Jun 022009
 
ResearchBlogging.orgVaccination plays such an important role in our seasonal influenza strategy in part because we don’t have many medicines that can be brought to bear on the disease. The neuraminidase inhibitors (specifically Tamiflu) are widely stockpiled, and continue to work for now, but the specter of resistance is already lurking. If these drugs are too widely or too improperly used, there is a good chance that resistance mutations will eventually render these drugs ineffective. Universal drug resistance may already be the fate of the drugs amantadine and rimantadine, built on an adamantane backbone (1). The adamantane drugs inhibit the M2 proton channel from influenza A, a tiny tetrameric protein that equalizes pH between the virus and the endosome of the cell that has swallowed it. This process releases the virus contents so that they can do their damage to the cell, so these medicines can significantly retard the infection process. Or rather, they could, if so many influenza strains didn’t harbor the S31N mutation that almost completely nullifies their effect. If we are to develop new drugs to attack the M2 channel, it would be helpful to know how this mutation causes drug resistance. Over the past few years a great deal of structural evidence has accumulated showing how adamantane drugs work on the older, non-resistant channels. The problem is that the evidence supports two different models of M2 inhibition, and so far it has proven difficult to determine which of them is probably correct.

How the question arose

The controversy is the result of two structures published in Nature early in 2008 (2,3). The first of these is a crystal structure of a tetramer of peptides encompassing the transmembrane (TM) region of the M2 channel reported by the DeGrado group at UPenn, which you can see at right (explore this structure at the PDB, noting that the numbering is off by 21). In the detergent used for crystallization, the peptides form a tetramer with a roughly conical pore, which amantadine (purple in these models) physically occludes, giving rise to the pore-blocking model (PBM). This model is consistent with previous results indicating that a single amantadine molecule is sufficient to inhibit the proton channel. In addition, in this model the drug binding site is adjacent to S31 (blue side chain), which is what we’d expect given that an S31N mutation is responsible for most amantadine resistance. The authors propose, given the position of the S31 side chain, that the mutant asparagines form a hydrogen-bonded network that is too constricted for amantadine to bind. Click on the picture for a larger view.

An alternative model was proposed by Schnell and Chou from Harvard University (3). They produced an NMR structure (left) of a 42 amino-acid peptide from M2 encompassing the TM region and an additional C-terminal helix (explore this structure at the PDB). In their structure, taken at pH 7.5 in detergent micelles, the tetramer forms a roughly cylindrical pore that is blocked by the side chains of the known gating residues W41 and H37 (light green in these models). Their structure shows rimantadine bound at four sites near the base of the helix but not in the pore. Using pH-dependent conformational exchange experiments, Schnell and Chou showed that a decrease in pH caused rapid structural changes in the channel, motions that rimantadine slowed. On the basis of this evidence, they proposed a mechanism in which protonation of the gating histidines destabilizes the packing of the TM helices and allows the conductance of protons. Rimantadine blocks the channel by stabilizing the helices, thus this is a dynamic quenching model (DQM). The position of S31 in this model is also somewhat different than the crystal structure, although these models were made at different pH conditions and so this may represent a difference between the closed and open states of the channel.

The distinction here is important. If Stouffer et al. are correct, then drug development should abandon the adamantane backbone altogether and start with a set of significantly different leads to address the resistance problem. The PBM implies that any molecule large enough to occlude the pore will be too large to fit in there following the S31N mutation that induces amantadine resistance. If the DQM is correct, however, then it is conceivable that further refinements to the adamantane base, or similar molecules, could improve affinity enough to overwhelm the mutational effect.

Unfortunately, neither result is unimpeachable. Although it agrees with a great deal of experimental evidence, the low resolution of the crystal structure means that the electron density called amantadine cannot be assigned unambiguously. It is also curious that a hydrophobic molecule like amantadine would bind tightly in the hydrophilic pore. In addition, the crystal form with amantadine bound contains a mutation, G34A (black side chain), which is near the drug binding site and could conceivably have altered the binding specificity of the protein.

The NMR structure has the advantage that it directly includes distance information in the form of NOEs. However, the authors used 40 mM rimantadine to obtain these results, meaning that there were as many rimantadine molecules in the solution as phosphate buffer molecules. Under these conditions, it is possible that the drug bound to a secondary, low-affinity site. Even if this is what happened, it is strange that the rimantadine never bound to the high-affinity site indicated by the crystal structure.

Both experiments use significantly truncated constructs and highly artificial systems to mimic a membrane environment. The structure of any membrane protein depends in often unexpected ways on the composition of the lipid bilayer in which it is embedded and on the structure of that bilayer. The intense curvature of the micelles may have distorted the structure in the NMR experiment, and possibly inappropriate lipids may have had effects on both structures. We know these considerations are relevant for this system, because Schnell and Chou report that the construct used for the crystal structure would not form stable tetramers in the micelle system. Also, as Chris Miller notes in his commentary on these papers (4), there were questions about both constructs with respect to their proton conductivity. Lacking significant stretches of the protein and placed in these environments, it is possible that both structures deviate from in vivo reality in significant ways.

Because the conditions diverge so much, it is difficult to weigh the mechanisms based on these structures alone. The binding site identified by Schnell and Chou is only at the very end of the construct used by Stouffer et al.. In addition, the inhibited crystal structure comes from a low-pH condition while the NMR structure exclusively represents a high-pH condition. Given these differences in conditions, it is not impossible that both models, in whole or in part, are correct. We must turn to additional experiments and alternative evidence to choose between them, specifically data on the stoichiometry of binding and the effects of mutations.

Binding stoichiometry

The crystal structure shows a single binding site for the drug, while the NMR structure implies four, and this is at odds with existing results that indicate that a single molecule of drug is sufficient to inhibit a single channel. Given the homotetrameric nature of the M2 channel, it is in principle not possible for the NMR experiment to distinguish between a single rimantadine binding event and four. That is, the NMR experiment cannot tell us whether the rimantadine-M2 inhibition occurs with a single binding event or requires four drug molecules to bind. Therefore, to argue that DQM is inconsistent with 1:1 stoichiometry overstates the case somewhat.

It may also be somewhat overstating the case to say that there is only one amantadine binding site on M2. Washing amantadine out of your buffer does not reverse inhibition, in part because of slow kinetics of leaving the binding site and in part because these drugs, being very greasy, preferentially partition into the lipid membranes and are therefore not readily removed from a system when its aqueous phase is replaced. It is difficult to measure a binding constant for the drugs because the equilibria under consideration will be quite complex. The studies often cited on the 1:1 stoichiometry (5,6) use structural and kinetic evidence to get at this question.

Czabotar et al. (5) measured tryptophan fluorescence in M2 as a function of pH and rimantadine concentration. They found that fluorescence from W41 was quenched by decreased pH, but recovered when 1 equivalent rimantadine per tetramer was added. This result implies that structural or dynamic changes caused by histidine protonation are reversed by rimantadine inhibition, but this is so general that it cannot be taken to support either the PBM or DQM.

Wang et al. (6) measured the reduction of surface currents in X. laevis oocytes after addition of various concentrations of amantadine. From these results they are able to construct a Hill plot with a coefficient of 1, showing that binding of amantadine is not cooperative. In further results, Wang et al. find that amantadine inhibits M2 channels slightly better at high pH (when the pore is closed) than at low pH, and that amantadine inhibits proton conductance in either direction (rather than favoring one). Both these outcomes are unexpected for PBM, but can be easily explained by DQM. However, the differences in the binding constants are relatively minor and the linearity of the current-voltage relationship may result from some other idiosyncratic feature of the M2 channel, so these results are not unequivocal.

Neither experiment refutes DQM because they do not measure the number of binding sites, but rather the number of efficacious binding sites. If there are four binding sites, but 95% or more of the inhibitory or structural effect is caused by the first drug molecule bound, then these experiments would be unable to distinguish DQM from PBM. Overall, the evidence on the question of binding stoichiometry does not eliminate the possibility of four binding sites existing, but it does place a requirement on DQM that the inhibitory effect of amantadine on the tetramer result from a single binding event. Because the proposed DQM binding site for rimantidine lies between monomers and is linked to the gating tryptophan, this is not unbelievable. Other evidence from these experiments is equivocal, but can be seen as somewhat more problematic for PBM than DQM.

Functional effects of mutations

A serious problem for DQM is that the mutations known to give M2 resistance to adamantane drugs are all located near the PBM binding site. In particular, S31 is adjacent to the drug in the crystal structure and quite distant in the NMR structure. As Miller notes in his commentary, mutational studies are substantially more difficult to interpret than is typically suggested, so this isn’t absolutely probative. In general, however, one predicts mutations to have short-range rather than long-range effects, so at least some resistance mutations ought to evolve at the binding site. However, many of the residues surrounding the DQM site are almost absolutely conserved, presumably because they are essential to the function of the channel. As a result, it would be very difficult to interpret any studies on point mutants in this area. What would be ideal, however, would be to find a set of mutations that produced a functional protein and abrogated amantadine inhibition.

This is the basis for an interesting experiment conducted by the lab of Robert Lamb and reported last year in PNAS (7). In this case, the authors took advantage of the fact that the M2 protein from influenza B virus is not sensitive to adamantane drugs. They constructed a chimeric protein containing about a dozen residues from influenza A M2 — specifically, the dozen or so residues surrounding the PBM site. If PBM is correct, then we would expect that these residues, which define that site, would impart amantadine susceptibility to the influenza B channel. This is what happens, sort of. For your benefit, I have shamelessly stolen their figure (right), but you can check out this paper yourself because it is open access. In this assay, again involving X. laevis oocytes, the hybrid channel is sensitive to amantadine (bottom trace), but only half as sensitive as the wild-type influenza A channel (second from top). This result suggests that there is important context conferring susceptibility outside the PBM site. However, this could be something as simple as helix orientation, so the result does not necessarily imply that there is an external binding site.

Additionally, the authors made point mutations at residues (L38, D44, and R45) that were presumed to be important in the DQM mechanism or have long-range effects on amantadine binding. None of these mutations appeared to affect amantadine resistance. In contrast, experiments in liposomes reported by the Chou group this May showed that a D44A mutation prevented rimantidine from having an effect (8). This conflict in results is difficult to reconcile, but may result from the different constructs used (the Chou group used a truncated form of M2 while the Lamb group used the full-length protein) or from changes in ion specificity caused by the D44A mutation. It might be of value to repeat these experiments with the alternative construct: truncated in oocytes, full-length in liposomes. Because the D44A mutant does not appear to conduct protons as efficiently as WT, the proposition that the function of this mutant is too deranged to provide trustworthy information should also be considered.

Additional experiments in the Chou paper are meant to address the relationship between the DQM site and the mutations at the PBM site. They show that the S31N mutation prevents rimantidine binding to the remote site, and also that this mutation makes the protein generally more dynamic. From this evidence they propose that this mutation, at least, disrupts amantadine binding by destabilizing the helical packing of the channel and thus interfering with the organization of the lipid-facing pocket.

They also examine an S31A mutation and find that it is not rimantadine-resistant or destabilizing to the packing. This supports their dynamic model in a limited way, because it demonstrates that only certain mutations at the S31 site will generate resistance. It does not cast any doubt on PBM, however, because in that model resistance in the S31N mutant is explained by the idea that its side chain will partially obstruct the pore so that rimantadine will not fit. I do not think it was ever proposed that specific contacts between S31 and the drug stabilize the binding; in fact, the general absence of such contacts strikes me as a concern about PBM.

Chou et al. also examine the effect of rimantadine on the shorter construct used for the crystal studies. They find that the inhibition of this construct is substantially weaker. However, it also conducts protons at a much slower rate in this assay, suggesting that there may be additional serious problems with the function of this construct. It may be that it simply is not appropriate to use this construct for studies in solution or living membranes. That doesn’t necessarily imply that this peptide will give incorrect information in the stabilizing environment of a crystal.

What do we know, and what do we need?

Very little of this evidence unequivocally prefers one model to the other. We know that a single adamantane molecule is sufficient to inhibit M2, and while this is most obviously compatible with PBM it need not be inconsistent with DQM. It is also apparent that various constructs of the M2 channel retain adamantane susceptibility after ablation of the DQM site, either by truncation, mutation, or the construction of a chimeric protein. In all assays, however, the adamantane drugs lose a considerable amount of inhibitory power, so these results are not entirely consistent with PBM either. And, at least in the Chou lab’s assays, interference with the DQM site also reduces adamantane susceptibility and deranges function. Moreover, the NMR data from the Chou lab shows that mutations at PBM site have a long range effect on the DQM site, which mitigates the probative power of the S31N mutation.

How do we address this question? One important step would be to start comparing like to like. We are considering evidence from a plethora of constructs and conditions, and the evidence in conflict is often collected in very divergent experiments. Ideally we would like to have structures of the wild-type channel at low and high pH in a lipid environment that closely mimics the composition and curvature of a mature influenza virion. As this is unlikely in the near term, we must hope for NMR and crystal structures that at least use the same construct, minimally mutated, under similar conditions. NMR studies at low pH would be of value in assessing whether these studies in fact contradict one another. Additionally, it would be useful to make adamantane derivatives labeled with a free radical or other paramagnetic label; this would presumably allow the identification of a binding site at lower drug concentrations in an NMR experiment. Labeling the drug with a metal might also allow its identification in a crystal structure without any need to push the resolution significantly higher. Finally, actual structures of the S31N mutant, positively identifying the disposition of this side chain, would be of great value in judging the question.

Structural experiments can take a great deal of time and careful tuning, a requirement exacerbated by the often-fickle behavior of membrane proteins. As such, additional mutational studies could prove useful. Inverting the chimera experiment of Jing et al. to create a chimeric protein with the upper channel from influenza B and the lower channel from influenza A may be a helpful supplement to the existing experiments. If the C-terminal portion of the channel makes a contribution to adamantane inhibition this chimera will also be rimantidine-sensitive. In addition, new mutations at S31 could help distinguish the possibilities. The PBM supposes that the N31 side chains stick into the pore and form hydrogen bonds, while the DQM supposes that they stick into the interface of the TM helices and destabilize them. An S31L mutant should disrupt the helical packing but not form hydrogen bonds or extend the L31 side chains into the pore. If functional, such a mutant ought to be rimantidine resistant if the DQM is correct, but not if PBM is correct. Assuming the geometry of the longer side chain is wrong for formation of a hydrogen bonding network, an S31Q mutation might be useful as well. Similarly, mutations that increase the size of the L40, I42, or L43 side chains could prevent adamantane binding to the DQM site without degrading the channel’s transport capabilities; the drug sensitivity of such a mutant would be a powerful argument either way. Any experiments of this kind would likely be easier to perform than to interpret, but could provide valuable insight. Obviously, it would also be important to establish that each mutant was competent at transporting protons.

The unspoken assumption of the debate so far is that these mechanisms are mutually exclusive, but there is no particular reason to believe this must be so. The structural experiments definitively show that binding to both sites is at least possible — even if one clings tenaciously to the idea that the density observed in the crystal is not in fact amantadine, that structure at least shows that the PBM site is capable of accommodating the drug. It might therefore be plausible that adamantane drugs inhibit M2 using both mechanisms simultaneously, or that DQM predominates at high pH and PBM at low pH. Redundancy in inhibitory mechanisms may explain the curious features of amantadine inhibition noted by Wang et al., and the inability of experiments specific to a single site to completely account for adamantane inhibition. In addition, the fact that S31N interferes with both mechanisms may explain why it is the primary resistance mutation.

An experiment with the alternate chimera mentioned above could test this possibility. In addition, if the mechanisms switch off in a pH-dependent fashion, then this should be testable with the hybrids: specifically, the A/B M2 used by Jing et al. should have lower susceptibility to adamantane drugs at high pH than at low pH. Similarly, the B/A M2 chimeric protein, if inhibited by amantadine, would be more resistant at low pH.

Doubtless these suggestions are nothing new to the members of the labs working on this perhaps unexpectedly hairy question. Membrane protein structure and function is one of the most difficult experimental subjects in biochemistry, and constitutes a critically important frontier in scientific efforts to improve human health. It is infinitely easier to propose most of these experiments than it is to perform them, and I would be remiss if I did not temper the persistently critical tone of this post with some praise for the efforts of all the scientists involved in this research, and for their commitment to getting the right answer. These papers represent years of work by incredibly talented people using some of mankind’s most advanced scientific techniques. The lack of clarity on the question of adamantane drugs binding to M2, even in the face of this amazing effort, is a testament to the enormous difficulty of researching these critical systems.


1. Deyde, V., Xu, X., Bright, R., Shaw, M., Smith, C., Zhang, Y., Shu, Y., Gubareva, L., Cox, N., & Klimov, A. (2007). Surveillance of Resistance to Adamantanes among Influenza A(H3N2) and A(H1N1) Viruses Isolated Worldwide The Journal of Infectious Diseases, 196 (2), 249-257 DOI: 10.1086/518936 OPEN ACCESS

2. Stouffer, A., Acharya, R., Salom, D., Levine, A., Di Costanzo, L., Soto, C., Tereshko, V., Nanda, V., Stayrook, S., & DeGrado, W. (2008). Structural basis for the function and inhibition of an influenza virus proton channel Nature, 451 (7178), 596-599 DOI: 10.1038/nature06528

3. Schnell, J., & Chou, J. (2008). Structure and mechanism of the M2 proton channel of influenza A virus Nature, 451 (7178), 591-595 DOI: 10.1038/nature06531

4. Miller, C. (2008). Ion channels: Coughing up flu’s proton channels Nature, 451 (7178), 532-533 DOI: 10.1038/451532a

5. Czabotar, P., Martin, S.R., & Hay, A.J. (2004). Studies of structural changes in the M2 proton channel of influenza A virus by tryptophan fluorescence Virus Research, 99 (1), 57-61 DOI: 10.1016/j.virusres.2003.10.004

6. Wang, C., Takeuchi, K., Pinto, L.H., & Lamb, R. (1993) Ion Channel Activity of the Influenza A Virus M2 Protein: Characterization of the Amantadine Block J. Virol. 67 (9) 5585-5594 Available free from PubMed Central

7. Jing, X., Ma, C., Ohigashi, Y., Oliveira, F., Jardetzky, T., Pinto, L., & Lamb, R. (2008). Functional studies indicate amantadine binds to the pore of the influenza A virus M2 proton-selective ion channel Proceedings of the National Academy of Sciences of the United States of America, 105 (31), 10967-10972 DOI: 10.1073/pnas.0804958105 OPEN ACCESS

8. Pielak, R., Schnell, J., & Chou, J. (2009). Mechanism of drug inhibition and drug resistance of influenza A M2 channel Proceedings of the National Academy of Sciences of the United States of America, 106 (18), 7379-7384 DOI: 10.1073/pnas.0902548106

The Scientific Activist and Discovering Biology in a Digital World also have interesting posts on this subject.

May 012009
 
ResearchBlogging.orgThe catabolite activator protein (CAP), which plays a significant role in telling bacterial metabolism to digest sugars other than glucose, is a classic example of allosteric activation. Binding of the small signaling molecule cyclic AMP (cAMP) switches CAP into an active state that recruits RNA polymerase to certain metabolic genes. The biochemistry of cAMP activation is well understood, but the structural basis is not as clear, because a structure of the inactive protein was not available. This week in PNAS, researchers from Rutgers University and the University of Wisconsin-Madison report a structure of the free state of CAP that illuminates this allosteric effect.

Many excellent structural studies have examined CAP in its activated and DNA-bound form. CAP is a dimer, and each monomer has two domains: a DNA-binding domain (DBD) that recognizes its specific sequence, and a cAMP-binding domain (CBD). The monomers bind to each other through a coiled-coil interaction between two long helices. When CAP is activated it binds to DNA, with two helices (the recognition helices) sliding into the major groove and specifically identifying the sequences to which it should recruit the transcription apparatus. Without cAMP bound, CAP can still interact with DNA, but this interaction is of low affinity and not specific for any particular sequence. There are a number of ways this could conceivably happen, but it’s difficult to be certain about any model in the absence of a structure of the free (apo-) protein.

In order to determine the structure, Popovych et al. used NMR. The 50 kDa size of the dimer means that it requires some extra effort for NMR work, but it is still well within the capabilities of the technique. The fact that the protein is a symmetric homodimer makes assigning the spectra somewhat easier, as the researcher only needs to deal with 209 residues rather than 418. The authors determined the structure using short-range distance restraints from nOe experiments, long-range restraints from paramagnetic relaxation enhancement, and angular restraints from residual dipolar couplings (RDCs). These angular restraints allowed the authors to unambiguously determine the relative orientation of the DBD and CBD in each monomer.

Getting that orientation right is key to the story here, as you can see from the image to the left. Here I’m showing you the DBD and coiled-coil helix (lower left) of a single monomer in the two different states. The activated CAP is in green (PDB code: 1G6N, and the apo- structure is in red (PDB code: 2WC2). You’re looking down the coiled-coil, and the recognition helix is in a brighter color right at the front. If you superpose these structures on the bottom end of the coiled-coil, you can see that the recognition helix is rotated by 60° when cAMP binds. This twist of the DNA binding domain gives the recognition helices the right orientation and spacing to slide into the major groove of DNA and identify genes to activate. In the apo- state, these helices cannot both fit into the major groove simultaneously, explaining the low affinity and lack of specificity in that state.

Although the DBDs undergo a radical change in position following cAMP binding, they don’t actually have any direct interactions with the signaling molecule, which binds down in the CBD near the coiled-coil helix. This helix, which links the CBD to the DBD, turns out to be key to communicating the allosteric signal. In the apo- state, the top part of this helix (near the DBD) is actually somewhat disordered and loop-like, not helical. Binding of cAMP to the CBD forms several contacts and causes several structural shifts that result in the formation of regular helical structure at the top of the coiled-coil. This in turn swings the DBDs around so that the recognition helices are in position to interact with target sequences (the authors provide a short movie of this in the Supplementary Information). A similar molecule, cGMP, that does not activate CAP, fails to make the key contacts with T127 and S128 that mediate this structural change.

The fact that the upper part of the coiled-coil is unstructured suggests that CAP may sample a range of conformations in the apo- state. This possibility is supported by one of the mutational studies in the paper. As you can see from Figure 5, a G141S mutation and binding of various effectors to the mutant causes the NMR resonances of DBD residues to shift on a line between the WT apo- and WT cAMP-bound states. This, in conjunction with the broadening of those intermediate peaks, suggests that the DBDs are exchanging between the two states on a timescale of microseconds. It seems quite likely that one or both DBDs in the inactive dimer occasionally samples the active conformation. In this model, the function of cAMP would be to stabilize, rather than enable the active conformation. The negative cooperativity of cAMP binding may help keep CAP switched “off” in the face of this conformational heterogeneity.

This study only dealt with a single protein, but the results are likely to be applicable to a number of systems. The allosteric mechanism described here seems to fit observations in at least some other members of the protein family to which CAP belongs. As such, this structural work and the dynamics investigations that will probably ensue are likely to provide important insights into a number of regulatory pathways in bacteria.

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

 Posted by at 3:00 AM
Mar 102009
 
ResearchBlogging.orgIn a post last week I mentioned a technique for obtaining the high-resolution structure of a protein inside a living cell, but I also pointed out that this technique was difficult and expensive, and might not be applicable to large proteins. Techniques improve and become more powerful, of course, but you might not want to wait for NMR to catch up to your question. Fortunately, high-resolution in vivo structures may not be necessary if you already have relevant dilute-solution structures of your protein and merely want to distinguish between different known conformational states. In a recent paper in PNAS, researchers from San Francisco used conformation-specific antibodies to locate activated caspase-1 in cultured cells.

Caspase-1 is a cysteine protease that plays a role in the immune response, as well as being released during apoptosis. From crystal structures we know that this protein can adopt two different structures, of which only one represents a catalytically competent state of the enzyme (the on-form). Caspase-1 also possesses an allosteric site where an inhibitor can bind, locking the enzyme in an inactive conformation (the off-form). When it’s not bound to anything (the apo-form) caspase-1 is presumed to have a conformation similar to the off-form. Like many proteases, caspase-1 has a large, inactivating tail when it is made (the pro-form) that must be cleaved off before activation is possible. The structure of the caspase-1 proenzyme is not known. Current models of inflammatory response propose that after processing, the on-form binds to scaffolding proteins in an “inflammasome”. In order to confirm this proposition, the authors decided to generate antibodies that would bind specifically to the on-form or the off-form of caspase-1.

The key to this experiment was combining irreversible inhibitors that could essentially lock the caspase into one conformation with the phage-display technique for optimizing antibody recognition. The authors had the advantage that both the active site and the allosteric site have cysteines in them. In an oxidizing environment, small molecules can covalently bind to the protein via disulfide bonds, thus locking the enzyme into the on-form or off-form. The authors immobilized these “locked” forms of caspase-1 and used them to screen antibody fragments (Fabs) using phage display. In addition to the typical selection approach, the authors performed anti-selection at one point using the “wrong” conformation to increase the specificity. After several rounds of selection, and some controls to ensure that the antibodies were binding to caspase and not the inhibitors, Gao et al. had several candidates for further optimization and screening. After they completed that process, they had two antibodies, Fabon and Faboff, specific for the two conformations. Each antibody bound to its intended target with a KD of less than 5 nM. The authors also made full antibodies (IgGon and IgGoff) from these Fabs for expression in mammalian cells.

The authors took these new antibodies for a spin with the apo-form of caspase-1. One might naively expect that only Faboff would bind to this protein, but in fact Fabon bound as well, albeit with substantially reduced affinity relative to the on-form. One possible interpretation of this finding is that the apo-form is equivalent to the off-form, but that Fabon can convert it to the on-form via an induced-fit mechanism. If this is the case, then we would expect Faboff to have the same affinity for the apo-form as it has for the off-form. However, the authors find that Faboff has reduced affinity for the apo-form relative to the off-form. This indicates that the apo-form is an ensemble of conformational states, most of which more closely resemble the off-form than the on-form. Consistent with this view, the authors found that they can activate or inhibit apo-form activity by adding Fabon or Faboff, respectively.

By contrast, IgGon did not bind detectably to a model of the pro-form, suggesting that this form’s conformational ensemble contains no members that are close in structure to the active form. The weak affinity of IgGoff for the pro-form suggests that there are substantial differences between this conformation and the off-form as well.

At this point we know that IgGon will bind tightly to the on-form of caspase-1, weakly to the apo-form, but not to the pro-caspase. This means it will likely be an effective probe of active caspase-1 in cells. The authors performed this experiment in THP-1 cells that they differentiated into macrophages. While IgGoff produced diffuse fluorescence in these cells, IgGon stained small, concentrated bodies in a fraction of the cells. This suggests that active caspase-1 is localized to supramolecular structures in these cells, which the authors argue are identical to a structure previously identified as the “pyroptosome”.

Although this particular experiment took advantage of binding-site cysteines that are particular to caspase-1, it should be possible to extend this approach to other proteins. Even non-covalent inhibitors or activators should be useful in this approach as long as the concentration is held high enough to saturate the target site during the selection step. Of course, the conformational change must alter the structure enough that the antibodies have something to grasp — it may not be possible to get specific antibodies if the shift is too subtle. If this requirement is met, however, it should be possible to determine the distribution of specific conformational states in cells, or even (as the authors suggest) to use antibodies as activators or inhibitors in vivo.

J. Gao, S. S. Sidhu, J. A. Wells (2009). Two-state selection of conformation-specific antibodies Proceedings of the National Academy of Sciences, 106 (9), 3071-3076 DOI: 10.1073/pnas.0812952106

Feb 132009
 
ResearchBlogging.orgClassically, allosteric and cooperative effects have been identified with large complexes of multiple protein subunits, in which the binding of a ligand to one subunit enhances ligand binding in a different subunit. While some features of the models developed to deal with these systems do not translate well to cases of allostery within a single protein or domain, many of their core ideas continue to illuminate these single-subunit systems. In an upcoming paper in the Journal of the American Chemical Society, a team of European researchers examine an allosteric effect based on population shifts in a transcriptional activator, comparing it to a famous model for explaining allostery in hemoglobin (1).

The CREB binding protein (CBP) is a large molecular scaffold that brings pieces of the transcriptional machinery together in order to turn on a gene. Like many scaffold proteins it contains several protein-protein interaction domains linked together by large unfolded regions. One of these domains is KIX, a small bundle of helices that binds other proteins at two distinct sites. In one case, a protein called MLL binds to one site while a protein called c-Myb binds at the other. What is so interesting about this is that KIX is much more likely to bind c-Myb when it is already bound to MLL. Brüschweiler et al. used NMR techniques to try and understand how this happens.

In order to pull this off they performed relaxation-dispersion experiments on the amide nitrogen, α-carbon, and some methyl carbon atoms of the KIX domain bound to a peptide derived from MLL. Many of the amino acids in the protein showed a significant contribution to R2 from exchange, suggesting a global conformational switch between two states. In order to cover their bases, the authors performed experiments to prove that this behavior was not related to the unfolding of the protein. Satisfied that the protein was stable, they used standard methods to calculate the rate of the conformational change, the population of the two states, and the chemical shift difference between them. They found that the minor state of the KIX-MLL complex is 7% of the total population of protein molecules. They also noticed that the chemical shift difference between the two states correlates very well with the chemical shift difference between the KIX-MLL complex and the KIX-MLL-c-Myb complex. Assuming that the conformation of KIX is the primary determinant of chemical shift in the bound state, this suggests that the dynamics are sensing a switch between a state that doesn’t bind c-Myb and a state that does.

In order to determine whether MLL binding gave rise to this conformational switching behavior, the authors measured relaxation dispersion in KIX at several different concentrations of MLL. Excluding residues highly sensitive (by chemical shift) to MLL binding, they found that the exchange contribution to relaxation increases as MLL is added. Although Brüschweiler et al. were unable to fit this small number of residues quantitatively, these results strongly suggest that the addition of MLL increases the population of the c-Myb binding state. Moreover, under conditions where KIX forms a saturated complex with MLL and a peptide from another protein (pKID), the chemical exchange contribution to relaxation vanishes, suggesting that the protein has been pushed completely to the binding-competent state.

In order to identify the pathway by which the MLL binding site communicates to the c-Myb binding site, the authors examined the residues in KIX that had the largest chemical shift change associated with the chemical exchange behavior. As it happens, residues satisfying these criteria cluster in a region stretching from the MLL site to the c-Myb site, as you can see to the right (explore this structure at the PDB). Here, KIX is blue, the MLL peptide is red, and the c-Myb peptide is green. The side chains of the residues Brüschweiler et al. identify are shown as sticks inside the pink atomic surface. As you can see, these residues constitute a contiguous body stretching from one site to the other. Presumably, this set of residues provides a pathway for communication between the two sites. A trio of isoleucines at the core of this region (I 611, 660, and 657) are present in KIX domains from many different species (supporting information), suggesting that this communication pathway is evolutionarily conserved. Mutational studies centered on this trio of residues may teach us more about the mechanism of information flow in this domain.

Although this allosteric pathway is known to work in reverse (binding of c-Myb enhances the binding of MLL), the authors were unable to detect any exchange contribution to R2 when only c-Myb or pKID was bound. While this may suggest that communication in the opposite direction uses a completely different mechanism, such that KIX has two unidirectional allosteric pathways, that’s not a necessary conclusion from this result. Alteration of R2 due to conformational exchange is dependent on the populations of the two states, the difference in chemical shift between them, and the rate of the switch. Actually detecting a dispersion curve requires that all these parameters lie within a ‘sweet spot’ that allows observation. This doesn’t always happen, even when a dynamic process is occurring with a μs-ms rate. Because the chemical shift changes that result from MLL binding appear to be quite large (2) the exchange process may be slow on the NMR timescale.

One minor concern I have with the paper is that the experiments were carried out at a pH of 5.8, which is lower than the pH of cytosol (7.2). The only groups likely to change their charge over that range are histidines, but one of the key residues for this paper is H651 in the KIX domain. The experiments that established the allosteric effect of MLL on c-Myb binding (2) were performed at pH 7.0 so it is formally possible that the dynamics and allostery are a coincidence (although the chemical shift data argue against this). It would probably be worthwhile to perform HMQC experiments to clarify the protonation state of the histidine, or to repeat the binding experiments at a lower pH. The latter might be preferable; I assume that mildly acidic conditions are used for the NMR experiments because KIX has undesirable spectral characteristics nearer neutral pH. Additionally, it might be interesting to perform experiments that explore the effects MLL has on the kinetics of binding, seeing as this appears to be a dynamic process.

Brüschweiler et al. identify their results with the Monod-Wyman-Changeux model of allostery. Although this model was formally developed for systems with multiple subunits, what the authors really wish to emphasize is the idea from the MWC model that proteins in solution exist in an equilibrium of high-affinity and low-affinity forms. The evidence from the relaxation-dispersion experiments indicates that a very small proportion of free KIX exists in a (unfavorable) conformation that’s ready to bind c-Myb. The binding of MLL enhances KIX affinity for c-Myb by stabilizing this structure — the allosteric effect arises because MLL binding defrays the energetic cost of adopting this fold. This manifests as a shift in the population of KIX proteins towards the binding-competent state. This kind of binding cooperativity may play a significant role in CBP’s transcriptional activation function.

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

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

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