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Conformational Flux
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by Michael Clarkson in Conformational Flux
Fluorescent sensors, be they proteins or small molecules, are extremely useful because they can be used to detect metabolic states and protein interactions in living cells. Fluorescent proteins are particularly useful because they can be produced inside the cell and, using tags, targeted to specific proteins, locations and organelles quite easily. Because of this, a [...]... Read more »
Kao, Y., Zhu, X., & Min, W. (2012) Protein-flexibility mediated coupling between photoswitching kinetics and surrounding viscosity of a photochromic fluorescent protein. Proceedings of the National Academy of Sciences, 109(9), 3220-3225. DOI: 10.1073/pnas.1115311109
by Michael Clarkson in Conformational Flux
In previous posts on this blog I’ve discussed efforts to perform NMR inside of living cells. These experiments, performed in bacteria, are primarily intended to establish whether dilute-solution experiments veridically reproduce biomolecular structures as they appear in live organisms. Now it seems that crystallography is starting to get in on the act. This week in [...]... Read more »
Koopmann, R., Cupelli, K., Redecke, L., Nass, K., DePonte, D., White, T., Stellato, F., Rehders, D., Liang, M., Andreasson, J.... (2012) In vivo protein crystallization opens new routes in structural biology. Nature Methods. DOI: 10.1038/nmeth.1859
by Michael Clarkson in Conformational Flux
Imagine that you could get an injection of a protein that would chop up arterial plaques. Imagine that you could drop a plastic bottle into a pool of bacteria that would transform it back into high-grade oil. Imagine that you could take any organic material at all and, with a minimum of planning, transform it [...]... Read more »
Eiben, C., Siegel, J., Bale, J., Cooper, S., Khatib, F., Shen, B., Players, F., Stoddard, B., Popovic, Z., & Baker, D. (2012) Increased Diels-Alderase activity through backbone remodeling guided by Foldit players. Nature Biotechnology. DOI: 10.1038/nbt.2109
by Michael Clarkson in Conformational Flux
While crystallography and NMR are useful for defining the structural characteristics of proteins, cryo-electron microscopy (cryo-EM) may be the most useful technique for investigating the structure of large biomolecular assemblies. Rapid advances in the technique have brought it to the point where it can deliver atomic-resolution models, without the need for crystallization or any relevant [...]... Read more »
Wu, W., Thomas, J., Cheng, N., Black, L., & Steven, A. (2012) Bubblegrams Reveal the Inner Body of Bacteriophage . Science, 335(6065), 182-182. DOI: 10.1126/science.1214120
by Michael Clarkson in Conformational Flux
One of the most serious challenges facing medical science today is the development of drug resistance by bacteria and viruses. Almost as quickly as we can develop drugs that attack the machinery of infectious disease, evolution, aided in some cases by careless use, defeats our efforts. In some cases this is because the specific target [...]... Read more »
Morrison, E., DeKoster, G., Dutta, S., Vafabakhsh, R., Clarkson, M.W., Bahl, A., Kern, D., Ha, T., & Henzler-Wildman, K. (2011) Antiparallel EmrE exports drugs by exchanging between asymmetric structures. Nature, 481(7379), 45-50. DOI: 10.1038/nature10703
by Michael Clarkson in Conformational Flux
One of the goals of computational biology is to predict the complete high-order structure of a protein from its amino acid sequence. Often reasonably good structures can be produced by modeling a new protein according to an already-known structure of a homologous protein, one with a similar sequence and presumably a similar structure. However, these [...]... Read more »
Khatib, F., DiMaio, F., Cooper, S., Kazmierczyk, M., Gilski, M., Krzywda, S., Zabranska, H., Pichova, I., Thompson, J., Popović, Z.... (2011) Crystal structure of a monomeric retroviral protease solved by protein folding game players. Nature Structural . DOI: 10.1038/nsmb.2119
by Michael Clarkson in Conformational Flux
Given that videogames are often demonized by research (and “research”) blaming them for everything from rudeness to the epidemic of youth violence, gamers often take a great deal of cheer from research attaching positive outcomes to videogame play. One such article that recently attracted some attention was work suggesting that playing videogames could correct amblyopia [...]... Read more »
Li, R., Ngo, C., Nguyen, J., & Levi, D. (2011) Video-Game Play Induces Plasticity in the Visual System of Adults with Amblyopia. PLoS Biology, 9(8). DOI: 10.1371/journal.pbio.1001135
by Michael Clarkson in Conformational Flux
Over the last two decades, multiple kinds of NMR experiments have repeatedly shown that protein structures are quite variable, frequently shifting to minor conformations. The most striking evidence in this line has come from hydrogen-exchange experiments, which have demonstrated that virtually all proteins undergo excursions to partially-folded states at equilibrium. As R2 relaxation-dispersion experiments have [...]... Read more »
Bouvignies, G., Vallurupalli, P., Hansen, D., Correia, B., Lange, O., Bah, A., Vernon, R., Dahlquist, F., Baker, D., & Kay, L. (2011) Solution structure of a minor and transiently formed state of a T4 lysozyme mutant. Nature, 477(7362), 111-114. DOI: 10.1038/nature10349
Mulder FA, Mittermaier A, Hon B, Dahlquist FW, & Kay LE. (2001) Studying excited states of proteins by NMR spectroscopy. Nature structural biology, 8(11), 932-5. PMID: 11685237
by Michael Clarkson in Conformational Flux
As I have mentioned before on this blog, the use of tools like CS-ROSETTA holds the promise of determining protein structures using only the chemical shifts of its backbone atoms. In addition to potentially making NOEs and RDCs redundant, this technology allows biologists to determine the conformations of minor members of the structural ensemble, which are very difficult to obtain using conventional approaches in population-dominated techniques like NMR and X-ray crystallography. There are two limitations here, however. First, we only gain insight into the backbone, and as we know, the positions of side chains in minor states can be critical for function. In addition, backbone chemical shifts are not always available due to relaxation problems. Both weaknesses could, in principle, be addressed by extracting conformational information from the chemical shifts of methyl groups, which report on side-chain behavior and continue to give good signal even in very large proteins. This is the rationale behind a series of recent papers from the Kay lab [1-3] intended to determine changes in side-chain rotameric state from methyl relaxation-dispersion data.
The roots of this idea have been around for a while, dating back at least to a 1996 paper in J. Biomol. NMR [4]. I've reproduced one of MacKenzie et al.'s figures at right, and as you can see, for this protein (a peptide of glycophorin A), the correlation between the Cδ chemical shift and JCδCα is quite striking. However, the quality of the correlation appeared to be protein-dependent, as the R2 for this relationship was significantly lower for staphylococcal nuclease side-chains, possibly because they were positioned in a less homogeneous chemical environment than a lipid bilayer.
A more systematic study was recently performed by Bob London and co-workers from the National Institute of Environmental Health Sciences [5]. They extensively compared side-chain rotameric angles extracted from the PDB to side-chain chemical shift data from the Biological Magnetic Resonance data Bank to see what correlations emerged. They expected to see that the chemical shifts of the carbons depended on the side-chain dihedral angles due to the "γ-substituent effect", which is believed to alter chemical shifts due to bond polarization caused by steric interactions. Although there are some complications due to other effects, this prediction turned out to be true, broadly speaking.
The left Thr has χ1=-60° while the right one has
χ1=60°. The rotation around the Cα-Cβ bond from
N to Oγ defines the dihedral angle.
London et al. found clear correlations between chemical shift and rotameric state for threonine, for instance, which has a true chiral center at Cβ. For χ1 of ± 60° (these angles are also referred to as gauche±), the chemical shift of the methyl carbon was around 22 ppm, while for χ1 of 180° (also called trans) the chemical shifts cluster loosely around 19 ppm. More broadly, London et al. observed that sterically crowded rotamers tended to move aliphatic carbon chemical shifts upfield. Structurally, the difference between these dihedral angles is that in the ±60° positions, Cγ2 has steric interactions with only one heavy atom (i.e. the amide N or carbonyl C), while in the 180° position it interacts with two.
As one might expect given the results of Mackenzie et al., London et al. also found a straightforward relationship in the case of the leucine δ carbons, where the population of rotamers could be determined rather simply using the difference between the δ1 and δ2 chemical shifts. While this only specifically gives the population of the trans rotamer (where Cδ1 is on the opposite side of the Cβ—Cγ bond from Cα), it turns out that, due to unfavorable sterics, population of the gauche- conformation is vanishingly small in the PDB, so that one can assert with some confidence that everything not in trans is in gauche+. Also, London et al. noted that the χ1 and χ2 angles were highly correlated for leucines, so that in principle the entire side-chain conformation could be defined using just the difference in Cδ chemical shifts.
Hansen et al. [1] decided to use the chemical shift-rotamer relationship to analyze the minor conformations of leucines in mutants of the Fyn SH3 domain. The G48M mutant is in a rapid equilibrium between folded and unfolded forms, while the A39V/N53P/V55L triple mutant appears to primarily exchange to an intermediate state. Using a combination of CPMG-based relaxation-dispersion experiements and HSQC/HMQC, the Kay lab were able to determine the chemical shifts of the leucine methyls in the alternate state for each mutant, and thus derive populations for the trans rotamer. In the unfolded state, on expects to see ~60-70% population of the trans rotamer. The folded state of Fyn SH3 has several leucines that lie outside this range, but in the minor form of G48M nearly all of them lie within it, consistent with the existing finding that this state is unfolded. In the case of the triple mutant, some leucines move into the unfolded range in the minor state, while others remain outside of it. This is consistent with the assignment of the minor state as a partially-folded intermediate.
In a subsequent paper, Hansen et al. derived a relatively simple method for estimating the population of the gauche- rotamer state for the isoleucine δ carbon and applied it to the same system [2]. The situation for the Ile Cδ is somewhat more complicated than that of leucine. Because it is an isolated methyl group, and the rest of the side chain has a complicated topology, as many as four unique rotamer positions are distinctly populated in the PDB. However, in solution only the trans and gauche- configurations are expected to be significantly populated.
The Fyn SH3 domain has two Ile residues, which by this technique appear to be populated primarily in the gauche- rotamer (I28) and the trans rotamer (I50) respectively. In the intermediate state (results from the unfolded state are not reported) both isoleucines populate the gauche- rotamer to about 20%. The authors interpret this as a non-native interaction in the case of I28 and a slight increase in dynamics in the case of I50. However, it seems that these values could also support a case that both side chains are totally (or almost totally) solvent-exposed in the intermediate state, and thus adopting random-coil configurations.
One might also take issue with the idea that an increase from 0 to 20% of an alternate rotamer population represents a "slight" increase in dynamics. It's difficult to make any firm statement in this regard because we don't actually know the rotamer distribution in the folded state: Cδ1 may be entirely in trans, or averaged somehow between all of the non-gauche states. The authors take the folded state to be essentially pure trans, from which one would plausibly expect to observe an order parameter of 0.8 or higher for the methyl group (according to the rough calculations in [6], see reproduced figure on left). Based on the population, the order parameter would decrease to around 0.5 in the intermediate, a fairly large change.
However, this does not undermine the conclusion that the core is relatively well-formed in the intermediate. One perplexing feature of methyl side-chain order parameters is that they correlate poorly with nearly every structural feature one might expect to explain them [7]. Solvent-accessible surface area, packing density, and depth of burial are all rather poor predictors of side-chain dynamics. By the s... Read more »
Hansen, D., Neudecker, P., Vallurupalli, P., Mulder, F., & Kay, L. (2010) Determination of Leu Side-Chain Conformations in Excited Protein States by NMR Relaxation Dispersion. Journal of the American Chemical Society, 132(1), 42-43. DOI: 10.1021/ja909294n
Hansen, D.F., Neudecker, P., & Kay, L.E. (2010) Determination of isoleucine side-chain conformations in ground and excited states of proteins from chemical shifts. Journal of the American Chemical Society, 7589-7591. DOI: 10.1021/ja102090z
Hansen, D.F., & Kay, L.E. (2011) Determining valine side-chain rotamer conformations in proteins from methyl 13C chemical shifts: application to the 360 kDa half-proteasome. Journal of the American Chemical Society, 133(21), 8272-8281. DOI: 10.1021/ja2014532
by Michael Clarkson in Conformational Flux
The classic neuropathological hallmarks of Alzheimer's disease are the appearance of amyloid plaques composed primarily of amyloid beta (Aβ) peptides, and neurofibrillary tangles composed mainly of hyperphosphorylated tau protein. For many years, research into treatments for Alzheimer's disease proceeded on the hypothesis that the plaques were toxic to the surrounding neurons. More recently, however, evidence has shown that soluble Aβ oligomers may be the primary toxic species. A recent paper in Proceedings of the National Academy of Sciences supports this hypothesis by showing that Aβ oligomers isolated from the brains of Alzheimer's sufferers cause neuronal degradation and improper phosphorylation of tau (1). This paper is open access, so open it up and read along.
Jin et al. isolated dimers of Aβ from homogenates of human brains from Alzheimer's patients. Dimers were separated from monomers and higher-order oligomers by size-exclusion chromatography in the presence of a strong detergent that typically breaks up folded proteins and repeating aggregates. This separates the dimers and higher oligomers from each other, and also dissociated weakly-interacting peptides (due to the effects of the detergent). As you can see from Fig. 1A, this produced fractions that contained either detergent-stable Aβ dimers (AD-TBS) or normal cortical proteins (cont-TBS) in identical solution conditions. They also created synthetic dimers by mutating Aβ to contain a cysteine that could form a covalent linkage between peptides (Aβ40S26C). They then used these various materials to treat primary cultures of neurons (that is, neurons that were obtained by directly harvesting them from an animal), with the dimers reaching a final concentration 0.5 nM in the growth medium.
Fig 1B establishes that, among the materials studied here, Aβ dimers are uniquely responsible for the appearance of tau "beads" along the neurites of the cultured cells after 3 days (the widespread dots in the final column of images). This effect is quantified in 1C, which shows that the dimer-containing fractions produced a dramatic increase in this clumping. According to the authors, these easily-visible clumps are only one symptom of widespread problems with the cells' cytoskeletons. This sort of cytoskeletal trouble is expected because tau's function is to stabilize and assist in the formation of microtubules from tubulin. The upshot of this figure is that continuous exposure to Aβ dimers (Fig 1D establishes that the dimers persist through the treatment period) appears to cause some sort of trouble with tau, which may reflect the incipient formation of the famous tangles.
The natural follow-up question is whether tau is necessary for this cytoskeletal derangement. The fact that the cultured neurons must mature, with a correlated increase in tau expression, for Aβ dimers to have an effect suggests that it must be. To check this, the authors used RNA inhibition to knock down tau levels. Fig 2A demonstrates that tau, but not tubulin, expression was altered using the tau-specific RNAi (but not the scrambled cont-RNAi). The cytoskeletal damage caused by both the natural dimer and the Aβ40S26C synthetic dimer were suppressed by tau-RNAi (Fig. 2B). At least at this timescale, it therefore appears that normal tau expression levels are necessary for this toxic effect of Aβ dimers. However, as tau in neurofibrillary tangles never breaks down, it seems like a longer exposure to Aβ under these conditions should produce similar toxic effects eventually.
The complementary experiment, is shown in Fig. 3, using a hybrid construct where human tau was fused to a fluorescent protein. As you can see from these images, under control conditions (columns labeled EGFP), cells treated with Aβ monomers and dimers have only subtle differences after two days, and beading is only evident after three days of treatment. When tau is overexpressed (columns labeled tau-EYFP), the cytoskeletal issues are obvious a day earlier. The tau-EYFP appears to be distributed in the same places as normal tau (fourth row), so the EYFP tag probably isn't responsible for this effect, and the normal behavior of monomer-treated cells is reassuring. However, the EYFP tag may make tau more susceptible to some kind of dysregulation. Because this experiment both increases the total amount of tau and introduces the human protein, the reason for the enhanced susceptibility is difficult to determine. A control experiment in which rat tau-EYFP was expressed in the same construct would have been very helpful in clarifying this point.
As I mentioned above the formation of the tangles is associated with tau becoming highly phosphorylated. Jin et al. therefore made an effort to confirm that this was happening in their cultured cells, using antibodies that would recognize some specific sites in the tau protein that receive phosphate tags. Fig. 4 summarizes the results, indicating that human tau expressed in rat neurons becomes highly phosphorylated at serines 202, 205, and 262. For some reason, the endogenous rat tau did not become significantly phosphorylated at S262; this may have something to do with the apparently enhanced toxicity of Aβ dimers in the presence of human tau.
The paper's final figure tests whether antibodies directed against specific sites in Aβ can prevent the observed cytoskeletal degradation. They found that two antibodies that bound to the N-terminus of Aβ significantly suppressed the effect of the dimers over the three-day timespan (fourth and fifth columns of A). However, an antibody directed towards the C-terminus of Aβ42 did not have much effect. Fig. 5C suggests that this is because this antibody simply didn't bind to much of the Aβ in solution, either because most of the isoforms are shorter or because the C-terminus is protected in some way.
These results clearly link cytoskeletal disruptions caused by tau to the presence of soluble Aβ dimers, linking the two well-known pathological hallmarks of Alzheimer's disease. That soluble oligomers, rather than fibrils, were responsible for the effect does not necessarily prove that the plaques aren't important, for two reasons. The first is that, while these results clearly demonstrate dysregulation and aggregation of tau, true neurofibrillary tangles did not appear, and until we can assemble a full chain of events leading from beads to tangles the case, though strong, is still unproven. Secondly, as I've discussed previously, research has shown that the plaques can release soluble oligomers into the surrounding neural tissue and will therefore serve as reservoirs of toxic protein even if the fibrils themselves are completely inert.
That Aβ dimers can derange tau regulation in cultured neurons is not a new finding; similar results were reported last year using synthetic dimers (2). Zempel et al.'s experiments used Aβ concentrations up to 5 μM, but Jin et al. show that naturally-obtained dimers have toxic effects at much, much lower concentrations. As the Zempel et al. paper suggests (consistent with much previous work), dysregulation of calcium levels caused by Aβ oligomers may be how they cause these effects. It is not presently clear why natural oligomers should be four orders of magnitude more potent than the various kinds of synthetic dimers at causing the effect; an understanding of this difference may be crucial in developing a suite of effective treatments for the disease.
1) Jin, M., Shepardson, N., Yang, T., Chen, G., Walsh, D., & Selkoe, D. (2011). Soluble amyloid β-protein dimers isolated from Alzheimer cortex directly induce Tau hyperphosphorylation and neuritic degeneration. Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.1017033108 OPEN ACCESS
2) Zempel, H., Thies, E., Mandelkow, E., & Mandelkow, E. (2010). Aβ Oligomers Cause Localized Ca2+ Elevation, Missorting of Endogenous Tau into Dendrites, Tau Phosphorylation, and Des... Read more »
Jin, M., Shepardson, N., Yang, T., Chen, G., Walsh, D., & Selkoe, D. (2011) Soluble amyloid . Proceedings of the National Academy of Sciences. DOI: 10.1073/pnas.1017033108
by Michael Clarkson in Conformational Flux
The enzyme imidazole glycerophosphate synthase (IGPS) can be a bit of a lump. If you bind just one substrate it doesn't do anything, even though its two active sites are separated by more than 30 Å. Only if the second substrate also binds does catalysis actually go at anything like a respectable rate. In a recent paper in Structure researchers from Yale report evidence that this change of pace results from a change in dynamics.
Apo- IGPS from Thermatoga maritima
PDB code: 1GPW
IGPS consists of two different protein subunits, HisH and HisF (right). HisH performs a relatively standard hydrolysis of glutamine, producing ammonia and glutamic acid. The ammonia molecule is then used by HisF as part of a cyclization reaction involving a weird nucleotide called PRFAR (with an IUPAC name that's just too long to bother with). The products of this reaction feed into the biosynthesis of histidine (as you might guess from the name) and the purines. In an example of poor planning, however, the active sites for these two reactions are separated by a great distance. Glutamine hydrolysis takes place near the interface between the proteins (which bind to each other with nM affinity), while PRFAR cyclization takes place at the far end of HisF (near the bottom of the image). This is too far for the ammonia to be efficiently transferred by any direct action of the enzyme itself. Therefore, the reaction proceeds when the NH3 travels down the β-barrel of HisF to its distant active site (see image below left). The upside of this system is that ammonia gets where it needs to go. The downside of it is that unless the hydrolysis reaction only occurs when PRFAR is in position, this enzyme will be a little ammonia factory, costing the cell a fortune in nitrogen. Therefore, the cleavage reaction must be tightly regulated.
Enzymes can deal with this kind of demand in two ways. The first is to make the binding of one substrate depend on another. This is called K-type allostery because what is changed is the affinity (KD) of the enzyme for its substrates. Alternatively, the rate of catalysis can be altered, which is called V-type allostery because the velocity (Vmax) of the reaction is changed. IGPS uses the latter approach. When glutamine binds, NH3 gets eliminated at a stately pace of about 10-3 /s. If PRFAR also binds, however, HisH starts firing NH3 down the barrel at about 5 /s, which may not win many races but is a substantial enhancement. The question, then, is how the HisF active site lets the HisH active site know that PRFAR has arrived, when they are separated by more than 30 Å. Examining the enzyme complex in the presence of various ligands, James Lipchock and Pat Loria find evidence that changes to the dynamics of HisF are responsible for this communication.
A rotated view, looking through the barrel
towards the HisH active site.
The authors start by examining the energetics of PRFAR binding to IGPS. This event is endothermic, with an unfavorable enthalpy of binding. However, the entropic contribution is sufficiently large to overwhelm this effect. This could indicate a major increase in conformational entropy upon binding, or it could just be related to the behavior of water. Lipchock and Loria found that PRFAR binding to form the ternary complex had similar energetics. Of course, you can't form a ternary complex with actual substrates for very long, because catalysis would occur and change the affinities. They dealt with this using acivicin, a glutamine analogue that binds covalently to the active C84 of HisH.
Unfortunately, these thermodynamic data aren't particularly illuminating, so the authors proceeded with a high-resolution examination of the system. Because IGPS is a bit over 50 kDa in size, they chose to use methyl groups as their primary probes. Most of the remaining work in the paper uses ILV (Isoleucine, Leucine, Valine) labeling, which takes advantage of the favorable relaxation properties of the methyl groups of those side chains.
Lipchock and Loria started by examining the enzyme in its apo- state using relaxation-dispersion experiments. As I've mentioned before, these experiments detect exchange between different conformations on the microsecond to millisecond timescale. If this represents motion between two well-defined states, then the apparent relaxation rate at a given refocusing field strength will be a function of total process rate (kex = kab + kba), the populations of the two states (pa and pb), and the chemical shift difference between them (Δω). If the exchange rate is fast on the NMR timescale (meaning that kex >> Δω), the last three parameters can be combined into a factor called φex.
This is how the authors fit their data, a choice they justified by stating that fitting the data to the full Carver-Richards formula (SI equations 8-18) gives similar answers for kex but yields large errors in the populations and chemical shift differences. However, most of the dispersion curves look like data from slower exchange regimes. Unfortunately, I'm having trouble reconstructing their fitted curves from the parameters in any convincing way, in part because the equations in SI contain a few errors, so it's difficult to discuss where the vulnerabilities in this fitting procedure lie.
Using their approach, Lipchock and Loria find that only a few residues are experiencing conformational exchange, and they believe that the motions are primarily local. I'm not so certain on that point: a quick examination of SI Table 1 indicates that all but two methyls have kex within error of 150 /s or so, which may indicate that most residues belong to a single process. However, most of the residues with similar fluctuation rates don't physically group in any obvious way (although V100 and V79 are adjacent).
Regardless of the particulars, it's clear that in the apo- state, few of the methyl groups in HisF are experiencing any kind of µs - ms fluctuation. Binding of acivicin to HisH doesn't change this too much. Within the bounds of the fitted error, the extracted dynamics parameters are the same for many residues. The exceptions are the adjacent residues V79 and V100, and L153δ1, which has an odd halving of both rate and the combined parameter.
Also, as you can see in SI Table 2, the R2° values in this state are significantly lower than apo- IGPS. This is difficult to interpret without knowing exactly how the experiment was performed; they could represent additional ns fluctuations, the removal of some very fast global process, or simply different deuteration efficiency. However, some methyls do not appear to have large changes in their R2° values (e.g. V56γ2, I73δ1, L94δ1). Most of the spurious factors that would give rise to the observed changes in R2° should affect all residues more or less equally; the lack of uniformity suggests this may be worth following up on.
When Lipchock and Loria added PRFAR to the system, all hell broke loose. Many of the amide groups in the protein had their signals broadened beyond the detection limit, indicating conformational exchange on the intermediate timescale. In addition, a large number of methyl groups showed evidence of conformational exchange.
Here the fluctuation is obviously a genuinely incoherent one. Not only do the fitted kex values vary wildly across the protein, they also have poor fitting characteristics (including fitted errors greater than 100%), and enormous differences between adjacent methyls on a side-chain (e.g. L153δ1,2). This suggests that the two-state mode... Read more »
Lipchock, J., & Loria, J. (2010) Nanometer Propagation of Millisecond Motions in V-Type Allostery. Structure, 18(12), 1596-1607. DOI: 10.1016/j.str.2010.09.020
by Michael Clarkson in Conformational Flux
In the Monod-Wyman-Changeux model for cooperative binding, proteins exist in an equilibrium of low-affinity and high-affinity states in solution, absent any ligand. In this view, although it may appear that the binding of a ligand causes a conformational transition, it actually stabilizes one conformation from a pre-existing equilibrium. In the past several years, advanced NMR techniques have yielded increasing evidence that these structural equilibria exist for a number of proteins, suggesting that this model for linkage between conformational change and binding may be quite general. An upcoming paper in the Journal of Molecular Biology (1) is typical of such findings.Farber and Mittermaier studied the behavior of a homeodomain, a small, all-helical domain that typically binds to DNA, often in concert with other homeodomains. In particular, they were interested in the homeodomain of PBX1 (PBX-HD) which binds DNA cooperatively with a homeodomain from HOXB1 (HOX-HD). The domains interact with the DNA target and with each other. Peptides representing the binding site from the HOX-HD bind detectably to PBX-HD only in the presence of the target DNA, suggesting that the two binding sites communicate. The third helix of the PBX-HD is likely to mediate the allostery since it's involved in both binding interactions, but it's not clear from the available structures how this would happen. Additionally, there is a C-terminal sequence, with no defined fold in the free structure, that forms a helix in the ternary complex. It does not interact directly with the DNA, but removal of this extension decreases the affinity of PBX-HD for DNA and weakens the cooperativity between PBX-HD and HOX-HD.
Helix folding has a low energy barrier, so it is reasonable to suspect that this helix could form even in the absence of DNA. Farber and Mittermaier examined this possibility using a technique I have often discussed on this blog: CPMG relaxation dispersion. As you may recall, this technique is sensitive to fluctuations between states (chemical exchange) that persist for microseconds or milliseconds. One can in principle determine the rate of exchange (kex), the population of each state (pA, pB), and the chemical shift difference (|Δω|) between them, although if the motion is too fast or too slow only composites of some of these can be reliably determined. When they performed the experiment, the authors found that residues throughout PBX-HD had significant broadening, indicating chemical exchange and suggesting that the protein does not spend all its time in one folded state. The relaxation-dispersion profiles they obtained at 10 °C and 15 °C were in the intermediate regime, where all three of the aforementioned parameters can be determined.
For the C-terminal extension, the |Δω| determined by fitting the relaxation-dispersion data were linearly correlated with the chemical shift change that was observed in an HSQC upon binding (|Δδ|). The correspondence wasn't exactly 1:1, but this is still reasonably good evidence that the helix is folding independent of binding. The authors used the |Δω| from the 10 °C fits to pull populations and rates from the experiments performed at higher temperatures, where only a composite parameter can be reliably determined (due to the speed of the fluctuation). Arrhenius plots derived from these data indicate thermodynamic parameters that are consistent with the folding of a single helix, again supporting the proposition that the C-terminal helix can fold on its own.
Numerous residues in the folded portion of the domain also experienced chemical exchange, which could mean that the helix is not the only thing undergoing a structural transition. The authors fit these residues individually, then tried again while fixing kex to the value determined from the helix behavior. The latter fits were not much worse in terms of their residuals than the floating fits were, so the fluctuations here could reasonably be seen as consistent with the helix-folding fluctuation.
If this is so, then removing this unstable helix should quench the dynamics in the folded part of the protein. This turned out to be the case — when the helix was removed, the dispersion curves for residues in the folded part of the protein became flat. This reinforces the case that the dynamics detected in the folded domain are related to the folding of the helix, and therefore represent an excursion to the "bound" structure for ligand-free protein.
Farber and Mittermaier note that for residues in the folded portion of the domain, the |Δω| determined through the CPMG analysis does not appear to agree with the |Δδ| observed upon binding DNA. From this they conclude that the conformational change in solution is actually going to some unknown third state that is different from both the free and bound structures. I disagree somewhat with this interpretation. Because the ligand (in this case a piece of double-stranded DNA) is large relative to the protein and possesses substantial negative charge, there's a significant possibility of long-range electrostatic effects on the chemical shift of the PBX-HD. That is, the protein's bound state might have different chemical shifts free in solution and bound to the ligand even without any major conformational changes. If this is the case, the |Δω| will correlate best with |Δδ| for residues that are far from the interface. Probably the structure sampled by the free protein is not exactly the same as the bound structure, but I think further data would be needed to determine whether the alternative structure in the free state differs significantly from the bound structure with DNA.
The uncertainty about the alternative structural state of the free protein makes it more difficult to make a firm argument about whether the binding mechanism more closely resembles conformational selection or induced fit, or whether it's some kind of middle ground between the two. Although it's suggestive, the observation of a structural equilibrium in the free state does not actually indicate how binding occurs. Moreover, because this is a complicated ternary complex, it is possible that, say, the protein-binding mechanism is conformational selection, while the DNA mechanism is induced-fit. This latter possibility might seem more sensible in light of existing studies indicating that long-range (e.g. electrostatic) interactions may predispose a system to induced-fit binding.
Complications aside, these data seem to support a model in which the PBX-HD transiently adopts the bound conformation in the absence of ligand. Binding of the PBX-HD domain to DNA shifts its population towards the state that is the minority in solution. This new structure has high affinity for the HOX-HD, promoting the formation of the ternary complex. In principle, binding of the HOX-HD to PBX-HD could precede DNA binding by both modules, but the interaction between these proteins appears to be weak in the absence of DNA. However, proving that the excursion to the bound (or near-bound) PBX-HD structure represents an actual intermediate in the binding process rather than just an interesting fluctuation on the side will require some determination of the binding kinetics in various conditions.
(1) Farber, P., & Mittermaier, A. (2010). Concerted Dynamics Link Allosteric Sites in the PBX Homeodomain Journal of Molecular Biology DOI: 10.1016/j.jmb.2010.11.016... Read more »
Farber, P., & Mittermaier, A. (2010) Concerted Dynamics Link Allosteric Sites in the PBX Homeodomain. Journal of Molecular Biology. DOI: 10.1016/j.jmb.2010.11.016
by Michael Clarkson in Conformational Flux
Clostridium difficile is an intestinal pathogen that causes diarrhea in hospitals and other healthcare settings (including nursing homes). Present as a commensal bacterium in a significant fraction of the population, C. difficile is usually rather harmless, its numbers suppressed by competition with the intestinal flora. When its competitors are decimated by antibiotics, however, C. difficile flourishes, releasing toxins that cause inflammation and diarrhea, which can be dangerous because the individuals suffering these effects are often already ill. There has been conflicting information, however, as to which of C. difficile's toxins are necessary to cause disease. A paper in the recent Nature (1) aims to resolve the question.
The two best-characterized C. difficile toxins (TcdA and TcdB) have the same general arrangement and function (and ~45% identical AA sequence). An N-terminal glucosylating domain attacks the cytoskeleton of host cells by inactivating Rho GTPases, a C-terminal domain mediates binding and uptake by the host cells, and a protease domain in the middle releases the glucosylating domain to do its work. Since these proteins appear to serve redundant functions, one might expect that both would support virulence. However, preceding work in the field has variously identified TcdA or TcdB as a key virulence factor (2,3). Differences in methodology and materials have contributed to the confusion, in part because different kinds of cells seem to be more or less susceptible to particular toxins, and different strains of C. difficile might have different behaviors.
Kuehne et al. aim to relieve some of the confusion by removing a subset of these confounding factors. In a single strain of C. difficile they inactivated the genes for either TcdA, TcdB, or both by inserting introns into them. An intron would be no problem for a eukaryote, but bacteria can't handle them, so this has the effect of eliminating the expression of the gene. They then tested the toxin mixtures shed by the bacteria against cultured human and monkey cells. As expected, A-B- bacteria (with both toxins knocked out) showed no toxicity towards the cells, but A-B+ and B+A- variants were toxic towards both kinds of cells to roughly the same degree. This suggests that both toxins are sufficient for virulence.
This implication was largely backed up by a subsequent experiment in hamsters. The animals were dosed with an antibiotic and then infected with C. difficile spores of a single strain. Colonization occurred (in every case but one) within three days. The hamsters infected with A-B- C. difficile remained asymptomatic until the end of the experiment, but the recipients of the other strains all perished within a week. The A+B- group survived somewhat longer, but not dramatically so; again, this supports the interpretation that both proteins are sufficient for virulence.
This contrasts with an earlier study published in Nature (2) where it was shown that deletion of the B toxin protected hamsters from C. difficile-associated disease, using very similar protocols. Kuehne et al. attribute the differences in their results to the hamsters or genetic variation in the C. difficile strains used. While the virulence of the B- strain in this experiment was slightly attenuated, all colonized hamsters still died in relatively short order, and in human beings the situation might well be reversed, since cultured human cells are more vulnerable to toxin A.
The results of Kuehne et al. largely agree with earlier experiments (3) and with what one would naturally expect of two very similar toxins being released by the same organism. While susceptibility to a particular toxin may vary with characteristics of the host species or cell type, it seems likely that both toxins are capable of supporting virulence. While it is to be hoped that additional research will clarify the reasons for the discrepancy between these two experiments, efforts to treat C. difficile-associated disease by attacking the toxins should proceed with the assumption that both must inactivated. Thanks to their functional and sequence similarity this will hopefully not be too much of a complication.
1. Kuehne, S., Cartman, S., Heap, J., Kelly, M., Cockayne, A., & Minton, N. (2010). The role of toxin A and toxin B in Clostridium difficile infection Nature, 467 (7316), 711-713 DOI: 10.1038/nature09397
2. Lyras, D., O’Connor, J., Howarth, P., Sambol, S., Carter, G., Phumoonna, T., Poon, R., Adams, V., Vedantam, G., Johnson, S., Gerding, D., & Rood, J. (2009). Toxin B is essential for virulence of Clostridium difficile Nature, 458 (7242), 1176-1179 PMCID: PMC2679968 OPEN ACCESS
3. Voth, D., & Ballard, J. (2005). Clostridium difficile Toxins: Mechanism of Action and Role in Disease Clinical Microbiology Reviews, 18 (2), 247-263 PMCID: PMC1082799 OPEN ACCESS... Read more »
Kuehne, S., Cartman, S., Heap, J., Kelly, M., Cockayne, A., & Minton, N. (2010) The role of toxin A and toxin B in Clostridium difficile infection. Nature, 467(7316), 711-713. DOI: 10.1038/nature09397
by Michael Clarkson in Conformational Flux
If you're going to study the role an enzyme plays in a biological pathway, it's often useful to "kill" it with a mutation. For example, the proline cis-trans isomerase cyclophilin A (CypA) needs a particular arginine residue for its chemistry, so mutations that remove or alter that functional group, like R55K and R55A, should destroy the protein's function and have effects on the related pathways that help illustrate its role. The hydrophobic pocket it uses to bind substrates is made by residues like H126, F113, and W121. Growing or shrinking those residues should alter the shape of the pocket and change binding or activity, leaving the enzyme "dead".
Using model reactions and various binding assays, researchers have previously examined a number of these mutants (4,7) and found that they diminish isomerase activity and alter inhibition. However, a detailed study of the effects of the mutations on CypA's catalytic cycle has not been performed. Former Kern lab members Daryl Bosco (now a professor at UMass Medical) and Elan Eisenmesser (now at UCHSC) examined these mutants in greater detail to see how they really behaved. I also contributed some data at the last minute, when the third reviewer requested we study an additional mutant, prompting a scene that I promise was not too much like that Downfall parody. In every case we found that these enzymes, although significantly impaired, weren't as dead as they had seemed.
You had me at "dunno"
CAN bound to CypA, from PDB structure 1AK4 (5).
CypA residues are labeled in black, CAN residues in red.
One key aspect of this work is that it involves a physiological substrate of CypA, namely the N-terminal domain of the HIV-1 capsid protein (CAN). Mature HIV-1 virions contain CypA that is bound to proline 90 of CAN. The absence of CypA dramatically reduces their ability to infect their target cells, which we know from experiments with mutant CA proteins as well as ones involving the CypA inhibitor cyclosporin (3). What we don't know about the system is exactly what CypA does for HIV-1. The crystal structure (right) of CAN in complex with CypA appears to only capture the trans isomer configuration (5), but for reasons I have discussed previously on this blog, that's not particularly informative. We know, largely from Daryl and Elan's previous research on the system (2), that when CAN is floating free in solution CypA will catalyze isomerization, but in the context of a fully assembled capsid that situation could conceivably change.
This leaves us with three possibilities for CypA's function in the capsid. Catalysis of cis-trans isomerization of the proline bond could be important. Or, maybe all capsid needs is for CypA to bind at P90, and catalysis is irrelevant. And perhaps neither of these functions matters and CypA just needs to be hanging around for some other reason. To address these possibilities, Saphire et al. performed an elegant series of experiments where they sneaked an engineered CypA protein into another part of the capsid by fusing it to a protein called Vpr. When they replaced the normal CypA sequence with a mutant (H126A) that was supposed to abrogate both binding and catalysis, HIV-1 could still infect CD4+ cells (6). But, how sure can we be that H126A, or any other mutant, is actually "dead"?
You can't measure what you can't see
The problem with proline isomerization, from a biochemist's standpoint, is that it's a difficult reaction to detect. While switching between isomerization states may have structurally significant effects, there's no direct spectroscopic signal to tell you whether a proline bond is in the cis or trans conformation. Even if there was, most proteins have many prolines and so the signal of the bond you care about might be difficult to separate from the bonds you don't.
You can get around this difficulty using a coupled reaction with a model substrate. CypA catalyzes the isomerization of tetrapeptides of the form AXPF pretty efficiently. As it turns out, sequences like this are also good substrates for the protease chymotrypsin, but there's a catch. Chymotrypsin only cleaves substrates where the proline bond is in the trans configuration. So, what you can do is take a substrate like succinyl-Ala-Ala-Pro-Phe-p-nitroanilide, add a tiny amount of cyclophilin, and then dump in a huge amount of chymotrypsin. With enough chymotrypsin, the peptide that's already trans will be cleaved before the solution stabilizes, causing a color change (due to the pNA) that can be measured with a conventional spectrophotometer. Then you can monitor the conversion of the remaining substrate from cis to trans, because there's so much chymotrypsin that cleavage after isomerization is essentially instantaneous.
This works reasonably well, but it has some limitations. You're stuck with a model peptide that may not behave very much like your particular protein substrate. You're only following the cis-to-trans reaction, and even that comes with limited detail. Also, performing the experiment takes some careful work, because if you add too much of your CypA the reaction will end before the solution turbulence settles, and if you add too little, the intrinsic cis-trans isomerization will interfere with your catalytic measurement.
Although proline isomerization is a difficult reaction to follow by spectrophotometry, it's actually quite convenient to assay by NMR. Because CypA catalyzes the reaction in both directions, it's impossible to exhaust the substrate. The kinetics can therefore be measured at equilibrium using NOESY and ZZ-exchange experiments (2). Of course the experiment is limited by our ability to express isotopically-labeled substrate proteins, but provided we can do that and visualize the active site in our spectra, then we can observe catalysis of the native substrate. When you perform this experiment on these various "dead" forms of CypA using CAN as a substrate, it becomes evident they're still active after all.
Night of the living "dead" enzymes
Panels B-G of Figure 3 in this paper directly show that every single one of the CypA mutants catalyzes CAN isomerization in solution (1). These spectra show peaks representing the chemical shifts of the nitrogen and hydrogen atoms of CAN's backbone amide groups in the presence of a small amount of CypA, so we are not looking at P90 directly. Fortunately, the chemical shift of the G89 amide is dependent on the isomerization state of P90. If the G89-P90 bond is in trans, G89 shows up as the large peak at lower right in these panels, but if the bond is in cis you get the small peak at upper left.
If you don't wait very long between determining the 15N chemical shift (y-axis) and the 1H chemical shift (x-axis), you get something that looks like panel A. If, however, you pause between determining the 15N shift and the 1H shift, you get cross-peaks representing the portion of CAN proteins that started the experiment in trans and ended it in cis, or vice-versa. The presence of these cross-peaks in the CAN/CypA samples, and their absence in the CAN-only sample (panel A), proves that catalysis is occuring. I've blown up the figure for H126A on the right to make things a little clearer. In this case the cross-peaks were pretty weak, but still in evidence.
... Read more »
Bosco, D., Eisenmesser, E., Clarkson, M., Wolf-Watz, M., Labeikovsky, W., Millet, O., & Kern, D. (2010) Dissecting the Microscopic Steps of the Cyclophilin A Enzymatic Cycle on the biological substrate HIV-capsid by NMR. Journal of Molecular Biology. DOI: 10.1016/j.jmb.2010.08.001
Saphire, A.C.S., Bobardt, M.D., & Gallay, P.A. (2002) "trans-Complementation Rescue of Cyclophilin A-Deficient Viruses Reveals that the Requirement for Cyclophilin A in Human Immunodeficiency Virus Type 1 Replication Is Independent of Its Isomerase Activity". Journal of Virology, 76(5), 2255-2262. DOI: 10.1128/jvi.76.5.2255-2262.2002
by Michael Clarkson in Conformational Flux
Most people never learn about an actual scientific controversy. Almost every "controversy" that bubbles into the public eye is manufactured, often reflecting social or ethical differences rather than genuine disagreements between experts about how different models fit to reality. Actual scientific controversies tend to be highly technical, and often concern points that lay people find to be esoteric. That doesn't mean that the issues involved aren't important, or that they're even difficult to understand. One controversy that has unfolded over the past few years and now may be over relates to a seemingly simple question. Where do adamantane drugs bind to the influenza A M2 channel?
Previously, on As the Channel Twists...
Bill DeGrado and James Chou, whose
competing structures began the controversy
The M2 proton channel plays an essential role in the life cycle of the influenza virus. The activity of the channel could be blocked, at least in influenza A, by drugs called adamantanes, including amantadine and rimantadine. Unfortunately, these antiviral drugs have been fading in efficacy due to the spread of an S31N mutation that interferes with their binding. On January 31, 2008, two articles appeared in the scientific journal Nature showing adamantanes bound to the M2 channel. Unfortunately, the structures had different answers about where the drug was bound. The X-ray crystal structure from Bill DeGrado's group at the University of Pennsylvania placed amantadine in the center of the channel's pore, suggesting a simple pore-blocking model (PBM) for inhibition. The NMR structure from James Chou's group at Harvard University located rimantadine on the outside of the channel, ultimately giving rise to an allosteric, dynamic quenching model (DQM) of adamantane activity.
As outlined in my previous post on the M2 channel, there was conflicting functional evidence as to which site was actually relevant in vivo, and reasons to doubt the conclusions from both structures. Since that time, several papers have been published that substantially clarify the issue. At this point, the evidence strongly supports the PBM as an explanation of adamantane activity in vivo.
Sure adamantanes bind there, but does it matter?
The direct observation of NOEs, even weak ones, between the adamantane and the protein proved that the drugs were binding at the DQM site, but there were some significant areas of concern with this finding. The greatest worry was due to the extremely high concentration of ligand used in the NMR experiment. This opened up the possibility that the DQM site was a low-affinity site that would not see binding under normal circumstances. Because both models had explanations for the efficacy of the S31N mutation, the only way to address the question would be to make mutations that would abolish binding at the DQM site and see if adamantanes were still effective. Because aspartate 44 was proposed to form a hydrogen bond to rimantadine, it was thought that a D44A mutation would eliminate binding, and if DQM was true, adamantane activity. This prediction was borne out by an experiment performed in liposomes by the Chou lab (6), but Robert Lamb's group from Northwestern University was not able to replicate this result in X. laevis oocytes (4).
Robert Lamb has studied the
M2 channel since the 80s.
What Lamb's group did do was test different parts of the influenza A channel for adamantane sensitivity by fusing them to the adamantane-insensitive influenza B channel. These A/B M2 chimeras should in principle have adamantane susceptibility if the legitimate binding site got imported from A to B. Their first results in this experiment were somewhat inconclusive. Adding the N-terminal portion of the A channel to the C-terminal portion of the B channel (essentially sticking the PBM site into B M2) created a chimera that was somewhat sensitive to amantadine treatment, but the effect was nowhere near what occurred for WT A channel (4). Subsequently, Lamb's group expanded these experiments to add a little bit more of the N-terminal sequence to the chimera, which then almost perfectly matched the WT A channel's susceptibility. Notably, when they made the opposite chimera that incorporated the DQM site from A into the B channel, only a very slight inhibitory activity was observed upon addition of amantadine (5). While the conclusions that can be drawn from the chimeras are limited by their particularly odd provenance, the fact that transplanting the PBM site from one channel to another confers adamantane susceptibility suggests that this is the functional binding site.
An upcoming paper in PNAS clarifies the picture somewhat using surface plasmon resonance (SPR) (7). This technique detects the binding of a ligand as a change in physical force exerted by a protein tethered to the surface of a gold chip. In this case, the tethering was mediated by a DMPC liposome. This was a tricky experiment because adamantanes like the greasy portions of lipid bilayers, so they can bind to the liposome itself. Rosenberg and Casarotto, however, were able to control for this effect. Their SPR experiments detect two distinct adamantane binding sites on M2 with vastly different affinities. Rimantadine binding at the high-affinity site could be abrogated by S31N and V27A mutations, but not a D44A mutation. At the low-affinity site, rimantadine binding could be knocked out by a D44A mutation or an S31N mutation, but not a V27A mutation. This result indicates that both binding sites are functional (and, incidentally, that the S31N mutation does indeed exert an allosteric effect on the DQM site). However, the authors note that the adamantane concentrations used in actual treatment are too low to significantly populate the low-affinity site, given the dissociation constants they calculated. This argues that the DQM site is irrelevant in vivo.
Amantadine caught in the pore
Mei Hong has studied M2
extensively by NMR
One of the problems with the PBM was that the crystal structure that supported it was unsatisfactory in a variety of ways. The structure was made using a construct that consisted of only the transmembrane segment of the protein. This construct could not be reconstituted in micelles, and functional experiments showed that it was not very similar to the WT in terms of its activity. In addition, the extra electron density in the pore could not be unambiguously assigned as amantadine. In a paper from February of this year, the DeGrado group collaborated with Mei Hong's group at Iowa State University to produce a structure of amantadine bound to M2 using solid-state NMR (2). An important advantage of this approach is that one can take spectra of proteins embedded in a membrane without penalty, because there is no requirement for the protein to tumble freely. While there are some trade-offs in terms of resolution and the kinds of data that can be obtained, biomolecular solid-state NMR can help us answer some very tricky questions.
... Read more »
Andreas, L., Eddy, M., Pielak, R., Chou, J., & Griffin, R. (2010) Magic Angle Spinning NMR Investigation of Influenza A M2 : Support for an Allosteric Mechanism of Inhibition . Journal of the American Chemical Society, 2147483647. DOI: 10.1021/ja101537p
by Michael Clarkson in Conformational Flux
We all know that linear polymers of amino acids (proteins) adopt complex three-dimensional structures when they are dissolved in water. The process of forming these structures is called folding, and it is understood to occur because proteins are amphiphilic. Some parts of a protein chain like to interact with water (hydrophilic), while others are oily and want to get out of water (hydrophobic). Folding of the chain sticks all the oily parts together on the inside of the structure while the parts of the chain that have favorable interactions with water remain on the outside. An upcoming paper from the Journal of Physical Chemistry B suggests that sufficiently long alkanes might undergo a similar transition, even though they don't have any chemical groups that like to interact with water.
Researchers from Purdue University performed a variety of simulations of linear alkanes, which are saturated hydrocarbon chains typically designated by the number of carbons they contain (C8 has 8 carbons). Because increasing the length of the chain just involves inserting an identical unit, one might expect that after a certain point the properties of these molecules would scale linearly with chain length. Previous experiments and simulations, however, indicated that the free energy of hydration did not match this predicted linear trend. Instead, the free energy of hydration (ΔG) remained flat or even decreased as chain length increased. This is because the linear extrapolation only holds for a chain that adopts a linear (all-trans) configuration. As chain length increases, however, the numerous additional degrees of freedom allow a chain to adopt a more compact conformation that decreases the penalty incurred by interacting with water.
Given this understanding, the authors asked whether a sufficiently long alkane might be hydrophilic. They established theoretical bounds for this question by examining two extreme possibilities. In the first, the alkane was assumed to be linear, and of course the ΔG never crossed zero. In the second, the alkane was assumed to collapse into a sphere; in this case the free energy becomes favorable after less than a dozen carbons. Presumably the reality lies somewhere in between. To get a more realistic view of the situation, they also simulated the behavior of alkane chains of various sizes, and found that the potential energy released by dissolving an alkane in water was correlated with the solvent-accessible surface area (SASA). From their findings they predicted that an alkane that was long enough would eventually cross over into hydrophilicity.
This is pretty interesting, but there are some significant weaknesses. The work here is purely theoretical and uses a molecular dynamics forcefield with an imperfect model of water behavior. The predictions of this simulation have been validated on real-world chemical samples, but only up to a comparatively modest chain length of C16. Because the surprising prediction lies very far from the zone of simulations that have been experimentally confirmed, one could argue that this is all just an extended discussion of a failure of the model. As they are aware of this shortcoming, the authors performed a number of simulations on collapsed (globular) C100 alkanes in order to determine the energy of the interaction between the chain and water, as well as the SASA. They found that, within error, the simulated values also indicated a negative ΔG of hydration.
As the authors note, this result doesn't necessarily mean that you could dissolve a whole bunch of C100 in water. The ΔG calculated here is for transfer from the gas phase into water, and C100 is unlikely to be highly volatile, given that all the higher paraffins are solids. In addition, these are simulations of a single hydrocarbon chain in water, and so they don't tell us about the energetics of lipid-lipid interactions. Oils segregate out of water because the oil-oil interaction is more favorable than the oil-water interaction. If this holds true for C100, even if dissolving in water is itself favorable, the alkane will still form oil droplets more readily than it will dissolve.
Using their models, the authors predict that the surface tension of an oil droplet will be negative at chain lengths greater than C50, thus tending to release oil into solution, but I'm a bit worried about this prediction. First, the molecular surface tensions are very far off from the macroscopic tensions, indicating that this calculation misses a great deal about the interaction. In addition, they perform a linear extrapolation from the approximately linear tail of what appears to be an exponential curve. It's not clear why this extrapolation was used or what conclusions can be drawn from it; the molecular surface tension could just as easily be asymptotic with respect to the zero point.
Experimental verification of this prediction is unlikely to appear any time soon, if at all. Synthesizing very long alkanes is not trivial, especially in the quantities and purities required to put these simulations to the test. Ultimately the value of a paper like this is not in any practical application, but rather in the fact that it reminds us of the strength of the forces that guide the formation of higher-order chemical structures. Even in the absence of any group that has an intrinsically favorable interaction with water, the energy released by self-binding of hydrophobic groups may give rise to a "folded" structure for very long alkanes.
Underwood, R., Tomlinson-Phillips, J., & Ben-Amotz, D. (2010). Are Long-Chain Alkanes Hydrophilic? The Journal of Physical Chemistry B DOI: 10.1021/jp912089q... Read more »
Underwood, R., Tomlinson-Phillips, J., & Ben-Amotz, D. (2010) Are Long-Chain Alkanes Hydrophilic?. The Journal of Physical Chemistry B, 2147483647. DOI: 10.1021/jp912089q
by Michael Clarkson in Conformational Flux
On several previous occasions on this blog I've discussed proteins that undergo significant changes in structure without drastic changes in their primary sequence or solution conditions. In some cases, a few mutations can take a protein to a novel fold, as with Philip Bryan's protein G work. In others, closely related sequences within a whole family populate different kinds of folds, as Matt Cordes illustrated for the case of Cro proteins. In addition, there are some cases such as lymphotactin, where interconversion between two very different structures takes place at equilibrium, as illustrated by Brian Volkman's research. Each time stories like this come up I have mentioned that this kind of behavior (termed "metamorphism" in a 2008 commentary by Alexey Murzin) suggests a means by which proteins could evolve from one structure to another without losing foldedness or function. Recently, a group from the Weizmann Institute published results in PNAS that speak to this possibility.
Yadid et al. are looking at a class of proteins called β-propellers. Characteristics of the sequences of these proteins, especially high homology between different blades within a protein, suggest that these proteins are "built up" by gene duplication and fusion from precursors that were either multimeric in nature or made from a smaller number of blades (or both). In particular, they worked with a protein called tachylectin-2, that binds sugars. You can see its structure at right (or examine it at the PDB). The color-coding recognizes that the N and C termini are adjacent to one another, meaning that each "blade" of the propeller actually incorporates one strand from a neighbor. The whole protein is a bit under 250 residues in size. Previously, the authors of this paper had randomly chewed up the tachylectin-2 DNA from either end, a process that one might expect would produce a bunch of useless garbage. Some of the products of this experiment, however, were functional pentamers. But, they were about 100 amino acids long, suggesting that each monomer incorporated two blades. This meant that the structure of the pentamers had to differ from that of the original protein in some key way, but the proteins could not be crystallized due to low yields and instability.
To solve this problem, Yadid et al. performed directed-evolution refinement of the sequences of two promising candidates. From the pool of proteins thus produced they were able to crystallize two, which had interesting properties. As one might expect given the known data, both these proteins formed ten-bladed propellers (the structures have PDB codes 3KIF and 3KIH) in the form of two five-bladed propellers that were linked to each other. In the case of the mutant called Lib2-D2-15, 3 of the 100-residue subunits contributed two blades to the propeller apiece, while the remaining two monomers each contributed to three blades. That doesn't add up to 10 because each of the two oddballs contributed four strands to one blade, three strands to another, and one strand to the third. That means one blade was uniquely of that monomer and the other two were shared. One of these blades was shoved into the second propeller, generating an asymmetric pentamer. Note also that the two oddballs weren't equivalent: one was arranged 4-3-1 and the other 3-1-4. The other mutant, Lib1-B7-18, was even weirder in some ways. In that mutant, four of the monomers contributed to three blades in a 1-3-4 manner. The last monomer, however, contributed to four blades, two from each propeller, with a pattern of 1-3-1-3. Because these structures cannot form unless the monomers adopt multiple structures (3 in the case of Lib2-D2-15 and 2 in the case of Lib1-B7-18), it follows that the monomers must be metamorphic.
The evolved fragments didn't have higher stability to guanidinium hydrochloride than the source fragments, suggesting that the improved expression and solubility was not due to improved stability. The authors argue that the improved expression was mostly due to a change in the isoelectric point of the mutants, which decreased towards neutral in both cases. However, the evolved fragments also were able to refold from the denatured state, which the source fragments could not do. To the authors, this suggests that the directed evolution process actually selected for metamorphism; that is, the proteins were stabilized by an increased ability to sample states that formed productive pentamers.
The observations in this study, although very interesting, do not tell us anything directly about the evolution of tachylectin-2. While it is possible that the current protein evolved from a metamorphic precursor like these fragments, there is no direct evidence that this is the case, nothing to indicate that evolution performed in reverse what Yadid et al. did here. Whether metamorphism contributed to the diversity of β-propeller folds in general, or to the evolution of this protein in particular, remains very much an open question. The metamorphism observed here may be more a consequence of a particularly robust fold tending towards its original state than evidence of hidden metamorphic potential in singular structures. As such, the article's title strikes me as overbold given the data. That said, it is certainly not implausible that odd assemblies like these pentamers played a role somewhere along the evolutionary path that created the rich library of β-propellers we have today, and this study establishes that even very strange steps along the way can occur without destroying the protein's function or certain gross features of its structure.
Yadid, I., Kirshenbaum, N., Sharon, M., Dym, O., & Tawfik, D. (2010). "Metamorphic proteins mediate evolutionary transitions of structure." Proceedings of the National Academy of Sciences, 107 (16), 7287-7292 DOI: 10.1073/pnas.0912616107... Read more »
Yadid, I., Kirshenbaum, N., Sharon, M., Dym, O., & Tawfik, D. (2010) Metamorphic proteins mediate evolutionary transitions of structure. Proceedings of the National Academy of Sciences, 107(16), 7287-7292. DOI: 10.1073/pnas.0912616107
by Michael Clarkson in Conformational Flux
Although we are most familiar with the circadian rhythm from its effects on our physiological state, the roots of the phenomenon lie in the molecular biology of individual cells. The circadian rhythm is the result of a transcriptional control system that regulates the levels of many different proteins in the cell with the passing of time. Not all of the proteins subject to this control have yet been catalogued, and as a result some surprising effects are still being discovered. A recent article in Proceedings of the National Academy of Sciences from the Sancar lab at UNC suggests that circadian control of a DNA repair factor may be a way to enhance the effectiveness of a chemotherapeutic agent. The article is open access, so I encourage you to open it up and read along.
Previously, the Sancar group has shown that the circadian rhythm affects DNA repair in brain cells. In that case, DNA had been damaged by UV irradiation, a lesion that had to be replaced by the excision repair mechanism. Because one of the critical factors for this kind of repair, the Xeroderma Pigmentosum A protein (XPA), undergoes a circadian oscillation, the efficiency of repair depends on the time of day at which the damage occurred. Kang et al. hypothesized that this circadian dependence could also be true for other forms of DNA damage that undergo excision repair.
This led them to cisplatin, a drug used as primary chemotherapy or part of a combinatorial regimen for several kinds of cancer. Cisplatin creates covalent bonds crosslinking DNA bases in an intra-strand or inter-strand manner. These covalent linkages make replication (and therefore mitosis) impossible, and elicit a DNA repair response. If the cell cannot clear the crosslink, it will either die by apoptosis, or if the apoptotic response is suppressed, fail to produce viable daughter cells. Either way, the growth of the tumor is suppressed. The excision-repair pathway is the only mechanism of clearing this kind of DNA damage, so Kang et al. thought that there might be a robust circadian dependence. In order to test this idea, they carried out experiments using extracts from mouse liver and testis.
Figure 1 shows the results of their experiment using liver extract. Panel C summarizes the key results (data shown in panels A and B) that XPA mRNA, XPA protein, and excision repair efficiency are correlated with the dark/light cycle the mice are experiencing, with the highest levels of protein and repair occurring in the late afternoon, and the lowest levels in the very early morning (around 5 AM). Panel E shows a comparison of excision repair between normal mice and ones that have been genetically modified to lack cryptochrome, a critical circadian clock protein. In these CryDKO mice the time of day has no effect on the efficiency of repair, and as panel F shows, they also do not have the daily fluctuation in XPA mRNA and protein levels. These results suggest that circadian control of XPA expression levels dictates repair efficiency in liver tissues — as panel D shows, addition of exogenous XPA protein can recover the excision repair activity. However, there was no detectable circadian dependence for excision repair activity in testis, as Figure 2 shows using similar experiments.
Circadian control of XPA activity is possible because the protein doesn't last very long in the cell. Figure 3 shows experiments using two inhibitors: cycloheximide (CHX), which prevents protein synthesis, and MG132, which prevents protein degradation by the proteasome. The gel in panel A shows that in two different types of cells, CHX treatment caused XPA protein to disappear over a period of three hours, in contrast to the control protein actin, which was unaffected. Addition of MG132 caused XPA to accumulate with time, although actin levels were again constant. The fairly rapid degradation of XPA protein means that the overall quantity of that protein in a cell will be highly dependent on the concentration of its mRNA transcript. That is, you can only have high XPA levels if there's a lot of mRNA so ribosomes can continue to produce it. Circadian control of transcription is therefore able to regulate protein concentration. The authors hypothesize that this tight circadian control may have developed to prevent deleterious effects of non-specific DNA repair activity during times when there is no chance of UV insult, although there is no specific evidence to support this conjecture presently.
The MG132 experiment indicates that XPA is degraded by ubiquitin ligation and subsequent destruction in the proteasome. Figures 4 and 5 show a variety of evidence indicating that this process is mediated by the ubiquitin ligase HERC2. The experiments in figure 4 establish that HERC2 binds to XPA (panels A and B) and colocalizes with it in the cell (panels C and D). The gels in Figure 5 show that when HERC2 levels in the cell are knocked down by RNA inhibition using siRNA specific for that protein, CHX treatment does not cause XPA to degrade. These facts indicate that HERC2 is the ubiquitin ligase for XPA. The direct effect of HERC2 activity on the repair of cisplatin DNA damage is shown by figure 6. Here, cells were treated with cisplatin and HERC2 siRNA. The left side of panel A shows the clearance of cisplatin adducts from A549 cells over time (the right side shows the total DNA). As you can see, addition of HERC2 siRNA allows for more rapid clearance of the adduct, with a particularly dramatic effect at low dosage.
Unfortunately, due to its extreme toxicity, treating cancer cells with CHX is not a viable strategy for chemotherapy. However, knowing that the level of XPA protein in some target cells varies in a predictable way with the time of day can help doctors optimize treatments for maximum effectiveness. In particular, for cancers originating in tissues that have a strong circadian rhythm and intact XPA, early-morning treatment with cisplatin may be more effective than treatment at other times of the day. More experiments are needed before this can be formally recommended — in particular, whole-animal studies and human trials will be necessary to definitively establish the effect. If these results hold up in whole organisms, however, the circadian effect on DNA repair may become a valuable tool for optimizing some chemotherapy regimens.
Kang, T., Lindsey-Boltz, L., Reardon, J., & Sancar, A. (2010). "Circadian control of XPA and excision repair of cisplatin-DNA damage by cryptochrome and HERC2 ubiquitin ligase". Proceedings of the National Academy of Sciences, 107 (11), 4890-4895 DOI: 10.1073/pnas.0915085107
Full Disclosure: I have previously collaborated with Aziz and his group on a research project on eukaryotic cryptochromes.... Read more »
Kang, T., Lindsey-Boltz, L., Reardon, J., & Sancar, A. (2010) Circadian control of XPA and excision repair of cisplatin-DNA damage by cryptochrome and HERC2 ubiquitin ligase. Proceedings of the National Academy of Sciences, 107(11), 4890-4895. DOI: 10.1073/pnas.0915085107
by Michael Clarkson in Conformational Flux
A protein has several different levels of structure. The primary structure is the arrangements of atoms and bonds, and it is formed in the ribosome by the assembly of amino acids as directed by an RNA template. The secondary structure is the local topology, the helices and strands, and this forms mostly because of the release of energy through the formation of hydrogen bonds. The tertiary structure is the actual fold of the protein, the way helices, strands, and loops are arranged in space. The fold forms primarily because of the favorable entropy of burying the protein's hydrophobic groups where water cannot access them, analogous to the formation of an oil droplet in water. This suggests that, in addition to the well-known phenomenon of proteins denaturing, or losing their higher-order structure, under conditions of high heat, proteins might also denature when they get too cold.
As you might remember from your chemistry classes, the change in free energy due to a reaction under conditions of constant pressure is given by:ΔG = ΔH - T ΔSWhere ΔH is the change in enthalpy (i.e. the heat released or absorbed by a reaction), ΔS is the change in entropy, and T is the temperature of the system in Kelvin. Here, the change we are talking about is the transition from the folded state to some unfolded state. Simplistically, since the entropic contribution is scaled by the temperature, one can imagine that for a reaction with favorable entropy and unfavorable enthalpy, lowering the temperature could cause the reaction to reverse. Protein folding is only marginally favorable at biological temperatures, so one could easily imagine that lowering the temperature enough could cause a protein to prefer the unfolded state.
Of course, this is an oversimplification: the entropy and enthalpy of a particular protein state do not remain constant over all temperatures. Rather, they vary in a way determined by the heat capacity (Cp), such that ΔG as a function of temperature is (1):ΔG(T) = ΔH(Tr) + ΔCp(T-Tr) - T [ΔS(Tr) + ΔCp ln(T/Tr)]Where Tr is some reference state at which the thermodynamic parameters have been determined, and ΔCp is defined with respect to the native (folded) state. Because the various states of the protein have different Cp (unfolded chains typically have higher Cp), at certain temperatures above and below the biological optimum we can expect proteins to lose their higher levels of structure. Even this is still an oversimplification, of course, because it does not directly account for changes in water structure and cosolute properties with temperature. These features may cause ΔCp itself to vary with temperature rather than remain constant.
Unfortunately, for most proteins the temperature that favors unfolding lies below the freezing point of water, which makes this phenomenon difficult to study unless you do something unusual to your system. In 2004, Babu et al. (1) reported results from experiments that used reverse micelles to study the denaturation of ubiquitin at temperatures below freezing. By encapsulating a protein-water droplet in inverted micelles dissolved in pentane, it was possible to reduce the temperature to 243 K without causing freezing. These micelles also had the convenient property of tumbling quickly in the pentane, which allowed for reasonable NMR spectra even at these low temperatures. The appearance of the spectra they obtained indicated that the protein underwent a slow unfolding process with many different unfolded states, and also that the protein did not unfold in a cooperative fashion. Rather, it appeared that one contiguous region of the protein unfolded while the rest remained folded (the main helix was particularly stable).
This wasn't expected, because ubiquitin apparently unfolds in a completely two-state manner when overheated. This being the case, what's expected is for the protein to either be all folded or all unfolded, not some mixture of the two. However, cold does not affect all intramolecular contacts the same way. Lowering the temperature is expected to make hydrophobic interactions less favorable while not significantly affecting polar interactions like hydrogen bonds. This being the case, one might expect an α-helix to persist through a cold-denaturation transition, as happens in this case.
Something similar is observed in an upcoming paper in JACS from the Raleigh and Eliezer Labs (2), which approaches cold denaturation using a mutant form of the C-terminal domain of ribosomal protein L9. An isoleucine to alanine mutation at residue 98 of this domain doesn't appear to significantly alter the structure, but it causes the protein to denature somewhere in the high teens. At 12 °C the unfolded state is about 80% of the visible population, and this is where Shan et al. performed their NMR experiments. They assigned the unfolded state using standard techniques and then decided to see what they could learn from the chemical shifts.
As I've mentioned before, the chemical shift of a nucleus depends on the probability distribution of the surrounding electrons, and therefore is sensitive to the strength, composition, and angles of the atom's chemical bonds. Because the dihedral angles of the protein backbone are a good proxy for the secondary structure, one can use the chemical shifts of particular atoms to determine whether a given residue is in a helix or strand. When they performed this analysis, Shan et al. noticed two major differences between the native and cold-denatured states of the protein. The first was that the helix and strand propensities of the denatured protein were much lower than the folded form, as expected. In addition, however, they noticed that one loop of the protein had gained α-helical character. That is, it seemed like an α-helix had actually gotten longer as a result of the unfolding.
This doesn't mean that denaturing the protein added secondary structure. The low values in the output from the algorithm Shan et al. used suggest that the secondary structure in this denatured state forms only transiently. However, the chemical shifts suggest, and other structural data appear to confirm, that this region of the protein has an increased propensity to inhabit a helical structure as a consequence of the unfolding.
These results emphasize the fact that the "unfolded state" isn't as simple as it's often described. Residual structure persists in unfolded states of many proteins, and unfolded ensembles of one protein generated through different means (heat, cold, pH, cosolutes) may not resemble each other. Unlike unfolding at high temperature, cold denaturation of ubiquitin appears to be non-cooperative. In both ubiquitin and L9, it appears that helices are robust to the unfolding process, persisting and even propagating as the protein denatures. While some of these features may be held in common between different kinds of denatured states, others may be unique to particular denaturation conditions. The lingering question is which of these unfolded ensembles best resembles the denatured state that exists under biological conditions, giving rise to misfolded states and their associated diseases.
(1) Babu, C., Hilser, V., & Wand, A. (2004). Direct access to the cooperative substructure of proteins and the protein ensemble via cold denaturation Nature Structural & Molecular Biology, 11 (4), 352-357 DOI: 10.1038/nsmb739
(2) Shan, B., McClendon, S., Rospigliosi, C., Eliezer, D., & Raleigh, D. (2010). The Cold Denatured State of the C-terminal Domain of Protein L9 Is Compact... Read more »
Babu, C., Hilser, V., & Wand, A. (2004) Direct access to the cooperative substructure of proteins and the protein ensemble via cold denaturation. Nature Structural , 11(4), 352-357. DOI: 10.1038/nsmb739
Shan, B., McClendon, S., Rospigliosi, C., Eliezer, D., & Raleigh, D. (2010) The Cold Denatured State of the C-terminal Domain of Protein L9 Is Compact and Contains Both Native and Non-native Structure. Journal of the American Chemical Society, 2147483647. DOI: 10.1021/ja908104s
by Michael Clarkson in Conformational Flux
The proposition that general fold architecture is preserved within a family of evolutionarily-related proteins is not controversial. The amino acid sequence of a protein determines its structure, and countless studies have substantiated the idea that proteins with similar sequences will adopt similar folded conformations. Because structure and dynamics are intrinsically linked, one could reasonably assume that many features of a protein's dynamics get conserved along with the fold. A growing number of experiments show that this is indeed the case, including a recent paper in Structure (1).
We already have some evidence of fold-dependent dynamics. An NMR study from my mentor Andrew Lee's lab comparing fast fluctuations of side chains among three related proteins from the PDZ family suggested that motions on this timescale could be evolutionarily conserved (2). That study compared the model-free order parameters of methyl groups from one protein to those of their counterparts in other PDZ domains. Predicting an order parameter using dynamics data from a structurally equivalent residue in another protein was shown to be slightly more accurate than calculations from structural considerations such as packing or methyl type. In a similar vein, I have previously discussed studies on adenylate kinase enzymes from E. coli and a thermophilic organism that show they have similar backbone dynamics under conditions where their enzymatic activity is about equal, although they differ substantially from each other at room temperature.
Of course, these studies were limited and involved just a few proteins, because getting experimental data about dynamics is costly and time-consuming. For comparisons across large numbers of different proteins, computational approaches may therefore be of great value. Previously, other groups have made use of short molecular dynamics simulations or normal mode analysis. Raimondi et al. continue in this vein, combining normal-mode analysis of single structures with principal component analysis of a large set of structures from the Ras superfamily of proteins.
The Ras superfamily encompasses several groups of related folds with nucleotide-dependent activity. When GTP is bound to them, they are active and propagate a particular signal. Over time, the GTP gets hydrolyzed to GDP and the signal turns off. This catalytic process is pretty inefficient, but it can be enhanced by the action of a GTPase Activating Protein (GAP). The exchange of GDP for GTP can be enhanced by the action of a Guanine nucleotide Exchange Factor (GEF). The GTP/GDP state manifests primarily in the positioning of two loops, termed the switch regions (SwI and SwII). This mechanism allows for several different modes of control, so the Ras architecture has been repurposed many times throughout evolution for a variety of different roles.
Because the different members of the superfamily play key roles in their respective pathways, there are many structures available, often in several different states (GTP-bound, GDP-bound, GEF-bound, etc.). Raimondi et al. aligned these structures using the common features of the Ras fold and used PCA to identify flexibility across this evolutionary ensemble. The goal of PCA is to take a dataset with many potentially correlated data points (in this case, the relative positions of the backbone Cα atoms) and identify a small set of variables that explain as much of the variance as possible. Here, the principal components (PC) are expected to describe the structural variability of the fold.
The first PC, which is expected to explain the largest amount of the variability, can separate the structures by their families. That is, the displacement along PC1 can distinguish a Rho family domain from an Arf family domain. The authors call this variability function-independent, because this principal component doesn't seem to make any meaningful distinction between the GTP/active and GDP/inactive states. That appears to be a property of the second PC, which for some families does a very good job of separating the GTP from the GDP-bound forms (for others there appears to be more mixing). According to this analysis, function-dependent variability appears to be confined to one half of the protein, while function-independent variability seems to be distributed across the whole fold.
The authors also performed normal mode analysis on individual proteins from the Ras superfamily using an elastic network model. In this kind of simulation the protein is modeled as a group of Cα "nodes" connected by spring-like harmonic potentials representing covalent and non-covalent interactions. Although any one of these "bonds" can be stretched, compressed, and moved, such deformations exert a force on other bonds connected to the nodes involved, which tends to damp most motions. Certain collective deformations will be favored as a result, and these can be calculated as "normal modes" that probably reflect slow fluctuations of the fold.
The deformations detected by ENM for all individual proteins overlapped significantly with the second PC identified in the evolutionary analysis. That is, the conformational variability of a conserved domain over evolutionary time is correlated with the conformational fluctuations of a single domain on a biological time scale. This makes sense, especially in this case, because the switch regions are areas of significant conformational variability, and are connected with the conserved catalytic function of these proteins. The fact that PC1 doesn't line up with the low-frequency normal modes probably means that the conformational transitions between different family members cannot be mimicked by ordinary thermal motion, i.e. the fold cannot change this way without the aid of mutations.
Although the results in these studies might seem rather pedestrian and expected, I find them quite encouraging. We're not particularly good at predicting structure from sequence yet, and our understanding of protein dynamics is even more primitive. What these studies indicate is that it should be possible to predict the conformational fluctuations of a given protein or domain using our knowledge of a related, homologous protein. This could have positive consequences for fields such as rational drug design and protein design, which have met with limited success in part, perhaps, because they do not sufficiently account for a protein's structural fluctuations.
(1) Raimondi, F., Orozco, M., & Fanelli, F. (2010). Deciphering the Deformation Modes Associated with Function Retention and Specialization in Members of the Ras Superfamily. Structure, 18 (3), 402-414 DOI: 10.1016/j.str.2009.12.015
(2) Law, A., Fuentes, E., & Lee, A. (2009). Conservation of Side-Chain Dynamics Within a Protein Family. Journal of the American Chemical Society, 131 (18), 6322-6323 DOI: 10.1021/ja809915a... Read more »
Raimondi, F., Orozco, M., & Fanelli, F. (2010) Deciphering the Deformation Modes Associated with Function Retention and Specialization in Members of the Ras Superfamily. Structure, 18(3), 402-414. DOI: 10.1016/j.str.2009.12.015
Law, A., Fuentes, E., & Lee, A. (2009) Conservation of Side-Chain Dynamics Within a Protein Family. Journal of the American Chemical Society, 131(18), 6322-6323. DOI: 10.1021/ja809915a
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