Michael Clarkson

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  • March 23, 2009
  • 09:00 PM
  • 1,445 views

Rare codons give domains time to fold

by Michael Clarkson in Conformational Flux

The ribosome produces proteins by matching tRNA that has been correctly loaded with an amino acid to a codon (triplet of DNA bases) in the mRNA that contains the gene sequence. The triplet code allows 64 combinations of nucleotide bases, but proteins are made from only 20 amino acids (plus a "stop" signal). This means that most amino acids are coded by multiple codons, and hence have multiple tRNAs. Not all codons are created equal, however; in bacteria some codons are found much less frequently than others that represent the same amino acid. The tRNA associated with these "rare codons" is also less abundant than other tRNA, and this means that when a ribosome hits a rare codon, it often has to pause while it waits to encounter a loaded tRNA. To structural biologists like myself, who do their work by overexpressing proteins in bacteria, rare codons can be a nuisance because they slow down protein production, or even prevent it entirely. In a recent paper in Nature Structural & Molecular Biology, however, researchers from Germany suggest that the slowdown due to rare codons may have a functional advantage in vivo.As a first step, Zhang et al. used a bioinformatics approach to survey the sequences of bacterial genes so that they could identify patches that would be slow to translate (the Methods section appears to contain an error in the description of this technique). They found that for proteins longer than about 300 amino acid residues, nearly every transcript contained at least one cluster of slow-translating codons. When the authors used a cell-free E. coli expression system to make some of these proteins and allowed only one round of translation initiation per ribosome, they saw a pattern of translation intermediates that matched the sizes predicted by the location of slow-translating patches.In order to find out whether these translation intermediates had any significance, the authors examined the multi-domain protein SufI. In their prediction of the translation speed, which is on top in this figure that I have shamelessly stolen, there are four slow spots. Aside from the first one, these appear to correspond to the boundaries of different structural domains in the protein (lower part of the figure). Experiments with proteases suggested that these domains actually folded during the pauses, as the ribosome-bound translation intermediates were resistant to proteolysis.Interestingly, when two rare leucine codons were replaced by more common ones (the authors call this SufIΔ25-28), the whole protein became vulnerable to degradation. Similarly, when extra tRNA for these rare codons was added to the cell-free expression system, the full-length protein became protease-sensitive. This suggests that the slow patches are actually necessary for proper folding of the protein. It's often the case that lowering the incubation temperature can improve the expression of certain proteins in E. coli. The authors of this study find that is also true for SufI, as the protease resistance of SufIΔ25-28 can be restored by lowering the temperature, and thus the overall translation rate. When analogous experiments with SufIΔ25-28 and tRNA supplementation were carried out in living E. coli, the translocation of SufI into the periplasmic space was reduced by a factor of 10 even though the overall protein concentration was not affected, indicating that the co-translational folding allowed by the rare codons is necessary for proper functioning of the protein in vivo.Of course this is a single case study, and it would be premature to conclude that every patch of rare codons corresponds to an important co-translational folding event. Indeed, that doesn't even appear to be true of SufI, which folds properly when one of its other slow patches is removed. However, at certain key locations these stretches of rare codons may be an important part of the folding machinery in multidomain proteins. In addition, the more frequent appearance of rare codons in β-strands (as opposed to α-helices) may also be related to folding due to the slower kinetics of β-sheet formation. As the authors note, the intrinsic kinetics aren't everything — pauses in the translation process may also buy time for the complex to encounter essential chaperones or cofactors. Regardless of the mechanism, it appears that rare codons, in at least some instances, provide a way for the folding process to catch up with the translation process.Zhang, G., Hubalewska, M., & Ignatova, Z. (2009). Transient ribosomal attenuation coordinates protein synthesis and co-translational folding Nature Structural & Molecular Biology, 16 (3), 274-280 DOI: 10.1038/nsmb.1554... Read more »

Zhang, G., Hubalewska, M., & Ignatova, Z. (2009) Transient ribosomal attenuation coordinates protein synthesis and co-translational folding. Nature Structural , 16(3), 274-280. DOI: 10.1038/nsmb.1554  

  • March 12, 2009
  • 08:30 PM
  • 1,293 views

Urea binds to the peptide group

by Michael Clarkson in Conformational Flux

I've mentioned urea and guanidinium (Gdm) before on this blog, usually with reference to questions about their mechanism of action. These small molecules cause proteins to denature, or lose their higher levels of structure and become unfolded chains. The complete unfolding of a protein typically requires a fairly high concentration of denaturant, almost always more than 1M, and the explanation for this is that the denaturant molecules preferentially associate with the polypeptide chain with low affinity. In a recent issue of PNAS, a paper from Walter Englander argues that urea, but not guanidinium, associates with the backbone of the protein via hydrogen-bonding interactions.Lim et al. reached this conclusion using hydrogen-exchange experiments. Amide nitrogens in proteins freely exchange their covalently-bound hydrogens (protons) with the surrounding water. The rate of this process can be measured (among other ways), by placing a protonated amide group into a deuterated solvent and tracking the decline in proton signal by NMR; this is called an HX experiment. In the case of a folded protein chain the observed rate will depend on the intrinsic chemistry of the particular amide and the stability of the protein structure, because this structure excludes water from the backbone and makes hydrogen bonds that lock the protons in place. Rather than deal with all of that, the authors used a small peptide mimic that (probably) has no complex structure. This had the additional advantage that the simple spectrum could be tracked by 1-D NMR, substantially increasing the time-resolution of the measurements. The authors measured the rates as they varied the pH — because we're talking about D2O, it's called the pD instead — and added various cosolutes that are known to denature or stabilize protein folds.As expected, the dialanine itself had a V-shaped rate profile in these HX experiments, with a minimum at a pD of 4. The hydrogen exchange reaction can be catalyzed by acid or base, so the rate increases as you go up or down in pD from this minimum. When urea was added to the solution, the authors found that acid-catalyzed HX accelerated while base-catalyzed HX decelerated. The most reasonable explanation for the latter result is that a hydrogen bond between the carbonyl of urea and the amide proton protects it from water attack. The authors do some mathematical modeling to establish that the effect on rate reflects a bonding association between the peptide and urea, not just random collisions or thermodynamically neutral associations.The acid-catalyzed result is interesting, because in theory one would expect that urea would accelerate acid-catalyzed HX more than it actually does, because under acidic conditions it can accept a hydrogen from the amide nitrogen. While there are some confounding factors, the most likely explanation for this result is that the NH2 groups of urea form hydrogen bonds to the carbonyl of the peptide. Because acid catalysis of HX hinges on the favorability of protonating this carbonyl, a hydrogen bond would be expected to reduce the HX rate. The authors argue that the ability of urea to serve as an acid catalyst is therefore mitigated by its propensity to bind to the carbonyl.The formation of hydrogen bonds between urea and the peptide group meshes well with evidence that it denatures proteins through interactions with the backbone, some of which I have mentioned before. From HX experiments under native conditions we know that even a folded protein chain regularly undergoes excursions from its water-excluded, hydrogen-bonded state. Urea may bind to the backbone during these fluctuations, preventing or slowing a return to the folded structure.Lim et al. also tested a number of other cosolutes, and found that none of them had a similar effect on the HX rate. In the case of the stabilizing molecules (glycerol, sorbitol) this is entirely expected, as their action cannot be explained in terms of a preferential association with the backbone anyway. The surprise concerns guanidinium, which is a more powerful denaturant than urea. The authors noted that Gdm has a small effect on the rate, but not in a pD-dependent way, and one that was little different from an equivalent concentration of NaCl (ordinary table salt). Gdm has no groups that can hydrogen bond to the amide, so the absence of an effect on base-catalyzed HX is expected. However, it should be possible for guanidinium to hydrogen-bond to the carbonyl, so it should seemingly have an effect on acid catalysis. This is not in fact the case.The authors note that existing evidence does not support the idea that Gdm forms hydrogen bonds with water (although urea is known to do so). Lim et al. suggest instead that the planar Gdm molecule forms favorable stacking interactions with other planar groups. These include the peptide bond and several side chains. They argue that the stacking of Gdm with these groups pries the protein apart without requiring hydrogen bonds.As a means to investigate diseases that result from protein misfolding, many groups are now trying to structurally characterize the unfolded state of protein molecules. Many of these experiments model the in vivo denatured state by using chemical denaturants such as urea or Gdm. The possibility that direct interactions between the denaturant and the protein will give rise to experimental artifacts should be taken seriously. Urea's promiscuous formation of hydrogen bonds with the backbone, itself, and water, may give rise to loose networks of hydrogen-bonded molecules that act to condense the chain. By contrast, Gdm's stacking effect will likely act to artificially extend the chain by steric obstruction. Because of the difference in these mechanisms, it may be of value to cross-validate findings from structural studies on unfolded states by repeating experiments with alternative denaturants.Lim, W., Rosgen, J., & Englander, S. (2009). Urea, but not guanidinium, destabilizes proteins by forming hydrogen bonds to the peptide group Proceedings of the National Academy of Sciences, 106 (8), 2595-2600 DOI: 10.1073/pnas.0812588106... Read more »

Lim, W., Rosgen, J., & Englander, S. (2009) Urea, but not guanidinium, destabilizes proteins by forming hydrogen bonds to the peptide group. Proceedings of the National Academy of Sciences, 106(8), 2595-2600. DOI: 10.1073/pnas.0812588106  

  • February 23, 2008
  • 12:03 AM
  • 1,276 views

The Evolution of Protein Folds

by Michael Clarkson in Conformational Flux

Now online for next week's edition of PNAS is a commentary by Alan R. Davidson (1) about a paper in this week's edition of PNAS out of Matthew Cordes' group (2). Both are worth reading because they speak to a very interesting question: where do new protein folds come from?The Roessler et al. paper doesn't address this question directly. Their initial intention was to identify the relationship between two distantly homologous proteins: P22 Cro and λ Cro. Though they both belong to the Cro repressor superfamily, these two proteins have just 25% sequence identity and significant dissimilar... Read more »

A Davidson. (2008) A folding space odyssey. Proceedings of the National Academy of Sciences. DOI: 10.1073/pnas.0800030105  

C Roessler, B M Hall, W J Anderson, W M Ingram, S A Roberts, W R Montfort, & M H Cordes. (2008) Transitive homology-guided structural studies lead to discovery of Cro proteins with 40% sequence identity but different folds. Proceedings of the National Academy of Sciences, 105(7), 2343-2348. DOI: 10.1073/pnas.0711589105  

E Kuloglu. (2002) Structural Rearrangement of Human Lymphotactin, a C Chemokine, under Physiological Solution Conditions. Journal of Biological Chemistry, 277(20), 17863-17870. DOI: 10.1074/jbc.M200402200  

  • September 18, 2008
  • 09:00 PM
  • 1,273 views

Where do new enzymes come from?

by Michael Clarkson in Conformational Flux

Biochemists often rave about the great wonders of enzymes, lavishing praise on the prodigious rate enhancements they produce, and their exquisite positioning of functional groups. One can quite reasonably ask how such magnificently useful proteins came into being. One accurate answer, of course, is that after a couple hundred million years evolution can get almost anything right. Another answer is that most enzymes come from other proteins, via a process called gene duplication. The genetic changes that follow one of these duplications turn two copies of one protein into two completely different proteins with diverse activities.Gene duplication events are infrequent errors of DNA replication or repair. Diploid eukaryotes such as ourselves carry two copies (or near-copies) of most genes as a matter of course, but gene duplications produce extra copies beyond that. In theory, the presence of these extra copies of a gene means that one of them can mutate freely, without the pressure of carrying out its normal job. When it drifts into a useful function, selective pressure is again applied, causing a refinement of the active site to maximize the efficiency of the new activity. The overall scheme looks something like this:Duplication → Divergence → RefinementIt may seem incredible that a vast diversity of protein structures and activities can arise simply by making copies, even imperfect copies. However, certain quirks of the translation machinery mean that small changes in DNA can amount to enormous changes in a protein's topology. For instance, an insertion or deletion of a single base can cause a frameshift mutation, producing a protein that bears no resemblance to its progenitor despite having only 1 different base pair. Many DNA triplets that normally encode amino acids are only a single base-pair mutation away from becoming a stop codon, truncating a protein and likely changing its structure significantly. Similarly, stop codons can be easily eliminated, producing much larger proteins. In eukaryotes, point mutations near the borders between introns and exons can cause new regions of DNA to be translated into protein. Of course, drastic changes like these mostly just produce useless junk, but occasionally a novel fold or function arises.More conservative alterations of a gene sequence can still produce significant changes. As I've mentioned before on this blog, some members of the Cro family of proteins have very high sequence identity and yet possess different structures. I also have not yet tired of reminding you that the chemokine lymphotactin has two different structures with a single sequence, either of which can be stabilized into an exclusive fold by a point mutation.Additionally, research from the lab of John Orban shows that a mere 7 mutations are required to convert the engineered protein GA88 (PDB) into a completely different structure, GB88 (PDB) (1). These proteins were previously shown to have different folds and functions, but the contrast between the high resolution structures (shamelessly stolen figure on the right) is striking. Moreover, the Orban lab has refined this system so that the structural conversion can be effected with only three mutations, rather than seven. What all this research indicates is that the transitions that convert a sequence from one fold into another may be sharper than previously realized; even a relatively small number of fairly conservative mutations may be able to completely transform a protein's structure.For all that, most new enzymes arising via gene duplication resemble their ancestors in identifiable ways. Often the two proteins perform the same chemical steps, and the novel function amounts to a different substrate specificity. This suggests the possibility of an alternate mechanism of gene duplication, in that a protein could evolve a novel specificity while retaining its original function. Diversifying its activities in this way would probably limit an enzyme's catalytic effect in both reactions, but a subsequent gene duplication event would allow each copy to refine its particular reaction. The scheme would look like this:Diversification → Duplication → RefinementThe advantage of this model, from an adaptationist's perspective, is that it brings selective pressure to bear at every step. Once a new function has evolved in response to environmental conditions, duplicating the gene may provide an organism a concrete advantage. After duplication, the advantage of separately refining the two activities is obvious.The two models are not as different as they might seem at first glance, because nearly every enzyme catalyzes two reactions anyway, that is, the forward and reverse reactions of an equilibrium. A "new" activity for a given enzyme can therefore result from something as simple as being targeted to a different cellular compartment or a change in specificity that involves an oppositely-oriented equilibrium.The most obvious objection to the latter model is that during the period of gene sharing prior to duplication, neither protein function will be very efficient. As a matter of fact, the appearance of a new activity does not always impair an enzyme's ability to do its original job (and indeed can even enhance that activity). Still, because of the exquisite tuning of enzyme active sites we can expect that many modifications to this region will reduce catalytic power. That being the case, how might an organism survive or thrive during the gene-sharing period? The answer, which always seems obvious in retrospect, is to make more of the less efficient enzyme, as was demonstrated in a recent paper by Sean Yu McLoughlin and Shelley Copley (2).McLoughlin and Copley took a strain of E. coli that lacked an enzyme, ArgC, that is critical for glucose metabolism. They treated these bacteria with a strong mutagen and then picked a colony that grew well on uncomplemented glucose. After showing that these bacteria had developed a novel activity equivalent to ArgC, they isolated the "new" enzyme and found that it was actually an existing enzyme, ProA, which performs similar chemistry. This enzyme had gained the ability to take over the tasks of the missing ArgC, enhancing the rate of that reaction 12-fold. The actual chemistry of these reactions was quite similar, but in gaining the ability to operate on ArgC's substrate, the activity of ProA towards its own substrate was reduced 2800-fold. The bacteria compensated for this by upregulating the production of the enzyme. A second mutation in the promoter region of the gene was helpful, but not necessary, in this respect.Because enzymes are catalysts, a small increase in protein concentration can result in a significant increase in the availability of the reaction products. Biochemists often say, seeing a 3000-fold reduction in activity, that an enzyme is dead. The reality is that it's just slower, and a living thing can compensate for that in ways not available to an isolated reaction in a test tube. Organisms have shown that they have ways to survive what an enzymologist might see as fatal.Of course, modern bacteria benefit from a number of well-tuned regulatory and feedback mechanisms that allow them to sense when particular metabolites are running low and to increase the production of proteins that can replenish them. Earlier, more primitive organisms might not have had these expedients available. Could they have survived gene sharing?Too little is known about early life forms to answer such a question definitively. However, it is interesting to note that one method of making more protein is to make more of the gene. That is, the concentration of a deficient enzyme can be increased via gene duplication. By a fortuitous coincidence, a single mechanism could both enable an organism to tolerate reduced enzymatic efficiency and allow the evolutionary process to independently refine its activities.It is also worth bearing in mind that just as ancient organisms did not necessarily resemble modern ones, ancient proteins might not have resembled the modern item. The exquisite positioning of functional groups that characterizes modern enzymes requires a rigid fold and contributes significantly to the rate accelerations they produce. However, substantial rate enhancements can still be achieved in the absence of a stiff native state.One occasional result of mutations is the formation of a molten globule, a protein that lacks a stable fold but still exists in a collapsed state with something resembling a hydrophobic core. Although that doesn't sound particularly useful, many molten globules have enzymatic or other functional activities. Recent computational studies on a molten-globule mutant of Methanococcus jannaschii chorismate mutase suggest that realistically low energy barriers can be achieved by a broader array of structural states in these proteins (3).Researchers from the lab of Arieh Warshel used a simplified model to sample the conformational space available to the molten globule enzyme (mMjCM) and a stably folded form of the enzyme (EcCM). As you might expect, the lowest-energy conformations are much more diverse for mMjCM than for EcCM. Roca et al. then computed the energy barrier for catalysis for conformations that closely resembled the ideal structure (region I), conformations which had most of the groups in the right general position but were significantly removed from the ideal (region II), and conformations that did not resemble the ideal at all (region III). For EcCM, only structures in region I had energy barriers low enough to plausibly allow catalysis. The molten globule, however, had energy barriers that would allow catalysis in region I and region II. You can see this in the figure below, which I shamelessly stole from their paper: the dotted orange line corresponds to a 16 kcal/mol energy barrier, what they felt to be the largest barrier reasonable for a catalyst. The results for mMjCM are on the left, EcCM on the right.The upshot of this is that molten globules may be able to maintain catalytic power in the face of structural diversity that causes folded proteins to fail. While the stable fold produces greater rate enhancements (note that EcCM has lower energy barriers), the molten globule tolerates a wider array of structural conditions. Consequently, proteins of this kind may be much more amenable to the addition of new functions. So long as an appropriate orientation of functional groups is reasonably likely, a protein without a rigid conformation can still achieve impressive rate enhancements.Conceivably, an early molten globule enzyme could have the ability to catalyze several different reactions, switching between the required conformations as needed, without a significant loss of catalytic power to any of them. Duplication of a multi-functional molten globule like this would allow each chemical function to be refined independently, with additional duplications and refinements giving rise to substrate specificity.The different models of gene duplication each have their own explanatory advantages, and the available evidence suggests that new proteins and enzymatic activities have evolved (even within the last century) using both routes. As this is one of nature's favored methods of generating novel activities, so it is becoming ours. The artificial enzymes recently produced by David Baker's lab were designed onto an existing protein scaffold in what could be taken as a computational mimicry of the gene duplication process.1. Y. He, Y. Chen, P. Alexander, P. N. Bryan, J. Orban (2008). NMR structures of two designed proteins with high sequence identity but different fold and function Proceedings of the National Academy of Sciences, 105 (38), 14412-14417 DOI: 10.1073/pnas.08058571052. S. Y. McLoughlin, S. D. Copley (2008). A compromise required by gene sharing enables survival: Implications for evolution of new enzyme activities Proceedings of the National Academy of Sciences, 105 (36), 13497-13502 DOI: 10.1073/pnas.08048041053. M. Roca, B. Messer, D. Hilvert, A. Warshel (2008). On the relationship between folding and chemical landscapes in enzyme catalysis Proceedings of the National Academy of Sciences, 105 (37), 13877-13882 DOI: 10.1073/pnas.0803405105... Read more »

S. Y. McLoughlin, & S. D. Copley. (2008) A compromise required by gene sharing enables survival: Implications for evolution of new enzyme activities. Proceedings of the National Academy of Sciences, 105(36), 13497-13502. DOI: 10.1073/pnas.0804804105  

M. Roca, B. Messer, D. Hilvert, & A. Warshel. (2008) On the relationship between folding and chemical landscapes in enzyme catalysis. Proceedings of the National Academy of Sciences, 105(37), 13877-13882. DOI: 10.1073/pnas.0803405105  

  • January 13, 2009
  • 06:30 PM
  • 1,268 views

How we taste umami

by Michael Clarkson in Conformational Flux

Although we still do not know the full breadth of our flavor-sensing capabilities, human beings are known to possess receptors for at least five basic tastes. Probably you have known about the sweet, sour, salty, and bitter flavors since you were in grade school, but the fifth, umami, was less widely accepted in the West until recently. Umami is a savory flavor element that is found in many foods, including tomatoes, parmesan cheese, truffles, and many kinds of meat and seafood. The umami taste primarily detects the amino acid glutamate (hence the popularity of the food additive monosodium glutamate, or MSG), but the effect is also intensified by the presence of the nucleotide inosine monophosphate (IMP). In a recent (open access) paper in PNAS, researchers from two corporations examined the umami taste receptor to understand how this happens.The umami flavor is detected by a pair of G-protein coupled receptors (GPCRs) that have an external venus flytrap (VFT) domain in addition to their classic 7-helix trans-membrane domain (TMD). This complex is closely related to the sensor for the sweet flavor: in fact one of the receptors (called T1R3) is the same in both sensors. It is the second receptor (T1R1 for umami, T1R2 for sweet) that determines what taste is recognized. What we don't know for sure is whether it is the TMD or the VFT of these receptors that identifies the flavor component.In order to answer this question, the researchers performed an experiment known as a "domain swap". Using recombinant DNA technology they assembled two chimeric proteins, one with the VFT of umami and the TMD of sweet, and one with the VFT of sweet and the TMD of umami. They then inserted these proteins into cultured cells that would fluoresce when the receptors were activated. The authors suspected that the VFT is primarily responsible for binding the ligand. As you can see from figures 1 & 2 (this is an open access paper, so go ahead and take a look), the experiment bears this out. The chimera with the VFT of sweet caused a fluorescent response in the presence of compounds such as sucrose and aspartame, while the umami-VFT chimera reacted to glutamate and aspartate. You can also see in figure 2C that the presence of IMP dramatically enhanced the activity of glutamate in this chimera. This indicates that the VFT is also responsible for IMP synergy in the umami receptor.The hurdle in going further than this is that no structure of the umami VFT is available, which makes it difficult to figure out exactly how everything fits together. However, T1R1 has a close evolutionary relationship to the metabotropic glutamate receptors (mGluR), and a crystal structure of that VFT is available. Using conserved and homologous residues as a guide, the authors made a model of the T1R1 fold from the mGluR data. Based on this model they predicted certain amino acids that would be essential for glutamate binding in T1R1 and then mutated them in order to measure the effect. Residues that were predicted by the model to interact with the zwitterionic amino acid backbone proved to be essential for ligand recognition. Interestingly, the amino acids that contact the side-chain carboxylic acid of glutamate in mGluR are not conserved in T1R1, and mutations at the matching sites do not alter glutamate binding. However, these mutations eliminate the effect of IMP.In order to understand this behavior, the authors modeled the binding cleft in the closed state, with IMP and glutamate in place. Glutamate binds at the bottom of the cleft, with its side chain pointed outwards. This conformation puts several positively-charged residues from the two lobes of the VFT close together higher up in the cleft. The authors propose, in keeping with previous models of VFT behavior, that the binding of the glutamate lowers the energy barrier between the open and closed states of the domain, but that glutamate alone is not sufficient to hold the domain closed. Their model places IMP higher up in the cleft, where its negatively-charged phosphate interacts with the positive residues. Thus, IMP stabilizes the closed conformation of the VFT domain.Some more work here would be welcome, particularly in the form of experimental crystal structures of the T1R1 VFT that can confirm the homology model. The VFT is rather large, but using a perdeuterated sample in a high-field magnet it might be possible to confirm the population-shift mechanism using NMR experiments. Lower-resolution techniques such as FRET may also be able to catch this stabilization behavior. If the model proves to be accurate, it would serve as an interesting example of positive allostery from a population shift.Although these experiments only concerned the umami taste receptor, this allosteric mechanism may be a more general feature of certain GPCRs. The authors indicate that they have unpublished data showing similar behavior in the sweet receptor, and it may be possible to design an allosteric stabilizer for any GPCR with a VFT domain. Because the related mGluR receptors are involved in many neurological and psychological diseases, successful design of such activators may have some therapeutic value.F. Zhang, B. Klebansky, R. M. Fine, H. Xu, A. Pronin, H. Liu, C. Tachdjian, X. Li (2008). Molecular mechanism for the umami taste synergism Proceedings of the National Academy of Sciences, 105 (52), 20930-20934 DOI: 10.1073/pnas.0810174106 OPEN ACCESS... Read more »

F. Zhang, B. Klebansky, R. M. Fine, H. Xu, A. Pronin, H. Liu, C. Tachdjian, & X. Li. (2008) Molecular mechanism for the umami taste synergism. Proceedings of the National Academy of Sciences, 105(52), 20930-20934. DOI: 10.1073/pnas.0810174106  

  • February 26, 2009
  • 09:00 PM
  • 1,258 views

A point mutation remodels a binding interface

by Michael Clarkson in Conformational Flux

Decades of studies involving extensive mutagenesis of proteins and protein domains have impressed on us the idea that the folded tertiary structures of proteins are fairly resilient. While a particular mutation may abolish function by directly ablating a key chemical group, it is rare for a single mutation, or even a group of several mutations, to significantly change the overall conformation of a folded polypeptide chain. When a major change does result, it often takes the form of complete denaturation. Because of this, it may seem that protein folds occupy stable islands in sequence space, surrounded by a sea of sequences that form random coils or molten globules. However, there is some evidence that this view is mistaken, that substantially divergent structures may have very similar sequences. A paper recently published in PNAS adds to this view by describing a major change in the structure of a PAS domain resulting from 1-3 mutations.PAS is a large family of protein-protein interaction domains contained in many signaling proteins. Although many of them have cofactors that modulate their binding, some PAS domains are constitutively active, which is the case for the domain under study here, the PAS-B domain from one of the founding members of the family, the aryl hydrocarbon receptor nuclear transporter (ARNT). The PAS-B domain was believed to dimerize with PAS domains from other proteins through one side of its β-sheet, and as a consequence Evans et al. decided to make several mutations on the outer surface of the sheet and monitor their effects on dimer formation.One of these mutations, Y456T, had a strange effect on the domain's NMR spectrum: about 30 new peaks showed up in the 1H-15N HSQC. Because this spectrum should show a single peak for each chemically unique proton-nitrogen pair, this result suggests that the pure proteins in the magnet exist in two distinct conformations. By lowering the temperature and repurifying the protein, Evans et al. were able to mostly separate these two conformations from each other. However, over time these conformationally purified samples became heterogeneous again, which means that the conformations can freely interconvert. This process was very slow, however — too slow to be detected using NMR relaxation techniques. From monitoring the HSQCs the authors concluded that the time constant for interconversion in the mutant is on the order of 16 hours.Intrigued by what they were seeing, Evans et al. made additional mutations to ARNT PAS-B and found that the proportion of protein in each structure can be adjusted within a wide range by mutation. Using a triple-mutant system they were able to drive about 99% of the proteins into the new conformation. Using this mutant the authors were able to assign the resonances in the HSQC spectrum and solve the structure using NOEs. They learned that the chemical shift changes in the mutant are quite widespread, as you can see in the figure I have shamelessly stolen (left) for your benefit. In this figure the chemical shift changes are mapped onto their structure of the new conformation using color, ranging from green (very little or no change) to red (significant changes) — the sites of the three mutations are shown. As you can see, the chemical shift effect is widespread, covering almost the whole β-sheet of the protein and reaching to the helix on the opposite side.Closer analysis of the structure shows why this is so. The strand of the β-sheet on which Y456 is situated has shifted its register by 3 spots. This has two effects. The first is that all of the hydrogen bonds involving that strand must be broken, at a substantial energetic cost. This is probably the reason the interconversion process is so slow. Moreover, because the register shifts by an odd number of residues, the strand must flip over, exposing to solvent the residues that were buried in the original structure, while burying the residues that were previously solvent-exposed. Although the backbone and side chain orientations in the strand overlay reasonably well between the two structures, the chemical groups available for interactions are completely different. Unsurprisingly, this alternate structure has very low affinity for its natural targets — titration experiments showed that the alternate conformation bound to its partner from hypoxia inducible factor at least 100x worse than the native structure.Of course, in living cells with a wide variety of surfaces to bind to, the mutant PAS-B might find an alternative partner for which it has high affinity. Studies that attempt to understand protein-protein interfaces from an engineering or evolutionary perspective typically adopt the assumption that point mutations have little effect beyond adding a particular functional group here or there. This study indicates that this attitude underestimates the ability of point mutations to radically remodel interface surfaces. While a Y→T mutation may not seem particularly conservative, a Y→S mutation has similar effects and requires only a single nucleotide base change. It is not inconceivable that this alternate conformation could be reached in vivo, potentially giving rise to completely novel protein-protein interactions.One might well wonder how common rearrangements of this kind are likely to be. As the authors point out, structural plasticity in the β-sheet is likely to be a common feature of PAS domains, making it difficult to assess whether this kind of mutational effect is widespread in other folds. However, the authors cite several examples of β-strand register shifts in other proteins. In addition, our decades of alanine-scanning mutagenesis have little to tell us about how common these kinds of rearrangements are, for two main reasons. First, the structural effects strongly depend on what a given residue is mutated to (see Table 1); had Evans et al. been content to leave things at alanine mutations they would never have detected this effect. Second, widely-applicable techniques for sensitively detecting small populations of alternate conformations have not been available until recently.While the conformational transition induced by the Y456T mutation preserves the protein's overall fold and stability, it rearranges the hydrogen bonding contacts of the main β-sheet and shortens a loop. Obviously this is not as dramatic a change as found in lymphotactin. However, this alternate structure has significant consequences for PAS-B function. Unexpectedly, this single point mutation can radically remodel the PAS-B binding surface. Moreover, this result adds to the evidence that new structures (even in the context of known folds) may be accessed with only a few changes in amino acid sequence, without any need to detour through molten-globule intermediates.M. R. Evans, P. B. Card, K. H. Gardner (2009). ARNT PAS-B has a fragile native state structure with an alternative -sheet register nearby in sequence space Proceedings of the National Academy of Sciences, 106 (8), 2617-2622 DOI: 10.1073/pnas.0808270106... Read more »

M. R. Evans, P. B. Card, & K. H. Gardner. (2009) ARNT PAS-B has a fragile native state structure with an alternative  -sheet register nearby in sequence space. Proceedings of the National Academy of Sciences, 106(8), 2617-2622. DOI: 10.1073/pnas.0808270106  

  • January 25, 2008
  • 09:06 PM
  • 1,231 views

What do we learn from the Protein Ensemble Method?

by Michael Clarkson in Conformational Flux

Anonymous left a comment on my post on Bruschweiller's work, referencing a couple of papers by Amarda Shehu, Cecilia Clementi, and Lydia Kavraki, the cites for which you can find at the bottom of this post. The most fascinating thing about these papers is the remarkable fidelity with which their Protein Ensemble Method (PEM) reproduces NMR-derived order parameters, 3-bond J couplings, and residual dipolar couplings. The authors demonstrate excellent correlations for ubiquitin, eglin c, Fyn SH3, Fnf10, and CI-2, and while all of these are relatively small proteins this is still a major accompli... Read more »

A Shehu, L Kavraki, & C Clementi. (2006) On the Characterization of Protein Native State Ensembles. Biophysical Journal, 92(5), 1503-1511. DOI: 10.1529/biophysj.106.094409  

Amarda Shehu, Cecilia Clementi, & Lydia Kavraki. (2006) Modeling protein conformational ensembles: From missing loops to equilibrium fluctuations. Proteins: Structure, Function, and Bioinformatics, 65(1), 164-179. DOI: 10.1002/prot.21060  

  • February 12, 2009
  • 07:00 PM
  • 1,153 views

Allostery in the CBP KIX domain

by Michael Clarkson in Conformational Flux

Classically, allosteric and cooperative effects have been identified with large complexes of multiple protein subunits, in which the binding of a ligand to one subunit enhances ligand binding in a different subunit. While some features of the models developed to deal with these systems do not translate well to cases of allostery within a single protein or domain, many of their core ideas continue to illuminate these single-subunit systems. In an upcoming paper in the Journal of the American Chemical Society, a team of European researchers examine an allosteric effect based on population shifts in a transcriptional activator, comparing it to a famous model for explaining allostery in hemoglobin (1).The CREB binding protein (CBP) is a large molecular scaffold that brings pieces of the transcriptional machinery together in order to turn on a gene. Like many scaffold proteins it contains several protein-protein interaction domains linked together by large unfolded regions. One of these domains is KIX, a small bundle of helices that binds other proteins at two distinct sites. In one case, a protein called MLL binds to one site while a protein called c-Myb binds at the other. What is so interesting about this is that KIX is much more likely to bind c-Myb when it is already bound to MLL. Brüschweiler et al. used NMR techniques to try and understand how this happens.In order to pull this off they performed relaxation-dispersion experiments on the amide nitrogen, α-carbon, and some methyl carbon atoms of the KIX domain bound to a peptide derived from MLL. Many of the amino acids in the protein showed a significant contribution to R2 from exchange, suggesting a global conformational switch between two states. In order to cover their bases, the authors performed experiments to prove that this behavior was not related to the unfolding of the protein. Satisfied that the protein was stable, they used standard methods to calculate the rate of the conformational change, the population of the two states, and the chemical shift difference between them. They found that the minor state of the KIX-MLL complex is 7% of the total population of protein molecules. They also noticed that the chemical shift difference between the two states correlates very well with the chemical shift difference between the KIX-MLL complex and the KIX-MLL-c-Myb complex. Assuming that the conformation of KIX is the primary determinant of chemical shift in the bound state, this suggests that the dynamics are sensing a switch between a state that doesn't bind c-Myb and a state that does.In order to determine whether MLL binding gave rise to this conformational switching behavior, the authors measured relaxation dispersion in KIX at several different concentrations of MLL. Excluding residues highly sensitive (by chemical shift) to MLL binding, they found that the exchange contribution to relaxation increases as MLL is added. Although Brüschweiler et al. were unable to fit this small number of residues quantitatively, these results strongly suggest that the addition of MLL increases the population of the c-Myb binding state. Moreover, under conditions where KIX forms a saturated complex with MLL and a peptide from another protein (pKID), the chemical exchange contribution to relaxation vanishes, suggesting that the protein has been pushed completely to the binding-competent state.In order to identify the pathway by which the MLL binding site communicates to the c-Myb binding site, the authors examined the residues in KIX that had the largest chemical shift change associated with the chemical exchange behavior. As it happens, residues satisfying these criteria cluster in a region stretching from the MLL site to the c-Myb site, as you can see to the right (explore this structure at the PDB). Here, KIX is blue, the MLL peptide is red, and the c-Myb peptide is green. The side chains of the residues Brüschweiler et al. identify are shown as sticks inside the pink atomic surface. As you can see, these residues constitute a contiguous body stretching from one site to the other. Presumably, this set of residues provides a pathway for communication between the two sites. A trio of isoleucines at the core of this region (I 611, 660, and 657) are present in KIX domains from many different species (supporting information), suggesting that this communication pathway is evolutionarily conserved. Mutational studies centered on this trio of residues may teach us more about the mechanism of information flow in this domain.Although this allosteric pathway is known to work in reverse (binding of c-Myb enhances the binding of MLL), the authors were unable to detect any exchange contribution to R2 when only c-Myb or pKID was bound. While this may suggest that communication in the opposite direction uses a completely different mechanism, such that KIX has two unidirectional allosteric pathways, that's not a necessary conclusion from this result. Alteration of R2 due to conformational exchange is dependent on the populations of the two states, the difference in chemical shift between them, and the rate of the switch. Actually detecting a dispersion curve requires that all these parameters lie within a 'sweet spot' that allows observation. This doesn't always happen, even when a dynamic process is occurring with a μs-ms rate. Because the chemical shift changes that result from MLL binding appear to be quite large (2) the exchange process may be slow on the NMR timescale.One minor concern I have with the paper is that the experiments were carried out at a pH of 5.8, which is lower than the pH of cytosol (7.2). The only groups likely to change their charge over that range are histidines, but one of the key residues for this paper is H651 in the KIX domain. The experiments that established the allosteric effect of MLL on c-Myb binding (2) were performed at pH 7.0 so it is formally possible that the dynamics and allostery are a coincidence (although the chemical shift data argue against this). It would probably be worthwhile to perform HMQC experiments to clarify the protonation state of the histidine, or to repeat the binding experiments at a lower pH. The latter might be preferable; I assume that mildly acidic conditions are used for the NMR experiments because KIX has undesirable spectral characteristics nearer neutral pH. Additionally, it might be interesting to perform experiments that explore the effects MLL has on the kinetics of binding, seeing as this appears to be a dynamic process.Brüschweiler et al. identify their results with the Monod-Wyman-Changeux model of allostery. Although this model was formally developed for systems with multiple subunits, what the authors really wish to emphasize is the idea from the MWC model that proteins in solution exist in an equilibrium of high-affinity and low-affinity forms. The evidence from the relaxation-dispersion experiments indicates that a very small proportion of free KIX exists in a (unfavorable) conformation that's ready to bind c-Myb. The binding of MLL enhances KIX affinity for c-Myb by stabilizing this structure — the allosteric effect arises because MLL binding defrays the energetic cost of adopting this fold. This manifests as a shift in the population of KIX proteins towards the binding-competent state. This kind of binding cooperativity may play a significant role in CBP's transcriptional activation function.(1) Sven Brüschweiler, Paul Schanda, Karin Kloiber, Bernhard Brutscher, Georg Kontaxis, Robert Konrat, Martin Tollinger (2009). Direct Observation of the Dynamic Process Underlying Allosteric Signal Transmission Journal of the American Chemical Society DOI: 10.1021/ja809947w(2) N. K. Goto, T. Zor, M. Martinez-Yamout, H. J. Dyson, P. E. Wright (2002). Cooperativity in Transcription Factor Binding to the Coactivator CREB-binding Protein (CBP). Journal of Biological Chemistry, 277 (45), 43168-43174 DOI: 10.1074/jbc.M207660200... Read more »

Sven Brüschweiler, Paul Schanda, Karin Kloiber, Bernhard Brutscher, Georg Kontaxis, Robert Konrat, & Martin Tollinger. (2009) Direct Observation of the Dynamic Process Underlying Allosteric Signal Transmission. Journal of the American Chemical Society, 2147483647. DOI: 10.1021/ja809947w  

N. K. Goto, T. Zor, M. Martinez-Yamout, H. J. Dyson, & P. E. Wright. (2002) Cooperativity in Transcription Factor Binding to the Coactivator CREB-binding Protein (CBP). Journal of Biological Chemistry, 277(45), 43168-43174. DOI: 10.1074/jbc.M207660200  

  • August 22, 2008
  • 08:00 PM
  • 1,092 views

Guided by the (blue) light

by Michael Clarkson in Conformational Flux

The ability to sense and respond to magnetic fields is a fundamental aspect of behavior in many animals. While migratory birds famously use the earth's magnetic field to navigate during, magnetic field responses occur in all manner of animals, from eels to invertebrates. Even the lowly fruit fly, best known as a reminder that you really should have taken the garbage out two days ago, can react to magnetism. While various explanations have been put forward in different species, magnetosensitivity remains fairly mysterious. In this week's Nature, researchers from the University of Massachusetts Medical School show that the blue-light photoreceptor cryptochrome plays an essential role in allowing fruit flies to detect magnetic fields.Cryptochrome (or Cry) inherited the ability to receive blue light along with its photolyase domain, which is homologous to a prokaryotic, light-dependent DNA repair protein. Cry proteins, which are present in all animals, do not perform any DNA repair work, but instead play a role in regulating the circadian rhythm. While it is not clear in all cases whether Cry's ability to absorb blue light is biologically significant in clock regulation, it is known that fruit flies (Drosophila melanogaster) use Cry to synchronize their circadian clocks. Previous experiments had suggested that the ability of fruit flies to detect magnetic fields was somehow related to photoreception, and that short wavelengths (like those sensed by Cry) had different effects from longer ones.Gegear et al. devised a relatively simple experiment to test the importance of Cry in Drosophila magnetosensing. They placed a T-junction in a box, with a magnetic coil on one side and a non-magnetic coil on the other. They released flies into the junction, with (trained) or without (naive) performing an earlier run where the magnetic field was associated with a sucrose reward. They shined a light into the box and used filters to investigate the role of specific wavelengths.They discovered that several strains of Drosophila could be trained to go to the magnetic field, although the degree of preference and the nature of the naive response differed substantially between strains. Gegear et al. chose the strain that showed the greatest response in full-spectrum light (and displayed a tendency to avoid the magnetic field in the naive state) to perform the filter experiment. Cutting off all wavelengths of light shorter than 500 nm abolished both the naive and trained responses to the magnetic field in these flies, as did filtering out all wavelengths shorter than 420 nm. If only wavelengths shorter than 400 nm were cut off, some of the trained and naive response returned. Simply dimming the light was not enough to replicate the effect of filtering. These experiments indicate that magnetic sensitivity in these flies requires light in the blue to ultraviolet range.In order to prove that cryptochrome specifically is necessary for this magnetic sensitivity, Gegear et al. took advantage of our tremendous knowledge of fly genetic manipulation to create mutant flies that did not have a functional Cry gene. No matter what wavelengths of light were used in the T-junction experiment, these flies did not respond to the magnetic field. Crossing these Cry-null mutants with normal flies restored magnetosensitivity. The authors also performed experiments to show that the circadian rhythm was not itself essential to magnetic response in the flies.Because this is a genetic experiment, it cannot address the question of whether Cry is both the blue-light photoreceptor and the magnetosensor. Going just on what we have in this paper, it is also possible that Cry acts upstream of another magnetosensor protein or is part of its downstream signaling pathway. However, in light of research that shows the flavin photoreception in other cryptochromes induces the formation of magnetically-sensitive radicals, some of which I discussed last year, it certainly seems possible that Drosophila cryptochrome does the whole job itself. As I mentioned in the case of the previous article, though, there is not yet any understanding of a mechanism by which information about magnetic field could be transduced from Cry radicals into the nervous system.Dorosophila Cry differs from other plant and animal Cry proteins in significant ways, so it's unclear whether these results have any relevance for other organisms. However, the finding that Cry is essential to Drosophila magnetosensitivity suggests at least the possibility of parallel systems in migratory birds and other species that use magnetic fields.Robert J. Gegear, Amy Casselman, Scott Waddell, Steven M. Reppert (2008). Cryptochrome mediates light-dependent magnetosensitivity in Drosophila Nature, 454 (7207), 1014-1018 DOI: 10.1038/nature07183... Read more »

Robert J. Gegear, Amy Casselman, Scott Waddell, & Steven M. Reppert. (2008) Cryptochrome mediates light-dependent magnetosensitivity in Drosophila. Nature, 454(7207), 1014-1018. DOI: 10.1038/nature07183  

  • March 26, 2008
  • 12:01 AM
  • 1,080 views

Two folds for lymphotactin

by Michael Clarkson in Conformational Flux

While reports of my man-crush on Brian Volkman are in general much exaggerated, it is true that I adore one of the systems he studies, the bizarre chemokine lymphotactin. In case you couldn't guess from past posts here, I am endlessly fascinated by this protein, and so I was very happy to finally see his latest paper on the subject in today's feed-dump from PNAS. Previously published research out of Brian's group indicated that lymphotactin adopted two totally different structures under different solution conditions. The new paper provides high-resolution structures of the non-chemokine fold a... Read more »

R Tuinstra, F C Peterson, S Kutlesa, E S Elgin, M A Kron, & B F Volkman. (2008) Interconversion between two unrelated protein folds in the lymphotactin native state. Proceedings of the National Academy of Sciences. DOI: 10.1073/pnas.0709518105  

  • February 29, 2008
  • 05:03 PM
  • 1,040 views

Don't eat the white snow!

by Michael Clarkson in Conformational Flux

A bunch of really great stuff came out today, so much that I'm not sure I'll be able to get to all of it. We can start with the shortest article of interest, a paper in Science that's sure to interest mothers whose children stand around with their tongues out in a flurry. Brent Christner and colleagues have discovered that snow from pretty much anywhere contains bacteria (1). Well sure, you probably suspected that, but these bacteria didn't move up from the ground... they fell down from the sky.Crystals generally form more readily when they have a nucleation point. Protein crystallograph... Read more »

B Christner, C E Morris, C M Foreman, R Cai, & D C Sands. (2008) Ubiquity of Biological Ice Nucleators in Snowfall. Science, 319(5867), 1214-1214. DOI: 10.1126/science.1149757  

  • March 24, 2008
  • 10:02 PM
  • 1,035 views

Enzymes almost as good as Ma Nature used to make

by Michael Clarkson in Conformational Flux

Biological systems have the interesting property that most of the reactions enabling life processes are, when left to their own devices, exceedingly slow. To reach the timescales that we associate with "living", these reactions must be sped up, which requires the presence of enzymes. Because they significantly enhance reaction rates under conditions that can be encountered almost anywhere, the design of artificial enzymes is an active area of research. In two papers this month, David Baker's lab describes notable success in designing enzymes in silico to have specific activities with significa... Read more »

Daniela Röthlisberger, Olga Khersonsky, Andrew Wollacott, Lin Jiang, Jason DeChancie, Jamie Betker, Jasmine Gallaher, Eric Althoff, Alexandre Zanghellini, Orly Dym.... (2008) Kemp elimination catalysts by computational enzyme design. Nature. DOI: 10.1038/nature06879  

  • November 4, 2008
  • 09:00 PM
  • 1,005 views

Video games and violence: grasping at causality

by Michael Clarkson in Conformational Flux

The latest evidence in the debate over the effects of video game violence has arrived in the November edition of the journal Pediatrics. Japanese and American psychologists, including well-known media violence researchers Craig Anderson and Douglas Gentile, report that violent video games constitute a causal risk factor for physical aggression. Perhaps unsurprisingly, the gaming internets have already expressed their disagreement with these results via angry blog postings based on secondary reporting (calmer coverage can be found at Gamasutra). A more professional critique has also been offered, in the form of a post-publication peer review by Texas A&M International University Professor Christopher Ferguson. The paper tries to sell itself as a significant piece of new proof, which it is not. Anderson et al. have found an interesting, if weak, correlation that they cannot prove to be causal, due to the limitations of the methods employed.The study has two key advantages that, in principle, make it a unique addition to our knowledge about the effects of video game violence. Firstly, it attempts to correlate physical aggression (PA) in teens and kids with habitual exposure to video game violence (HVGV) 3-6 months earlier. While the use of a timecourse alone cannot prove causation, long-term correlations are thought to suggest a causal relationship more strongly than instantaneous correlations. Secondly, the study involves several age groups from two countries, the United States and Japan. Although more children play video games in Japan than in the US, the rate of violent crime in Japanese society is much lower than in the US. This has occasionally been held out as disproof of an HVGV-PA link, but all it really establishes is that other factors play a significant role. Therefore it would be interesting to determine whether cultural differences between the US and Japan alter the effect of HVGV on PA.Three sets of children (two in Japan, one in the US) filled out questionnaires querying their gaming habits and physical aggression levels. Some months later, these same children were surveyed again to see whether their physical aggression levels had changed. The authors found that HVGV levels at the first time point had a weak correlation (r= 0.28) with PA at the second time point. This effect varied significantly over the individual datasets and was strongest in the youngest age group. However, the r value did not exceed 0.5 for any of these datasets.In layman's terms, one could see these results as evidence that HVGV predicts between 8% and 16% of the level of physical aggression, depending on the age group and nationality. I caution my readers that this interpretation is an oversimplification that depends on certain assumptions about the data to have any validity. Because no statistics of the underlying matrices are provided I cannot substantiate those assumptions, so this should not be taken as a definitive description of the study's findings. Statistics (even averages) imply a model, and should not be trusted if it cannot be proved that the model is appropriate.These results are interesting and indicate that, although the magnitude of the effect may differ between societies, there is nonetheless a universal positive correlation between HVGV and subsequent physical aggression. Despite the elaborate discussion of youth violence in the paper, this does not directly indicate a linkage to criminal behavior. Moreover, this correlation is difficult to interpret due to the study's numerous flaws.There are good reasons to wonder whether the interpretation of the questionnaires produced a valid measure of HVGV at all, the assignment of violence level by genre being particularly suspect. A more significant problem may be that HVGV and PA were assessed by different means in every single group. Each group used different delays between surveys, and each involved differently-aged children. This doesn't necessarily mean that conclusions drawn by aggregating the three are wrong, and the authors contend that agreement across the varying methodologies indicates robustness. However, the differences in method and subjects multiply the potential sources of error considerably. Since the derived correlations are so weak, this is a significant concern. In addition, because the populations differ substantially in respects other than nationality, it is impossible to accurately assess the effect of culture on the relationship between HVGV and PA. Doubtless future longitudinal studies will apply more uniform methods.This brings me to another weakness of the study. Scientists will occasionally joke that the best possible set of correlational data is the one that contains only two points, the reason being that you are assured of being able to draw a perfect, straight line through all your data. In practice, however, we know that having limited numbers of data points makes our interpretations much more likely to be wrong. A "longitudinal" study involving two questionnaires given a couple of months apart hardly provides firm footing for a long-term correlation or a causal relationship. The authors acknowledge that the study is limited in this regard, but argue that the short wait would most likely depress correlations from their true value. Still, a longer timecourse with more measurement points would be highly desirable.The authors make no attempt to account for any confounding factors other than gender. They do not seem to have taken data on family situation, peer influence, parental involvement, or school performance, although all of these factors are known to correlate to greater or lesser degrees with both PA and video game habits. If we only wish to establish that there is a correlation between HVGV and PA that's not a huge problem. However, Anderson et al. clearly mean to establish video games as a causal factor for aggression. In the absence of controls for confounding factors, that is impossible.Curiously, the authors also do not seem to have measured HVGV at the later time point. One objection to existing research linking HVGV to real-world violence has been that the observed correlations exist because people predisposed to violence choose to enjoy violent media. Testing the hypothesis that PA at the initial timepoint predicts HVGV at the second timepoint seems like an obvious thing to do, if only to squelch this objection. This seems to me particularly worthwhile, because the predictive power of HVGV for later aggression appears to be less than the instantaneous correlation between HVGV and aggression, significantly so for the older group. In light of these facts, the choice not to assess HVGV at the later time seems extremely odd.Despite these flaws, this research is a step in the right direction. We need longitudinal studies, carefully controlled for confounding factors, over a range of ages and nationalities to parse out the true effects of video games on aggressive behavior in teens and adults. I do not find the present study terribly convincing, and I particularly dislike the more sensationalistic high points of its discussion section. Nonetheless, I hope that the authors will take criticisms like those of Dr. Ferguson into account as they design studies that will more rigorously investigate the causal relationship between HVGV and PA. Only a particularly obstinate person would deny that there is a correlation between the intake of violent media, including video games, and aggressive behavior. They may inspire aggressive behavior, or serve as an outlet for existing aggression; either way, the correlation ought not be ignored. However, video games are just one, and doubtless not the most important one, of a constellation of potential factors affecting child behavior. Without a genuine analysis of the complicated causal relationships among these it is impossible to provide good advice to parents, doctors, and psychologists. The present study does not fill that gap in our understanding; it is doomed by its single-minded focus on video games and failure to account for confounding factors. While it is of value to know that the correlation between violent video games and aggression transcends national and cultural boundaries, it would be of greater value to know whether excessive playing of violent video games is a cause of aggressive behavior, a result of pre-existing aggression, or both. That is a question this research does not adequately, much less conclusively, address.C. A. Anderson, A. Sakamoto, D. A. Gentile, N. Ihori, A. Shibuya, S. Yukawa, M. Naito, K. Kobayashi (2008). Longitudinal Effects of Violent Video Games on Aggression in Japan and the United States PEDIATRICS, 122 (5) DOI: 10.1542/peds.2008-1425... Read more »

C. A. Anderson, A. Sakamoto, D. A. Gentile, N. Ihori, A. Shibuya, S. Yukawa, M. Naito, & K. Kobayashi. (2008) Longitudinal Effects of Violent Video Games on Aggression in Japan and the United States. PEDIATRICS, 122(5). DOI: 10.1542/peds.2008-1425  

  • February 19, 2008
  • 10:09 AM
  • 996 views

What's that appendix for, anyway?

by Michael Clarkson in Conformational Flux

Well, it keeps coming up, doesn't it? Famous cdesign proponentsist Dembski brought it up again recently in his list of ID "predictions" (click for epic fail). While his point was nicely deconstructed by Afarensis, I think it's worth examining the paper that attributed a function to the appendix. Just what did Bollinger et al. say about its function? On what basis did they draw their conclusions? And, I suppose most exasperatingly, what does the paper mean for evolution? Is the appendix vestigial or not, and if not, does that vindicate ID, evolution, or both?The paper in question is an el... Read more »

R RANDALBOLLINGER, A BARBAS, E BUSH, S LIN, & W PARKER. (2007) Biofilms in the large bowel suggest an apparent function of the human vermiform appendix. Journal of Theoretical Biology, 249(4), 826-831. DOI: 10.1016/j.jtbi.2007.08.032  

  • June 21, 2008
  • 09:00 AM
  • 996 views

Structural dynamics of PDZ allostery

by Michael Clarkson in Conformational Flux

If Michele Vendruscolo were trying to get me to blog about one of his papers, he could hardly have assembled a more perfect lure than his upcoming paper in JACS. It brings together all sorts of things I've been talking about on this webpage: NMR dynamics, MD simulations, and dynamics-driven allostery (in the PDZ domain, no less). Previous investigations of this PDZ domain indicated the existence of a network of residues that had a dynamic response to ligand binding. Dhuselia et al. extend this work using molecular dynamics simulations constrained by the existing dynamics results. This leads them to discover not one, but two networks in the PDZ domain, with different properties.NMR experiments have enormous power to sensitively detect changes in dynamics resulting from a perturbation, but they are also quite limited. Because of the models we use, the parameters we can fit out of relaxation data only give us information about the magnitude and timescale of fluctuations. Chemical shift overlap and interference caused by nearby dipoles limit the number of probes. Moreover, because NMR can only measure an ensemble, it is practically impossible to extract anything other than the most general information about correlated motions. MD has answers to all of these problems, but as a general rule has done poorly at reproducing NMR data about side-chain motions, calling the validity of the conclusions into question. Vendruscolo has taken some interesting strides in this regard by employing the limited experimental dynamics data as a component of the energy function. By constraining the simulation to mimic the known dynamics, we can hopefully learn more about the sites to which we are blind, as well as what kinds of motions the experiment is sensing and how they are linked.In this instance, the authors make use of the PDZ domain previously studied by Ernesto Fuentes in Drew Lee's lab (there was also some hack working there at the time). Ernie's research followed on previous evolutionary studies indicating a network of communication in PDZ domains (local summary here), and Ernie found, by comparing the dynamics of the free and ligand-bound states, that changes in motions propagated away from the binding site to two distal surfaces. The pathways of communication compared pretty well with the evolutionary results. Dhulesia et al. aim to extend these results by determining which motions are correlated and identifying the mechanisms by which energy is transmitted. They accomplished this by running multiple parallel simulations of the free and ligand-bound states of the PDZ domain constrained by Ernie's dynamics results, as well as NOE and 3J data.They find that two regions of the protein have correlated motions internally and move in an anticorrelated fashion relative to each other (Figure 3A). One of these regions consists of part of the binding site and all of distal surface 2 (DS2), while the other includes the other half of the binding site and all of distal surface 1 (DS1). When the ligand binds, something interesting happens. The motions of DS2 become more tightly correlated to the motion of an area around V30. The tight correlation between the motions of DS1 and α2 (an element of the binding cleft) switch to a slight anticorrelation. When a ligand binds to a protein we expect a broad increase in rigidity of the complex so that the proper orientations of bonding pairs are maintained. For the most part, the simulations affirm this expectation, but not for all regions. For the binding site and DS2, the backbone mobility decreases, as expected, but the backbone mobility of DS1 increases (I am going off the text and Table 3 here, rather than Figure 3). The side chains have a similar response. This agrees with other studies indicating that the change in conformational entropy upon binding a ligand need not be homogeneous. What is more interesting is that these results imply that opposite coherent responses can be induced in a small domain by a single stimulus.Although (as far as I know) this PDZ domain has no allosteric behavior in vivo, one can imagine that the binding of a ligand at the cleft could alter the binding of other modules to this domain. The entropic penalty for binding to DS2 would be lower in this case, while the penalty for binding to DS1 would be higher. The opposed nature of the dynamic responses may be related to the broad regional anticorrelation of free-state motions; disruption of this mode (by linking the motion of β2 and α2) may shunt that energy into DS1.The authors also find, using a series of structural parameters, that a set of residues have clear structural changes. Some of them appear to be associated with coupled changes in rotameric states; the authors map out one pathway in Figure 5. Because it is a rotameric pathway, it should be possible to test whether it is essential to communication experimentally—mutation of the intermediary residues should abolish the linkage. The authors also carry out a network analysis to identify the most connected residues, a prediction that may also be testable by mutagenesis. These "structural network" residues overlap only slightly with the dynamic network, and indeed do not generally intersect with the evolutionary network either. In the absence of identified allosteric behaviors or clear energetic connectivities it's difficult to say what this disjunction means. However, the residues undergoing structural changes surround most of the residues undergoing dynamic changes. It is possible that these changes in structure provide the context that allows the changes in dynamics (or vice-versa); the two properties are inextricably linked.Although communication between the binding site and distal surfaces is proven in this PDZ domain, and appears to be a general feature of the fold, the absence of a known function for the propagation in this instance makes it tough to assess the quality of these results. However, the findings of Dhulesia et al. make it clear that this approach can produce testable predictions and explanations. Hopefully this approach will be employed in the near future to study PDZ domains known to possess allosteric properties.1. Dhulesia, A., Gsponer, J., Vendruscolo, M. (2008). Mapping of Two Networks of Residues That Exhibit Structural and Dynamical Changes upon Binding in a PDZ Domain Protein. Journal of the American Chemical Society DOI: 10.1021/ja0752080... Read more »

Anne Dhulesia, Joerg Gsponer, & Michele Vendruscolo. (2008) Mapping of Two Networks of Residues That Exhibit Structural and Dynamical Changes upon Binding in a PDZ Domain Protein. Journal of the American Chemical Society. DOI: 10.1021/ja0752080  

  • March 5, 2008
  • 10:02 PM
  • 980 views

Allostery without conformational change

by Michael Clarkson in Conformational Flux

Allostery is a strange-looking word for a relatively simple idea: regulation at a distance. Binding events at one location on a protein can influence binding events that are relatively far away. It is allostery—in the form of cooperative binding in hemoglobin—that makes our oxygen-delivery system work. Because it provides an alternative way to attack drug targets, allosteric regulation is an attractive possibility for new medicines; recent results suggest that allosteric inhibitors may have promise in the treatment of diseases related to hormone receptor activation. Yet, as interes... Read more »

C TSAI, A DELSOL, & R NUSSINOV. (2008) Allostery: Absence of a change in shape does not imply that allostery is not at play. Journal of Molecular Biology. DOI: 10.1016/j.jmb.2008.02.034  

A Cooper, & D Dryden. (1984) Allostery without conformational change. European Biophysics Journal, 11(2), 103-109. DOI: 10.1007/BF00276625  

  • April 30, 2009
  • 11:00 PM
  • 976 views

cAMP gives CAP a twist

by Michael Clarkson in Conformational Flux

The catabolite activator protein (CAP), which plays a significant role in telling bacterial metabolism to digest sugars other than glucose, is a classic example of allosteric activation. Binding of the small signaling molecule cyclic AMP (cAMP) switches CAP into an active state that recruits RNA polymerase to certain metabolic genes. The biochemistry of cAMP activation is well understood, but the structural basis is not as clear, because a structure of the inactive protein was not available. This week in PNAS, researchers from Rutgers University and the University of Wisconsin-Madison report a structure of the free state of CAP that illuminates this allosteric effect.Many excellent structural studies have examined CAP in its activated and DNA-bound form. CAP is a dimer, and each monomer has two domains: a DNA-binding domain (DBD) that recognizes its specific sequence, and a cAMP-binding domain (CBD). The monomers bind to each other through a coiled-coil interaction between two long helices. When CAP is activated it binds to DNA, with two helices (the recognition helices) sliding into the major groove and specifically identifying the sequences to which it should recruit the transcription apparatus. Without cAMP bound, CAP can still interact with DNA, but this interaction is of low affinity and not specific for any particular sequence. There are a number of ways this could conceivably happen, but it's difficult to be certain about any model in the absence of a structure of the free (apo-) protein.In order to determine the structure, Popovych et al. used NMR. The 50 kDa size of the dimer means that it requires some extra effort for NMR work, but it is still well within the capabilities of the technique. The fact that the protein is a symmetric homodimer makes assigning the spectra somewhat easier, as the researcher only needs to deal with 209 residues rather than 418. The authors determined the structure using short-range distance restraints from nOe experiments, long-range restraints from paramagnetic relaxation enhancement, and angular restraints from residual dipolar couplings (RDCs). These angular restraints allowed the authors to unambiguously determine the relative orientation of the DBD and CBD in each monomer.Getting that orientation right is key to the story here, as you can see from the image to the left. Here I'm showing you the DBD and coiled-coil helix (lower left) of a single monomer in the two different states. The activated CAP is in green (PDB code: 1G6N, and the apo- structure is in red (PDB code: 2WC2). You're looking down the coiled-coil, and the recognition helix is in a brighter color right at the front. If you superpose these structures on the bottom end of the coiled-coil, you can see that the recognition helix is rotated by 60° when cAMP binds. This twist of the DNA binding domain gives the recognition helices the right orientation and spacing to slide into the major groove of DNA and identify genes to activate. In the apo- state, these helices cannot both fit into the major groove simultaneously, explaining the low affinity and lack of specificity in that state.Although the DBDs undergo a radical change in position following cAMP binding, they don't actually have any direct interactions with the signaling molecule, which binds down in the CBD near the coiled-coil helix. This helix, which links the CBD to the DBD, turns out to be key to communicating the allosteric signal. In the apo- state, the top part of this helix (near the DBD) is actually somewhat disordered and loop-like, not helical. Binding of cAMP to the CBD forms several contacts and causes several structural shifts that result in the formation of regular helical structure at the top of the coiled-coil. This in turn swings the DBDs around so that the recognition helices are in position to interact with target sequences (the authors provide a short movie of this in the Supplementary Information). A similar molecule, cGMP, that does not activate CAP, fails to make the key contacts with T127 and S128 that mediate this structural change.The fact that the upper part of the coiled-coil is unstructured suggests that CAP may sample a range of conformations in the apo- state. This possibility is supported by one of the mutational studies in the paper. As you can see from Figure 5, a G141S mutation and binding of various effectors to the mutant causes the NMR resonances of DBD residues to shift on a line between the WT apo- and WT cAMP-bound states. This, in conjunction with the broadening of those intermediate peaks, suggests that the DBDs are exchanging between the two states on a timescale of microseconds. It seems quite likely that one or both DBDs in the inactive dimer occasionally samples the active conformation. In this model, the function of cAMP would be to stabilize, rather than enable the active conformation. The negative cooperativity of cAMP binding may help keep CAP switched "off" in the face of this conformational heterogeneity.This study only dealt with a single protein, but the results are likely to be applicable to a number of systems. The allosteric mechanism described here seems to fit observations in at least some other members of the protein family to which CAP belongs. As such, this structural work and the dynamics investigations that will probably ensue are likely to provide important insights into a number of regulatory pathways in bacteria.Popovych, N., Tzeng, S., Tonelli, M., Ebright, R., & Kalodimos, C. (2009). Structural basis for cAMP-mediated allosteric control of the catabolite activator protein Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.0900595106... Read more »

Popovych, N., Tzeng, S., Tonelli, M., Ebright, R., & Kalodimos, C. (2009) Structural basis for cAMP-mediated allosteric control of the catabolite activator protein. Proceedings of the National Academy of Sciences. DOI: 10.1073/pnas.0900595106  

  • April 18, 2008
  • 06:02 PM
  • 975 views

Rapid evolution of lizards in the Adriatic

by Michael Clarkson in Conformational Flux

Enough about Ben Stein and his lies about evolution. Let's talk some truth about evolution, namely scientific truth. The fine folks at Zooillogix brought my attention to a paper that flew under my radar at a time I may (perhaps) have been more focused on basketball. In it, researchers from Harvard and Amherst studied a population of lizards on a very small islet in the Mediterranean. In less than 40 years, this population of lizards has evolved to have significantly different morphology from its parent population, a new set of endosymbionts, and novel anatomical features rarely in related liza... Read more »

A Herrel, K Huyghe, B Vanhooydonck, T Backeljau, K Breugelmans, I Grbac, R Van Damme, & D Irschick. (2008) Rapid large-scale evolutionary divergence in morphology and performance associated with exploitation of a different dietary resource. Proceedings of the National Academy of Sciences, 105(12), 4792-4795. DOI: 10.1073/pnas.0711998105  

  • April 13, 2009
  • 10:00 PM
  • 973 views

Drugs disrupt DHFR dynamics

by Michael Clarkson in Conformational Flux

One of the most-studied cases of the relationship between dynamics and catalysis is the bacterial dihydrofolate reductase (DHFR). DHFR catalyzes the reduction of dihydrofolate to tetrahydrofolate while oxidizing the cofactor nicotinamide adenine dinucleotide phosphate (NADPH). As part of this catalytic process, a region of the protein called the "Met 20 loop" switches from a "closed" state that shields the active site from solvent to an "occluded" state that separates the substrate from the cofactor. NMR studies of DHFR structural dynamics have correlated the protein motions with the chemical changes. In a recent study appearing in Structure, researchers from the University of North Carolina show that the binding of inhibitors such as methotrexate (MTX) and trimethoprim (TMP) appears to uniquely disrupt the dynamic networks of DHFR.Previously, seminal work from the lab of Peter Wright surveyed the dynamics of DHFR in every step of its reaction pathway. Boehr et al. determined that structural fluctuations in each complex represented motions towards the next step in the reaction. The conformational exchange rates they obtained from their relaxation-dispersion experiments closely resembled the rate constants that had been independently determined for the chemical steps. In almost every complex the conformational exchange was widespread, affecting residues in both the substrate and cofactor binding sites, as well as important distal locations such as the Met 20 loop.Because the existing work from the Wright lab hewed as close to the natural substrates and products as possible, Mauldin et al. chose to examine the dynamic effects of inhibitor binding to DHFR. Like Wright's group, they used relaxation-dispersion experiments to identify conformational changes taking place on the μs-ms timescale. In the NADPH:DHFR complex the motions are widespread, encompassing the substrate binding site, the Met 20 loop, and distal locations. Binding of either inhibitor eliminates about half of this dynamic network and dramatically reduces the fluctuation rates of those residues for which conformational exchange continues to occur.Based on their fits of the exchange rates, Mauldin et al. conclude that the substrate binding pocket moves in a way that mimics the enzyme's normal motions in the transition from its closed state to its occluded state. The long-range conformational changes that actually complete this transition, however, have been completely quenched. With the inhibitors bound, DHFR is like a car that's turning over but won't start. Part of the enzyme is still moving in exactly the right way to proceed along the reaction coordinate, but for some reason this motion doesn't catch on throughout the protein.In order to gain a more complete understanding of the dynamic effects, Mauldin et al. performed experiments to identify the motion of the protein on the ps-ns timescale. Analyzing the dynamics of methyl and amide resonances using the Lipari-Szabo model-free formalism, the authors realized that inhibitor binding did cause long-range changes in dynamics, just in a faster regime. Where the natural substrate complexes have motions that occur hundreds or thousands of times per second, the inhibitor-bound forms have (smaller) motions that occur millions of times per second. Because these altered motions encompass the Met 20 loop and surrounding residues, the authors argue that they reflect abortive attempts by the protein to transition into the occluded state.Although these inhibitors do not appear to change the protein's overall conformation, they produce long-range dynamic effects on short timescales and quench distal motions on intermediate timescales. The binding pocket appears to still be experiencing fluctuations related to the transition between the closed and occluded conformational states, but the mechanism that couples the binding site dynamics to the motion of the loop that defines these two states appears to be broken.The million-dollar question is this: do drugs alter DHFR dynamics because they inhibit the chemistry, or do these drugs inhibit the chemistry because they alter DHFR dynamics? Quenching dynamics costs energy in the form of conformational entropy, and it may be possible to tune a drug for improved efficiency by blocking the binding site without altering the dynamics. This is only true, however, if the dynamics don't matter to successful inhibition. On the other hand, if blocking the conformational switching of the Met 20 loop inhibits the enzyme, then drugs can be designed for that angle of attack as well. In the case of a protein like DHFR, where the bacterial enzyme has similar activity but a very different structure from its human equivalent, drugs that target regions other than the active site may significantly reduce side-effects. As a result, protein targets that were previously off-limits due to shared chemistry may become tractable due to divergent dynamics and structure.Mauldin, R., Carroll, M., & Lee, A. (2009). Dynamic Dysfunction in Dihydrofolate Reductase Results from Antifolate Drug Binding: Modulation of Dynamics within a Structural State Structure, 17 (3), 386-394 DOI: 10.1016/j.str.2009.01.005Boehr, D., McElheny, D., Dyson, H., & Wright, P. (2006). The Dynamic Energy Landscape of Dihydrofolate Reductase Catalysis Science, 313 (5793), 1638-1642 DOI: 10.1126/science.1130258... Read more »

Mauldin, R., Carroll, M., & Lee, A. (2009) Dynamic Dysfunction in Dihydrofolate Reductase Results from Antifolate Drug Binding: Modulation of Dynamics within a Structural State. Structure, 17(3), 386-394. DOI: 10.1016/j.str.2009.01.005  

  • March 10, 2008
  • 10:03 PM
  • 942 views

Protein Structure from Chemical Shifts Alone

by Michael Clarkson in Conformational Flux

Unless you have extremely good luck or a lot of supporting information, deriving a protein structure from NMR data is an enormous pain in the ass. First, you have to assign the resonances of the protein—that is, you must determine the chemical shifts of most or all of the protons in the protein, which in turn entails figuring out the chemical shifts of most of the carbon and nitrogen atoms as well. Then you have to acquire nuclear Overhauser effect (NOE) and/or residual dipolar coupling (RDC) data to figure out how far the atoms are from each other and how some of the bonds are oriented.... Read more »

Y Shen, O Lange, F Delaglio, P Rossi, J Aramini, G Liu, A Eletsky, Y Wu, K Singarapu, A Lemak.... (2008) Consistent blind protein structure generation from NMR chemical shift data. Proceedings of the National Academy of Sciences. DOI: 10.1073/pnas.0800256105  

A Cavalli, X Salvatella, C Dobson, & M Vendruscolo. (2007) Protein structure determination from NMR chemical shifts. Proceedings of the National Academy of Sciences, 104(23), 9615-9620. DOI: 10.1073/pnas.0610313104  

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