: The burning of low-14C fossil fuels (because the fuels are old and the 14C has all decayed), [...]... Read more »
Peter K. Swart, Lisa Greer, Brad E. Rosenheim, Chris S. Moses, Amanda J. Waite, A. Winter, Richard E. Dodge, & Kevin Helmle. (2010) The 13C Suess effect in scleractinian corals mirror changes in the anthropogenic CO2 inventory of the surface oceans. GEOPHYSICAL RESEARCH LETTERS,. info:/10.1029/2009GL041397.
by The Curious Wavefunction in The Curious Wavefunction
Virtual screening (VS), wherein a large number of compounds are screened, either by docking against a protein target of interest or by similarity searching against a known active, is one of the most popular computational techniques in drug discovery. The goal of VS is to complement high-throughput screening (HTS) and the ideal goal is to at least partly substitute HTS in finding new hits.But this goal is still far from being achieved. VS still has to make a significant contribution in the discovery of a major drug and typical hit rates range from a few tenths of a percent to perhaps a percent or two. VS has been intensively investigated for more than a decade. What do we know about its limitations, and where do we go from here?Gisbert Schneider of ETH Zurich has some thoughts on VS in a recent review. Success in VS ultimately boils down to understanding the detailed structure and dynamics of protein-ligand complexes, a goal that we are still miles away from. We still struggle to realistically include entropy in any calculation, and we are still not completely clear about the role that buried water molecules play in dictating ligand binding. Plus we cannot yet take allosteric binding properly into account, let alone more complex interactions like protein-protein interactions. Thus, maybe, as pointed out in a past post and article, the correct question to ask would be the "anti-question", namely, why does VS work at all in spite of this supposedly woeful lack of understanding?First of all it is important to know what VS can do well and what it can't. As the article notes, VS is still best for negative selection, that is for weeding out inactive molecules which are bad binders. One of the goals of VS is also to duplicate the correct protein-bound x-ray conformation of the ligand, and in this endeavor (termed pose prediction) VS seems to be succeeding much better than in the ultimate goal which is to rank ligand binding to a protein in order of free energy of binding. As the article notes, the true binding interaction energy landscape for a protein might be more of a plateau; thus there may be a variety of protein-ligand contacts corresponding to a 'good' solution, rather than a global optimum. Plus, one may end up modeling details that are not very relevant to the gist of the ligand binding event; in such a case productive contacts can be preserved with no great sacrifice of qualitative prediction.Nonetheless, tiny details can sometimes radically shift the balance. No wonder that VS has been heavily dependent on the target rather than on the computational algorithm. Nature continues to throw up surprises as protein entropy, hydrophobic interactions and subtle behavior of water molecules continue to be uncovered as powerful forces operating for a particular protein-ligand complex.In the end, modeling the dynamic behavior of macromolecules is an absolute must for lending general utility to VS campaigns. In the absence of adequate modeling of entropy, it may be wise from a practical viewpoint to aim for ligand chemotypes whose binding is dominated more by enthalpic effects. It's interesting to note a past set of studies which I had highlighted which suggested that it's really the enthalpy rather than entropy which is rendered favorable in a drug discovery project as one proceeds from hit to lead.Finally, the author makes an appeal to fields spread far and wide to come up with ideas that could be applied in VS and related approaches. It is likely that while incremental improvements will continue to be made in the field through better understanding of protein-ligand interactions, only a novel idea would revolutionize the field. Thus insights could possibly come from unlikely quarters, including complexity theory, non linear dynamics, other aspects of physics and even engineering and architecture. How this might happen is not at all clear, but it definitely calls for more multidisciplinary work and for more scientists from diverse fields to become interested in the problem. After all VS is fundamentally an optimization problem, one of locating the optimal ligand energetic minimum in a multidimensional landscape of protein, ligand, ions and solvent. I can't see why any mathematician, physicist or engineer worth his or her salt won't find it exciting.Schneider, G. (2010). Virtual screening: an endless staircase? Nature Reviews Drug Discovery, 9 (4), 273-276 DOI: 10.1038/nrd3139... Read more »
Schneider, G. (2010) Virtual screening: an endless staircase?. Nature Reviews Drug Discovery, 9(4), 273-276. DOI: 10.1038/nrd3139
by Duncan Hull in O'Really?
Whatever your inclination, it’s difficult to ignore that sandwiched between the Vernal equinox and Beltane, it’s Easter time already. So Happy Easter, Frohe Ostern or Καλό Πάσχα, as they say down south, to all readers of this O’Really? blog.
If you’re gorging yourself on chocolate (see picture right), you might like to consider the food science [...]... Read more »
Stephen T. Beckett. (2000) The Science Of Chocolate. Royal Society of Chemistry Publihshing. DOI: 10.1039/9781847552143
by Michael Long in Phased
John Koh (University of Delaware, United States) and coworkers have fabricated primitive "artificial tissue," which will help shed light on the biochemical consequences of cellular arrangement into defined patterns for tissue and organ assembly. This news feature was written on March 30, 2010.... Read more »
Sauers, D. J., Temburni, M. K., Biggins, J. B., Ceo, L. M., Galileo, D. S., & Koh, J. T. (2010) Light-Activated Gene Expression Directs Segregation of Co-cultured Cells . ACS Chemical Biology, 5(3), 313-320. DOI: 10.1021/cb9002305
by The Curious Wavefunction in The Curious Wavefunction
Just like bioinformatics, cheminformatics has come into its own an independent framework and tool for drug design. As a measure of the field's independence and importance, consider that at least five journals primarily dedicated to it have emerged in the last couple of years, and 15000 articles on it have been published since 2003.But how useful is it in drug discovery? The answer, just like for other approaches and technologies, is that it depends. For calculating and analyzing some properties it is more useful than for others. A group at Abbott summarizes the current knowledge of cheminformatics approaches as applied to various parameters.To do this the group utilizes a useful classification made (in)famous by ex-Secretary of Defense Donald Rumsfeld (Rumsfeld et al., J. Improb. Res. 2002). This is the classification of knowledge and facts into 'known knowns', 'unknown knowns', 'known unknowns' and 'unknown unknowns'.The 'known known' category of properties calculated by cheminformatics consists of those that we think we have a very accurate handle on and that are easy to calculate. These include molecular weight, substructure (SS) searches, and ligand efficiency. Molecular weight can be easily calculated, and a variety of studies have indicated that high MW generally impacts drug discovery negatively. Thus the general thrust is on keeping your compounds small. Ligand efficiency is calculated as the free energy of binding per heavy atom. Medicinal chemists are more familiar with IC50 than free energy. Since IC50s are usually easy to measure and the number of heavy atoms are of course known, ligand efficiency would be a 'known known'. However the caveat is that IC50 is not the same as in vivo activity, so biochemical potency in terms of ligand efficiency might be a very different kettle of fish. Lastly, substructure searches can be carried out easily by many computer programs. Such searches are usually used when a compound having a substructure similar to one that is known is sought. The problem with SS searches arises when the decision on which SS to search becomes subjective. SS is also valuably used when certain SSs are to be avoided. In general SS searching belongs with the 'known known' category because of its ease, but subjective interpretations can render this more fuzzy.In the 'unknown knowns' category lie an interesting set of properties; those which we think we know how to calculate but which sometimes look deceptively simple and are often subject to overconfidence in calculation. The first property in this category is one of the most important ones in drug design; logP, which is regarded to be a measure of the lipophilicity of the compound, a key parameter dictating absorption, bioavailability, and partitioning of drugs between membranes and body fluids. Several programs can calculate logP. However, as the article notes, a recent study of no less than 30 such programs located a mean error in logP calculation of 1 log unit, which means that some programs would do much worse. Thus calculation of logP, just like other computational techniques, crucially depends on the method used to calculate it. The caveat is that absolute cutoffs for logP values in library design of compounds searches might mislead, but many programs seem to do a fairly good job in producing trends. Solubility is another parameter that is notoriously difficult to calculate, especially since its calculation hinges on calculation of pKa values. pKa values in turn again are very method-dependent, and trouble arises especially for charged compounds, which include most drugs. Medicinal chemists are understandably suspicious of theoretical solubility prediction, but as for logP, such calculations may at least be used for quick estimation of qualitative trends. Another parameter in this category is plasma protein binding. Although we know a fair amount about the effect of this parameter on drug ADME, good luck trying to calculate this. Lastly, in vivo ADME is a minefield of complications. I personally would not have placed this in the 'unknown knowns' category, but at least some of the properties in this category can be calculated on the basis of specialized fragment-based models.What about 'known unknowns'? This includes polar surface area (PSA)'. PSA is a known unknown because we know that is not exactly a real, measurable quantity. However it is still a useful parameter since PSA has been shown to relate to membrane permeability and hence is especially useful for guessing blood-brain barrier penetration for CNS drugs. A set of rules similar to the Lipinski rules says that compounds with a PSA of less than 120 A^2 are more likely to penetrate membranes. As for other properties though, calculation of PSA depends on method and usually involves calculating the 3D structure of a molecule and then calculating the PSA by assigning some kind of a 'surface area' associated with polar atoms. As the article notes, one can get wildly different results depending on which atoms are assigned as 'polar'. Plus compounds containing sulfur or phosphorus can result in big discrepancies. Clearly PSA is a useful parameter, but we have to go some way in calculating it reliably. Finally, similarity searching is all the rage these days and promises a windfall of potential discoveries. In its simplest incarnation, similarity searching aims to discover compounds similar in some structural metric to a given compound, with the assumption that similarity in structure would correspond to similarity in function. But similarity, just like beauty, is notoriously in the eye of the beholder. As the authors quip from a quaint piece of literature-related controversy:Deciding whether two molecules are similar is much like trying to decide whether something is beautiful. There are no concrete definitions, and most chemists take an “I know it when I see it” attitude (attributed to United States Justice Potter Stewart, concurring opinion in Jacobellis v. Ohio 378 U.S. 184 (1964), regarding possible obscenity in The Lovers)." As again illustrated, different similarity searching methods give very different hits. One of the most successful metrics for measuring similarities has turned out to be the 'Tanimoto coefficient', but other metrics are also rampant. Thus it is quite remarkable that similarity is already being used widely in every endeavor from virtual screening to finding new protein targets for old drugs based on drug similarity. One of the most valuable application of similarity is in finding bioisosteres (chemically similar fragments), something which medicinal chemists strive for all the time. A recent review of similarity-based methods in JMC summarizes the utility of such techniques. Nonetheless, similarity based methods are still in the 'known unknowns' because we don't have an objective handle on what constitutes similarity, and we may never have such a handle even if such methods are widely and successfully adopted.Finally we come to the dreaded 'unknown unknowns'. As the authors, can we even list properties which we have no idea about? We can take a shot. This category includes flight of fancy which may never be achieved but which are worth striving for. One such holy grail is the large-scale, high-throughput computation of binding free energies. The binding free energy for a protein ligand complex includes contributions from an enormous numbers of complicated factors, but the mere attempt to calculate all these factors have valuably increased our understanding of biological systems. Thus we should continue in this endeavor. Another fancy endeavor which is the talk of the town these days is systems biology, where construction of biological networks and applications of graph theory are supposed to shed valuable light on molecular interactions. Such approaches may well be successful, but they always run the risk of becoming too abstract and divorced from reality to be truly understandable. QSAR models can suffer from the same shortcomings.In the end, only a robust collaboration between informaticians, computer scientists, medicinal chemists and biologists can make sense of the jungle of data uncovered by cheminformatics approaches. It is key for one group of scientists to keep reality checks on others. In the end it's all about reality checks. And it is necessary if we are to successfully rescue the 'unknown unknowns' into other territory, and if we are to avoid the fiasco that the previous classification of these categories led to.Muchmore, S., Edmunds, J., Stewart, K., & Hajduk, P. (2010). Cheminformatic Tools for Medicinal Chemists Journal of Medicinal Chemistry DOI: 10.1021/jm100164z... Read more »
Muchmore, S., Edmunds, J., Stewart, K., & Hajduk, P. (2010) Cheminformatic Tools for Medicinal Chemists. Journal of Medicinal Chemistry, 2147483647. DOI: 10.1021/jm100164z
by Katie Kline in EcoTone
One hundred million years ago, Earth experienced its first great peak in biodiversity. Flowers emerged and with them pollinators, dinosaurs towered over newly evolved mammals and marsupials, the steaming jungles were teeming with newly arrived ants and termites, and the oceans were filled with gigantic, air-breathing reptiles. This was life during the Cretaceous period, Earth between two great extinctions.... Read more »
Whiteside, J., Olsen, P., Eglinton, T., Brookfield, M., & Sambrotto, R. (2010) Compound-specific carbon isotopes from Earth's largest flood basalt eruptions directly linked to the end-Triassic mass extinction. Proceedings of the National Academy of Sciences. DOI: 10.1073/pnas.1001706107
Organ, C., Janes, D., Meade, A., & Pagel, M. (2009) Genotypic sex determination enabled adaptive radiations of extinct marine reptiles. Nature, 461(7262), 389-392. DOI: 10.1038/nature08350
Pennisi, E. (2010) On Rarity and Richness. Science, 327(5971), 1318-1319. DOI: 10.1126/science.327.5971.1318
Boyce, C., Brodribb, T., Feild, T., & Zwieniecki, M. (2009) Angiosperm leaf vein evolution was physiologically and environmentally transformative. Proceedings of the Royal Society B: Biological Sciences, 276(1663), 1771-1776. DOI: 10.1098/rspb.2008.1919
Schulte, P., et al. (2010) The Chicxulub Asteroid Impact and Mass Extinction at the Cretaceous-Paleogene Boundary. Science, 327(5970), 1214-1218. DOI: 10.1126/science.1177265
by Katie Kline in EcoTone
One hundred million years ago, Earth experienced its first great peak in biodiversity. Flowers emerged and with them pollinators, dinosaurs towered over newly evolved mammals and marsupials, the steaming jungles were teeming with newly arrived ants and termites, and the oceans were filled with gigantic, air-breathing reptiles. This was life during the Cretaceous period, Earth between two great extinctions.
... Read more »
Whiteside, J., Olsen, P., Eglinton, T., Brookfield, M., & Sambrotto, R. (2010) Compound-specific carbon isotopes from Earth's largest flood basalt eruptions directly linked to the end-Triassic mass extinction. Proceedings of the National Academy of Sciences. DOI: 10.1073/pnas.1001706107
Organ, C., Janes, D., Meade, A., & Pagel, M. (2009) Genotypic sex determination enabled adaptive radiations of extinct marine reptiles. Nature, 461(7262), 389-392. DOI: 10.1038/nature08350
Pennisi, E. (2010) On Rarity and Richness. Science, 327(5971), 1318-1319. DOI: 10.1126/science.327.5971.1318
Boyce, C., Brodribb, T., Feild, T., & Zwieniecki, M. (2009) Angiosperm leaf vein evolution was physiologically and environmentally transformative. Proceedings of the Royal Society B: Biological Sciences, 276(1663), 1771-1776. DOI: 10.1098/rspb.2008.1919
Schulte, P., et al. (2010) The Chicxulub Asteroid Impact and Mass Extinction at the Cretaceous-Paleogene Boundary. Science, 327(5970), 1214-1218. DOI: 10.1126/science.1177265
by Michael Long in Phased
Ren'an Wu, Hanfa Zou (Chinese Academy of Sciences), and coworkers have used carbon nanotubes to kill the cancer cells that commonly linger after chemotherapy, which are a major threat to successful treatment. This news feature was written on March 23, 2010.... Read more »
Li, R., Wu, R., Zhao, L., Wu, M., Yang, L., & Zou, H. (2010) P-Glycoprotein Antibody Functionalized Carbon Nanotube Overcomes the Multidrug Resistance of Human Leukemia Cells. ACS Nano, 4(3), 1399-1408. DOI: 10.1021/nn9011225
by agoldstein in WiSci
Bhut jolokia is now confirmed to be the world’s spiciest chili and is being used to create natural, nontoxic weapons.... Read more »
Liu Y, & Nair MG. (2010) Capsaicinoids in the hottest pepper Bhut Jolokia and its antioxidant and antiinflammatory activities. Natural product communications, 5(1), 91-4. PMID: 20184029
by Rob Mitchum in ScienceLife
Stem cells are a little like teenagers, full of potential but not sure what they’re going to be when they grow up. It’s that uncertain destiny that makes stem cells so exciting to scientists and physicians, who hope to someday use them for everything from spinal cord repair to organ regeneration. But corralling the uncertain [...]... Read more »
Kilian, K., Bugarija, B., Lahn, B., & Mrksich, M. (2010) Geometric cues for directing the differentiation of mesenchymal stem cells. Proceedings of the National Academy of Sciences, 107(11), 4872-4877. DOI: 10.1073/pnas.0903269107
by Neuroskeptic in Neuroskeptic
Absinthe is a spirit. It's very strong, and very green. But is it something more?I used to think so, until I came across this paper taking a skeptical look at the history and science of the drink, Padosch et al's Absinthism a fictitious 19th century syndrome with present impactAbsinthe is prepared by crushing and dissolving the herb wormwood in unflavoured neutral alcohol and then distilling the result; other herbs and spices are added later for taste and colour.It became extremely popular in the late 19th century, especially in France, but it developed a reputation as a dangerous and hallucinogenic drug. Overuse was said to cause insanity, "absinthism", much worse than regular alcoholism. Eventually, absinthe was banned in the USA and most but not all European countries.Much of the concern over absinthe came from animal experiments. Wormwood oil was found to cause hyperactivity and seizures in cats and rodents, whereas normal alcohol just made them drunk. But, Padosch et al explain, the relevance of these experiments to drinkers is unclear, because they involved high doses of pure wormwood extract, whereas absinthe is much more dilute. The fact that authors at the time used the word absinthe to refer to both the drink and the pure extract added to the confusion.It's now known that wormwood, or at least some varieties of it, contains thujone, which can indeed cause seizures, and death, due to being a GABA antagonist. Until a few years ago it was thought that old-style absinthe might have contained up to 260 mg of thujone per litre, a substantial dose.But that was based on the assumption that all of the thujone in the wormwood ended up in the drink prepared from it. Chemical analysis of actual absinthe has repeatedly found that it contains no more than about 6 mg/L thujone. The alcohol in absinthe would kill you long before you drank enough to get any other effects. As the saying goes, "the dose makes the poison", something that is easily forgotten.As Padosch et al point out, it's possible that there are other undiscovered psychoactive compounds in absinthe, or that long-term exposure to low doses of thujone does cause "absinthism". But there is no evidence for that so far. Rather, they say, absinthism was just chronic alcoholism, and absinthe was no more or less dangerous than any other spirit.I'm not sure why, but drinks seem to attract more than their fair share of urban myths. Amongst many others I've heard that the flakes of gold in Goldschläger cause cuts which let alcohol into your blood faster; Aftershock crystallizes in your stomach, so if you drink water the morning afterwards, you get drunk again; and that the little worm you get at the bottom of some tequilas apparently contains especially concentrated alcohol, or hallucinogens, or even cocaine maybe.Slightly more serious is the theory that drinking different kinds of drinks instead of sticking to just one gets you drunk faster, or gives you a worse hangover, or something, especially if you do it in a certain order. Almost everyone I know believes this, although in my drinking experience it's not true, but I'm not sure that it's completely bogus, as I have heard somewhat plausible explanations i.e. drinking spirits alongside beer leads to a concentration of alcohol in your stomach that's optimal for absorption into the bloodstream... maybe.Link: Not specifically related to this but The Poison Review is an excellent blog I've recently discovered all about poisons, toxins, drugs, and such fun stuff.Padosch SA, Lachenmeier DW, & Kröner LU (2006). Absinthism: a fictitious 19th century syndrome with present impact. Substance abuse treatment, prevention, and policy, 1 (1) PMID: 16722551... Read more »
Padosch SA, Lachenmeier DW, & Kröner LU. (2006) Absinthism: a fictitious 19th century syndrome with present impact. Substance abuse treatment, prevention, and policy, 1(1), 14. PMID: 16722551
by The Curious Wavefunction in The Curious Wavefunction
As is well-known, peptides helices can be right or left handed. Many details of structure, amino acid identity and orientation can control this screw sense, and sometimes the controlling factors can be quite subtle. In a JACS communication, Jonathan Clayden (yes, the co-author of the amazing organic chemistry textbook) and his group uncover a surprising factor that controls the helical screw sense and also incorporate a neat "reporter group" to monitor the screw sense.But this reporter group is nothing fancy and is simply a gycine installed in the middle of a long sequence of amino acids which consists of alpha-aminoisobutyric acid or Aib. Aib is simply alanine with an extra methyl at the alpha carbon. It is well known to impart helical propensities to peptides and has been used several times as a helical 'lock'.In this case the Gly is in the center of a 20 amino acid peptide where all other residues are Aib. The peptide is clearly helical, but what's the screw sense? That's where the power of NMR spectroscopy comes in. The two protons in Gly are diastereotopic which means that in principle they could have different chemical shifts and signals in the NMR spectrum. In practice though, rapid interconversion between the left and right handed helices leads to an average and gives a single signal in the spectrum.However if interconversion between the two screw senses could be 'biased' by making the equilibrium constant favor one of them, then one could presumably observe two separate signals for the two Gly protons even if the transition is fast on the NMR time scale. To accomplish this, Clayden et al. do something peculiar; they incorporate a L-Phe residue at the N-terminal of the helix. This group, even if far away from the central Gly, somehow seems to remotely interact differently with each of the two Gly protons. The incorporation of this terminal group leads to a considerable splitting in the signals of the two protons (up to 100 ppm), easily distinguishing them apart. Also for some reason, N-terminal groups seem to work better than C-terminal groups.The reasons for the transmission of this effect over no less than 27 bonds are not clear, but they probably have something to do with the subtle change in conformational behavior that dictate helix folding. The authors even observe small differences for amide vs ester bonds as capping groups. Finally, they obtain an x-ray structure of this helix which turns out to be a 3/10 helix and confirm their observations.These days there is a drive to 'tether' certain parts of oligopeptides to lock the resulting conformation in a helical form. Sometimes, even constraining end groups covalently (by metathesis for instance) seems to ensure a critical 'nucleation' structure that then zips up the rest of the helix. The exact percentage of the helix in solution could be a matter for discussion, but this study seems to indicate similiar end-group influenced conformational organization. I thought it was neat and points to further challenges and questions in our understanding of the deceptively simple question, "Why are helices stable in solution"?Solà, J., Helliwell, M., & Clayden, J. (2010). N- versus C-Terminal Control over the Screw-Sense Preference of the Configurationally Achiral, Conformationally Helical Peptide Motif Aib-Gly-AibJournal of the American Chemical Society DOI: 10.1021/ja100662d... Read more »
Solà, J., Helliwell, M., & Clayden, J. (2010) N- versus C-Terminal Control over the Screw-Sense Preference of the Configurationally Achiral, Conformationally Helical Peptide Motif Aib GlyAib . Journal of the American Chemical Society, 2147483647. DOI: 10.1021/ja100662d
by calvinus in Post Tenebras Lux
Solar cells can be thought of as an artificial leaf, turning sunlight into energy. Mimicking the surface of lotus leaves takes this analogy one step further.... Read more »
Zhu, J., Hsu, C., Yu, Z., Fan, S., & Cui, Y. (2009) Nanodome Solar Cells with Efficient Light Management and Self-Cleaning. Nano Letters, 2147483647. DOI: 10.1021/nl9034237
by Lars Fischer in EuCheMS 2010 Blog
Hydrogels are the only materials that have the potential to be used as a replacement material for functional tissues like cartilage, sinews or muscles. However, while the biological wet and soft materials have impressive mechanical properties and are generally very tough, conventional hydrogels are rather brittle and tend to disintegrate under duress. With one exception, [...]... Read more »
Gong, J. (2010) Why are double network hydrogels so tough?. Soft Matter. DOI: 10.1039/b924290b
by Michael Long in Phased
Kenneth Suslick (University of Illinois, Urbana-Champaign, United States) and coworkers have discriminated between 10 different brands of coffee, based on the volatile chemicals they emit under roasting, within two minutes with a cheap, disposable synthetic nose. This news feature was written on March 11, 2010.... Read more »
Suslick, B. A., Feng, L., & Suslick, K. S. (2010) Discrimination of Complex Mixtures by a Colorimetric Sensor Array: Coffee Aromas. Analytical Chemistry, 82(5), 2067-2073. DOI: 10.1021/ac902823w
by UUCJC in Uppsala University Cheminformatics Journal Club
The article, Towards pharmacogenomics knowledge discovery with the semantic web, written by Michael Dumontier and Natalia Villanueva-Rosales attempts to demonstrate the importance of pharmacogenomics and how the data should be structured in the best possible way. Their strategy towards knowledge discovery involves ontology design, population and question answering. In a more specific manner this was established with Web Ontology Language OWL-DL, Protégé and Manchester OWL Syntax.With the SO-Pharm project as inspiration the authors attempts to improve the area of pharmacogenomic by reducing classes and instances and focus on better relations creating a not so complex base. In this manner the authors intended to extend the existing knowledge base PharmGKB with OWL-DL. The area of application lies within personalized medicine where knowledge around depression is their main field. Hence the management system Protégé is used with Manchester OWL Syntax as query language to ease the use for doctors, researchers and patients.The methods used for the design of the knowledge base (PO) is described in a very detailed way but unfortunately this is quite hard to come to grips with as a rookie in the field. Their aim for the design was to create a ground where it would be easy for researchers and doctors to use the system.The authors discuss the use of XML in the semantic web. Sadly they do so in a less then awesome way, claiming that XML lack semantics, and then later in the article they use the built in semantics of XML for doing automated converting of data stored in XML. Although the authors probably have a point in that the semantics of RDF and OWL is more explicit and powerful it is important to remember that XML is a syntactic language while OWL is a data model. The OWL data model can be stored in XML. Thus just stating that XML lack semantics is a bit like saying that a book does not contain a good chaptering -- it is not enforced but it sure could contain it... There are many data formats based on XML and the point here is that they can be very different and it is difficult to say general things about XML in this way.The use of XML2OWL for converting from the XMLS of PharmGKB to OWL highly states that XML do have semantics.The way that they use the words class and concepts creates greater confusion since class and concept is the same in ontology. Sometimes the word concept is referred to it self and other times as class. “... representation containing 70 core classes and over 40000 concepts..” and further into the text “... Pharmacogenomics Ontology identifies 40 core concepts...”.In the area of relations there must be further development. Even though many relationships are correctly described with the Basic Relation Ontology (BRO) some relationships are only described as bro:isRelatedTo, because of the low level of semantics. But in order to create an accurate base for knowledge retrieval where all queries are possible this must be managed.The ambition of the research is of importance to a brighter and more knowledge-filled future of personalized medicine. It might have a bit further to go but at least the aim is in the right direction.Annsofie Andersson and Jonathan AlvarssonDumontier, M., & Villanueva-Rosales, N. (2009). Towards pharmacogenomics knowledge discovery with the semantic web Briefings in Bioinformatics, 10 (2), 153-163 DOI: 10.1093/bib/bbn056... Read more »
Dumontier, M., & Villanueva-Rosales, N. (2009) Towards pharmacogenomics knowledge discovery with the semantic web. Briefings in Bioinformatics, 10(2), 153-163. DOI: 10.1093/bib/bbn056
by Michael Long in Phased
Shin-Yuan Liu (University of Oregon, United States) and coworkers have addressed a challenge that is often brushed aside in hydrogen fuel cell research, but which is absolutely critical for practical, real-world applications. This news feature was written on March 10, 2010.... Read more »
Campbell, P. G., Zakharov, L. N., Grant, D. J., Dixon, D. A., & Liu, S.-Y. (2010) Hydrogen Storage by Boron−Nitrogen Heterocycles: A Simple Route for Spent Fuel Regeneration. Journal of the American Chemical Society, 132(10), 3289-3291. DOI: 10.1021/ja9106622
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