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J. Biol. Chem., Vol. 282, Issue 3, 1863-1872, January 19, 2007

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Disruption of Interdomain Interactions in the Glutamate Binding Pocket Affects Differentially Agonist Affinity and Efficacy of N-methyl-D-aspartate Receptor Activation^*

Wolfgang Maier¹, Rudolf Schemm², Christof Grewer^¶, and Bodo Laube³

From the Max-Planck-Institute for Brain Research, Frankfurt 60528, Germany, the Max-Planck-Institute for Biophysics, Frankfurt 60438, Germany, and the ^¶University of Miami School of Medicine, Department of Physiology and Biophysics, Miami, Florida 33136

Received for publication, August 24, 2006 , and in revised form, November 9, 2006.

	ABSTRACT

TOP ABSTRACT INTRODUCTION EXPERIMENTAL PROCEDURES RESULTS DISCUSSION REFERENCES

 
In ionotropic glutamate receptors, agonist binding occurs in a conserved clam shell-like domain composed of the two lobes D1 and D2. Docking of glutamate into the binding cleft promotes rotation in the hinge region of the two lobes, resulting in closure of the binding pocket, which is thought to represent a prerequisite for channel gating. Here, we disrupted D1D2 interlobe interactions in the NR2A subunit of N-methyl-D-aspartate (NMDA) receptors through systematic mutation of individual residues and studied the influence on the activation kinetics of currents from NR1/NR2 NMDA receptors heterologously expressed in HEK cells. We show that the mutations affect differentially glutamate binding and channel gating, depending on their location within the binding domain, mainly by altering k_off and k_cl, respectively. Whereas impaired stability of glutamate in its binding site is the only effect of mutations on one side of the ligand binding pocket, close to the hinge region, alterations in gating are the predominant consequence of mutations on the opposite side, at the entrance of the binding pocket. A mutation increasing D1D2 interaction at the entrance of the pocket resulted in an NMDA receptor with an increased open probability as demonstrated by single channel and whole cell kinetic analysis. Thus, the results indicate that agonist-induced binding domain closure is itself a complex process, certain aspects of which are coupled either to binding or to gating. Specifically, we propose that late steps of domain closure, in kinetic terms, represent part of channel gating.

	INTRODUCTION

TOP ABSTRACT INTRODUCTION EXPERIMENTAL PROCEDURES RESULTS DISCUSSION REFERENCES

 
Ionotropic glutamate receptors (iGluRs)⁴ are the major mediators of excitatory neurotransmission in the brain and play important roles both in neuronal development and synaptic function (1). They are tetrameric protein complexes (2, 3) in which each subunit is composed of (i) an extracellular amino-terminal domain, (ii) a ligand binding domain (LBD), sharing sequence homology to bacterial periplasmic binding proteins, (iii) a membrane-associated domain with the transmembrane helices M1–M4 that forms the ion pore, and (iv) an intracellular carboxyl-terminal domain (4).

The family of iGluRs is divided into the subclasses of AMPA, kainate, and NMDA receptors that differ, among other things, in their ligand specificities (1). Despite the pharmacological differences, crystal structures have been obtained for LBDs of subunits from all three subclasses of iGluRs (5–9) and have revealed a conserved clam shell-like architecture of two lobes (D1 and D2) around a central cleft that harbors the ligand binding site. Lobe D1 is formed from residues preceding the first transmembrane domain (M1) and the C-terminal residues of the extracellular loop between transmembrane domains 3 and 4, whereas the N-terminal part of this loop forms lobe D2.

LBD structures in complex with different ligands (10–12) have shed light on the molecular mechanism of ligand binding and, in the absence of structural information on the transmembrane domain, have led to the formulation of hypotheses on how agonist binding may be coupled to channel gating. Agonists differ from antagonists in that they promote closure of the LBD clam shell through rotation of lobe D2 toward D1. In a largely mechanical model of receptor activation (11), this motion is thought to generate conformational strain within the tetrameric receptor complex that transduces to the membrane regions and, eventually, causes channel opening. Several studies in AMPA and kainate iGluRs (6, 7, 11) relating structure to agonist efficacy show that the degree of domain closure induced by different agonists correlates with their functional activity. Interestingly, there is evidence that the glycine binding domain of the NR1 subunit of the NMDA receptor does not exhibit a similar correlation between domain closure and agonist efficacy (8, 12). Recent structure-function data show that engineering sterical restrictions within the glutamate-binding pocket of the NR2B subunit of the NMDA receptor is correlated to the degree of agonist efficacy (13), implicating that the action of glutamate and glycine on the NR2 and NR1 subunits, respectively, may induce different structural mechanisms underlying agonist efficacy.

However, although crystallographic data have uncovered the difference between agonist- and antagonist-bound LBD structures, kinetic studies are essential to elucidate the sequence and timing of conformational changes following agonist binding and their relationship to gating. Recently, one such study was performed for GluR2 AMPA receptors and has demonstrated that destabilizing the closed conformation of the binding domain through single amino acid mutations at the D1D2 interface reduces receptor open probability (14). Kinetically, the results place LBD closure as an intermediate step of receptor activation between ligand binding and channel opening, with domain closure being a prerequisite for channel opening but kinetically separate from it. At the same time, domain closure also contributes to apparent ligand affinity, because only the open state of the binding domain is permissive for dissociation of the ligand. The kinetic scheme proposed by Robert et al. (14), however, is derived from the effects of mutations at only one position in the binding domain. It is, therefore, based on the assumption that binding domain closure is itself a concerted step that can be monitored accurately by looking at single positions along the D1D2 interface. Here, we provide a more systematic exploration of the contributions of interdomain contacts in an iGluR LBD to ligand binding and channel gating. To this end, we introduced mutations into the NR2A subunit of NMDA receptors, targeting several D1D2 interactions predicted to stabilize the closed conformation of the binding domain and determined the kinetics of ligand binding and channel opening of the resulting receptors expressed in HEK293 cells. Our study reveals differential kinetic effects of the mutations depending on their location in the binding domain, arguing for the existence of distinct kinetic steps in the conformational rearrangements necessary for binding domain closure.

	EXPERIMENTAL PROCEDURES

TOP ABSTRACT INTRODUCTION EXPERIMENTAL PROCEDURES RESULTS DISCUSSION REFERENCES

 
In Vitro Mutagenesis—Single amino acid mutations of the NR2A subunit were introduced into the pCis WT vector (15) with the QuikChange site-directed mutagenesis kit (Stratagene) following the manufacturer's instructions. All mutations were verified by partial DNA sequencing.

Cell Culture and Transfection—HEK293 cells (ATCC CRL 1573) were cultured at 37 °C and 5% CO₂ in Dulbecco's modified Eagle's medium with 10% fetal calf serum. For transfection, cells were plated onto fibronectin-coated glass coverslips. After 24 h, cells were cotransfected with green fluorescent protein (in the pGreenLantern vector (Invitrogen)) and the NMDA receptor subunits NR1 and NR2A (both in the pCis vector) using the Effectene transfection kit (Qiagen) and a DNA ratio of 1:10:30 (green fluorescent protein/NR1/NR2A). Transfected cells were incubated in the presence of 2 µM 3-(2-carboxyethyl)-4,6-dichloro-1H-indole-2-carboxylic acid and 200 µM to 1 mM D-2-aminophosphonovalerate (both from Tocris) for 24–48 h before electrophysiological recordings.

Flash Photolysis and Whole Cell Recording—Flash photolysis was used for fast application of glutamate in whole cell recording experiments, with NI- and MNI-caged glutamate (from Sigma and Tocris, respectively) as photolabile precursors. Both compounds are suitable for studies on NMDA receptors (16, 17), with MNI-caged amino acids being characterized by higher photorelease efficiency compared with the NI-based precursors (18). MNI-caged glutamate, therefore, was used preferentially with low affinity mutant receptors.

The setup for solution exchange and photorelease of NMDA receptor agonists was as described previously (17). Briefly, it consisted of a quartz tube (350-µm diameter) from which solutions emerged with a speed of 5–10 cm/s and a quartz fiber (365-µm diameter) positioned perpendicular to it that served as the laser light guide. For whole cell recordings, cells were lifted from the coverslip and positioned between solution outlet and optical fiber. This configuration allowed complete solution exchange around the cell within 100–200 ms and optional photorelease of L-glutamate from its caged precursors through a light flash (345 nm, 15 ns) from an excimer laser-pumped dye laser (Lambda Physik). The amount of ligand released in photolysis experiments was controlled by attenuating the laser light with neutral density filters. Typical light intensities applied to cells were in the range of 50–400 mJ/cm². In this range, the concentration of released glutamate is a nearly linear function of light intensity, and absolute concentrations can be calculated after initial calibration as described (17). To determine EC₅₀ values of WT and mutant NMDA receptors, dose-response curves of glutamate-induced currents were analyzed in independent experiments by a rapid solution exchange application system in the presence of 50 µM glycine as described previously (19).

All whole cell recordings were done at a holding potential of -60 mV in extracellular solution containing 140 mM NaCl, 5 mM KCl, 0.85 mM CaCl₂, and 10 mM HEPES at pH 7.4. Recording pipettes had resistances of 1.5–3 megaohms and were filled with intracellular solution composed of 145 mM KCl, 10 mM EGTA, and 10 mM HEPES at pH 7.4. Data were low pass-filtered at 10 kHz and digitized at a sampling rate of 12 kHz.

Single Channel Recording—Single channel data for WT NR1/NR2A and NR1/NR2A(N668D) receptors transiently expressed in HEK293 cells were obtained from patches in the inside-out configuration as described previously (19). The membrane potential was clamped at -100 mV. The bath/internal solution in these experiments contained 141 mM potassium gluconate, 2.5 mM NaCl, 11 mM EGTA, and 10 mM HEPES at pH 7.4. The pipette/external solution contained 125 mM NaCl, 3 mM KCl, 1.25 mM NaH₂PO₄, 0.85 mM CaCl₂, and 20 mM HEPES also at pH 7.4 and was supplemented with the agonists L-glutamate and glycine at concentrations of 100 nM and 20 µM, respectively. Data were filtered at 10 kHz, digitized at 48 kHz, and stored on digital audio tape (DTR 1204; Biologic, Claix, France). For analysis, data were replayed from tape and sampled at 10 kHz. Tables of channel opening and closing events were generated with the TAC software (Instrutech). Open and shut time distributions were calculated using the method of maximum likelihood and the pStat program of the pclamp 6.0 package (Axon Instruments).

Data Analysis and Statistics—Photorelease of ligands from NI-caged precursors occurs on a time scale of microseconds or below (t 150 ns for an NI acetate model compound (20)). This is orders of magnitude faster than activation kinetics with millisecond time constants reported for NMDA receptors (e.g. see Refs. 21 and 22). Consequently, the time course of currents in our flash photolysis experiments is independent of the rate of ligand release and instead reflects intrinsic receptor kinetics. To interpret the observed kinetics in terms of rate constants of distinct steps of the activation process, we used the kinetic model shown in Scheme 1.

SCHEME. 1

Here, R denotes the receptor, and L denotes the ligand that is photoreleased during the course of the experiment. k_on and k_off are the rate constants for ligand binding and dissociation, and k_op and k_cl are those for channel opening and closing. The model takes into account that two molecules of glutamate have to bind to the NMDA receptor. It assumes that their binding sites are equal (i.e. that they can be occupied and freed in any order, and, for simplicity, that they are independent of each other (i.e. there is no cooperativity between them)). Because all flash photolysis experiments were done in the presence of saturating concentrations of the co-agonist glycine, steps for glycine binding could be omitted from the kinetic scheme, assuming that the glycine binding sites are always occupied, independent of the glutamate concentration. In order to determine kinetic properties of WT and mutant receptors, the model was translated into a Berkeley Madonna (Macey and Oster) equation file. The software was used to run a least squares fit procedure with a Levenberg-Marquardt minimization algorithm and the four rate constants in the model as free parameters to give the best match between sets of experimentally observed currents at different ligand concentrations and theoretical currents predicted by the model. Theoretical currents were calculated for each iteration of the fitting routine with a numerical integration method (4th order Runge-Kutta, 100-µs time interval), using the current values of the rate constants. From the rate constants, the dissociation constant and open probability were calculated as K_D = k_off/k_on and P_o = k_op/(k_op + k_cl).

We used numerical integration of the differential equations, because analytical integration of the full set of differential equations by using preequilibrium simplification methods was not possible in this system. The reason for this was that the high affinity of the NMDA receptor for glutamate results in a small ligand dissociation rate constant, k_off, which is in the same range as k_op and k_cl. Thus, it cannot be assumed that the ligand binding equilibrium is fast in comparison with the channel-opening equilibrium, a simplification that has been used in the past for analyzing the kinetics of other ligand-gated ion channels with lower affinities for the ligand (e.g. see Ref. 23).

Desensitization was omitted from the simplified kinetic scheme used for determination of the channel opening rates. This simplification is justified, because desensitization in NMDA receptors is 100–1000-fold slower than channel activation, as shown in supplemental Table 1. Furthermore, the rate of desensitization is not significantly changed by the mutations studied here, except by T494N (2-fold larger desensitization time constant). Therefore, a maximum of 6% of receptors desensitize during the time window of the current activation used for analysis of the channel opening kinetics.

Rate constants were determined, and K_D and P_o were calculated independently for each cell recorded from. Values are presented here as means ± S.E. One-way analysis of variance with a Tukey-Kramer post-test was used to test for differences between rate constants of WT and mutant receptors after logarithmic transformation. Differences were considered significant at p < 0.05, highly significant at p < 0.01, and extremely significant at p < 0.001.

Molecular Modeling and Prediction of Effects of Mutations— Since this work was carried out before publication of the crystal structure of the ligand binding domain of the NR2A subunit (9), candidate residues for mutagenesis were chosen based on a modeled structure. This model of the NR2A LBD with bound L-glutamate was generated based on the published (10) crystal structure of the GluR2 binding domain (Protein Data Bank entry 1FTJ [PDB] ) using the Sybyl 6.9 software (Tripos Associates) with residue numbering as in Ref. 24. The modeling procedure was analogous to that described previously for the binding domain of NR2B (25). Together with models of the NR2B binding domain with and without glutamate, this model was used to identify amino acid residues that may contribute to binding domain closure and that, therefore, represent candidate residues for mutagenesis and kinetic analysis of the resulting mutated receptors. Specifically, we were looking for residues that are involved in energetically favorable interactions between D1 and D2 across the binding cleft that are stronger in the ligand-bound than in the apo state. Such residues should help in stabilizing the closed conformation of the binding domain, and their mutation should change the equilibrium between the open and closed state of the binding domain. If binding domain closure is a prerequisite for channel gating, we hypothesized that a strong interaction between such residues might also change the equilibrium between the open and closed states of the ion channel. Although model-based, all of our predicted D1D2 interactions were later shown to be essentially correct with the advent of the crystal structure of the NR2A LBD (Protein Data Bank entry 2A5S).

To evaluate the effects of mutations, model structures of some of the mutated binding domains were obtained from the NR2A WT model with bound glutamate by manual exchange of the respective residues and subsequent dynamization and minimization of the structures. Differing from Ref. 25, dynamization was run for 10,000 fs (with 1-fs intervals) at low simulated temperature (20 K, 20-fs coupling factor) on the core of the binding domain (defined by an 8-Å radius around Glu³⁹⁴, Lys⁴⁶⁵, Asn⁶⁶⁸, and Asp⁷¹² and including about a quarter of total atoms in the model). In this way, overall structure remained largely preserved, whereas regions around mutations were allowed to settle into relatively unstrained conformations.

In addition, published interaction propensity values (26) were used to estimate the impact of mutations on the strength of the corresponding D1D2 interaction. These values are based on a set of 1073 known protein structures and a distance cut-off of 4.5 Å used to define an interaction.

	RESULTS

TOP ABSTRACT INTRODUCTION EXPERIMENTAL PROCEDURES RESULTS DISCUSSION REFERENCES

 
Interactions across the NR2A D1D2 Interface That Stabilize the Closed Conformation of the Binding Domain—From our NR2 binding domain models, we could identify two main regions in which agonist-induced D1D2 interactions are formed. These are located on opposite sides of the binding pocket, facing the ammonium group or the two carboxyl groups of the agonist, respectively. The first region comprises residues Glu³⁹⁴ and Thr⁴⁹⁴ in D1 (yellow balls 1 and 4 in Fig. 1A) and Tyr⁷¹¹ and Asp⁷¹² in D2 (gray balls) of NR2A. Residues that contribute to the domain interactions in the second region are Lys⁴⁶⁵ in D1 and Asn⁶⁶⁸ in D2 (yellow balls 2 and 5 in Fig. 1A). Our model and the now published crystal structure of the NR2A LBD agree in that they both suggest differential roles of the agonist in the formation of the interactions in these two regions. Domain interactions in the first region directly involve the bound agonist. The ammonium group of L-glutamate, for example, interacts with Thr⁴⁹⁴, which, in turn, forms a hydrogen bond with Asp⁷¹². Via a water molecule (present in the crystal structure), the agonist also interacts with Glu³⁹⁴, which itself contacts Tyr⁷¹¹. Thus, L-glutamate brings together the D1/D2 interaction partners Glu³⁹⁴/Tyr⁷¹¹ and Thr⁴⁹⁴/Asp⁷¹² in a complex network of hydrogen bonds (Fig. 1C). In contrast, the agonist does not form direct contacts to any of the interacting residues in the second region. Two prominent interactions in this region are single hydrogen bonds between Lys⁴⁶⁵ in D1 and Asn⁶⁶⁸ in D2 (Fig. 1D) and between Lys⁴⁶⁵ and Glu⁶⁷² (not shown). Glu⁶⁷² is located within helix F of the binding domain, and Asn⁶⁶⁸ is located immediately N-terminal of it. This helix carries two residues, Ser⁶⁷⁰ and Thr⁶⁷¹, that are critical for binding the carboxyl groups of L-glutamate (24) and moves toward the agonist and the D1 lobe during domain closure. Thus, D1D2 contacts in this region are induced by the agonist indirectly by promoting the movement of helix F.

View larger version (51K): [in this window] [in a new window]   FIGURE 1. Amino acid residues involved in glutamate-induced cross-lobe interactions in the NR1/NR2A binding domain. A, schematic illustration of the location of the mutated residues (yellow balls) and their proposed interaction partners (gray balls) in the binding domain (modeled structure in the closed conformation with S1 in blue and S2 in green). B, sequence comparison between NMDA receptor subunits NR2A, NR2B, and NR1 and the AMPA receptor subunit GluR2. Mutated residues are indicated by their numbers from A, and their interaction partners are indicated by asterisks. C and D, detailed views of the cross-lobe interaction regions 1 and 2, respectively, showing the orientation of the residues highlighted in A relative to each other and to glutamate in the binding site.

Kinetic Effects of the Mutations—For a first characterization of the NR2A mutants, we determined glutamate dose-response curves and calculated the respective EC₅₀ values and Hill coefficients (n_H) by using a conventional capillary application system. Of the seven substitutions introduced, six significantly affected the EC₅₀ value of glutamate (supplemental Table 1). The respective Hill coefficients were in the range of 1.02–1.35 (i.e. not different from the value obtained with the WT protein) (n_H = 1.27 ± 0.19; supplemental Table 1). Together these data corroborate earlier reports showing that mutations introduced at the D1D2 interface of iGluRs affect apparent glutamate affinity (13, 14, 27, 28). To assess the effects of the mutations on receptor activation, rate constants for glutamate binding and dissociation as well as for channel opening and closing of the mutant receptors were compared with the corresponding values of WT receptors. Using our whole cell approach and kinetic model of receptor activation, we found the following values for the WT parameters (n = 8 cells): k_on = 5 x 10⁷ ± 0.6 x 10⁷ M^-1 s^-1, k_off = 160 ± 30 s^-1, k_op = 380 ± 70 s^-1, k_cl = 250 ± 40 s^-1. From these parameters, the open probability P_O can be calculated as 0.59 ± 0.08, and the dissociation constant K_D can be calculated as 3.3 ± 0.5 µM. These values and our relatively simple kinetic model are sufficient to describe adequately the lag and the rising phases of receptor currents induced by a range of agonist concentrations in our experiments (Fig. 2). The value determined here for P_O is in reasonably good agreement with that recently reported for NR1/NR2A receptors (29), despite the different kinetic models used for analysis.

View larger version (18K): [in this window] [in a new window]   FIGURE 2. Descriptive quality of the kinetic model. A, example whole cell currents (solid lines) elicited from one cell by photorelease of three different concentrations of L-glutamate from its caged precursor. B, magnification of the first 20 ms of traces in A. Superimposed on the traces in A and B are the currents (dashed lines) predicted for the same concentrations by the kinetic model and the parameter values determined for this cell. Predicted currents describe adequately only the rising phases of currents, because neither desensitization nor decrease in agonist concentration during the course of recordings is accounted for by the kinetic model used.

View larger version (15K): [in this window] [in a new window]   FIGURE 3. Illustration of kinetic results for WT and mutant receptors. Kinetic parameters for the binding step of receptor activation are shown in A, and those for the gating step are shown in B. Glutamate binding rate (kon) is plotted against dissociation rate (koff)in A, and channel opening rate (kop) is plotted against closing rate (kcl)in B. The ratio of koff to kon and of kcl to kop, and consequently the values of KD and Po, are constant and equal to WT receptors along the solid lines in A and B, respectively. Data points above these lines thus correspond to receptors with decreased affinity/open probability compared with WT, whereas those below it indicate receptors that have higher affinity/open probability than WT. Error bars represent S.E. values, and the S.E. for the lines of equal affinity and open probability is indicated by dashed lines.

Comparison of WT NR1/NR2A and NR1/NR2A(N668D) Receptors at the Single Channel Level—Although the emphasis of this study was on comparison of the kinetic characteristics of mutated and WT receptors on the whole cell level, the unique properties conferred by mutation N668D (i.e. a gain of function with respect to gating efficiency) prompted us to verify this result by single channel analysis as an independent method. Also, among the mutations studied here, the N668D substitution particularly lends itself to this comparison of the two methods, because its strong effect on gating suggested by the whole cell results should be readily observable also in single channel data. Comparison of recordings from patches with WT and with N668D mutant receptors in the inside-out configuration, by visual inspection of traces alone, suggested a clear difference between WT and part of the mutant receptors (Fig. 5A), in agreement with the analysis of the whole cell data. Unexpectedly, however, responses of mutant receptors strongly differed between patches, and only about half of the patches (4 of 10) showed activity patterns characterized by the long openings that are apparent in the example trace, whereas the remaining patches seemed to behave more like WT. Because we did not observe switching between these two patterns within recordings from individual patches, we classified patches of mutant receptors into WT-like (class I) or different from WT (class II) based on visual inspection of traces and analyzed open and shut time histograms of three WT receptors, three mutant receptors of class I, and three mutant receptors of class II (Table 2, Fig. 4B). This revealed values for shut and open time constants of WT receptors that are comparable with previously published ones (30) for NR1/NR2A receptors transiently expressed in HEK293 cells and verified the initial impression that there was no significant difference between either open or shut time distributions of WT receptors and mutant receptors of class I. In contrast, mutant receptors of class II, while showing no significant difference from WT in their shut time distribution, exhibited a clear change in open time distribution. Like for WT receptors (and mutant receptors of class I), this distribution could be described by a single component, but the time constant associated with this component is more than 20-fold slower than in WT. From the data, the values of k_cl can be calculated to be 470 ± 30 s^-1 and 30 ± 12 s^-1 for WT and N668D receptors of class II, respectively, which is in reasonably good agreement with the values determined with the whole cell approach. Thus, class II mutant receptors confirm the whole cell results at the single channel level. On the other hand, the limited amount of single channel data obtained so far does not allow us to give an experimentally supported explanation for the apparent existence of the two classes of mutant receptors. An intriguing finding is the similarity between the kinetic characteristics of the two classes and those reported for WT NR1/NR2A receptors in the so-called H- and L-modes of gating (31). However, the H-mode of gating is normally not observed in the absence of Mg²⁺ chelators in the extracellular recording solution, and switching between modes should occur in individual receptors (31), although there is a chance that we have missed such events due to relatively brief recording periods of around 1–5 min in our experiments.

View larger version (11K): [in this window] [in a new window]   FIGURE 4. Correlation of interaction propensity of residues 465 and 668 with glutamate gating efficacy in WT and four mutant receptors. Propensity values of the residue pairs (indicated in parentheses) at positions 465 and 668 are plotted against the observed kop/kcl ratio ± S.E. of the corresponding receptors. The dashed line represents the best linear fit to the data.

	DISCUSSION

TOP ABSTRACT INTRODUCTION EXPERIMENTAL PROCEDURES RESULTS DISCUSSION REFERENCES

Specifically, we investigated the NR1/NR2A subunit combination of NMDA receptors and quantified rate constants for binding and gating steps based on whole cell recordings of currents in response to rapid application of L-glutamate. Theoretically, analysis of equilibrium dose-response relationships should provide similar quantitative information on underlying binding and gating parameters (34). However, the practical quality of such dose-response data is in most cases not adequate to separate the binding and gating effects of a receptor mutation, since changes in gating efficacy are assumed to be mirrored only in small changes of the respective Hill coefficient (34). Therefore, we chose to activate the receptors by jumping the glutamate concentration, because following the subsequent channel opening in real time and as a function of the glutamate concentration allows the direct and independent determination of the rate constants associated with the glutamate binding and the channel opening processes. In choosing a kinetic model for fitting experimental currents, we gave preference to a simple model, including only ligand binding and gating steps, in which all rate constants can be determined from whole cell recordings, over more complex ones that describe more adequately certain aspects of NMDA receptor activity at the single channel level but would require fixing of some of their parameters to estimated values. It is, therefore, an important question whether our simplified model can provide meaningful information about the binding and gating steps underlying real NMDA receptor activation in our experimental system. There are three arguments that make us confident that this is the case. First, quality of fits to our experimental data were generally very good (see Fig. 2) for all agonist concentrations at all receptor variants investigated, indicating that, although simple, our model still provides an adequate description of whole cell data. Also the quality of fits was not improved by using more complex models for receptor activation, such as the one proposed in (35). Due to the lack of desensitization steps in the kinetic scheme, it is capable of describing adequately only the rising phase of current responses. However, since desensitization compared with channel opening is several orders of magnitude slower in wild type NMDA receptors, as well as in the mutant receptors studied here (supplemental Table 1), and because its mechanism is not a focus of this study, this does not compromise our results. Second, the parameter values that we determined for WT NR1/NR2A receptors are comparable with published ones (29) that were obtained from a more sophisticated activation scheme derived from single channel analysis and initially proposed by Banke and Traynelis (35). This well accepted model assumes that the NR1 and NR2 subunits undergo independent conformational changes before gating of the receptor. The channel opening rate determined from our model should correspond approximately to k_s+, the forward reaction rate for the conformational change undergone by the NR2 subunit, which is rate-limiting for channel opening in the Banke and Traynelis model. The values are as follows: k_op = 380 ± 70 s^-1 and k_s+ = 230 ± 26 s^-1, which is in reasonably good agreement, given the complexity of the fitting procedures involved. Likewise, our value for the channel closing rate (250 ± 40 s^-1) is similar to the sum (352 s^-1)of k_f- and k_s-, the combined backward reaction rates for the conformational changes in NR1 and NR2, of which reversal of either is sufficient to close the channel. Furthermore, our value determined for the maximum channel open probability (P_o = 0.59 ± 0.08), calculated from k_op and k_cl, is close to the one inferred directly from single channel data (0.50 ± 0.03) in Ref. 29. Thus, our analysis agrees with Ref. 29 in that it finds a P_o value that is substantially larger than previous estimates (e.g. Refs. 22 and 36). Third, our whole cell approach indicates a strongly reduced closing rate and increased P_o as an effect of the N668D mutation, and this finding is corroborated by single channel data for the mutant receptors. Taking these arguments together, we conclude that our kinetic analysis allows meaningful interpretation of macroscopic current responses in terms of changes to binding and gating.

View larger version (40K): [in this window] [in a new window]   FIGURE 5. Single channel comparison of NR2A(N668D) and WT receptors. A, representative stretches of recordings from inside-out patches of mutant class II (upper two traces) and WT (lower two traces) receptors. B, shut time and open time distributions for single patches of mutant class II (top row) and WT (bottom row) receptors. Note the different x-scale in the open time distribution.

We show here that cross-lobe interactions in two regions on opposite sides of the ligand binding pocket have very different effects on the kinetics of NMDA receptor activation. Of the residues investigated here, those that are involved in hinge region interactions (region 1; see Fig. 1C) are also interacting, either directly (Thr⁴⁹⁴) or indirectly via a water molecule (Glu³⁹⁴) with the agonist through its ammonium group, thus providing a direct explanation for the effect on ligand affinity of mutations in this region. Together with the absence of gating effects of these mutations, this result suggests that the formation of cross-lobe interactions near the hinge region is a process associated kinetically with ligand binding and separate from channel opening. Hinge region interactions may be necessary to create an optimal binding site for the ammonium group of glutamate and/or to lock the agonist into its binding site. This situation parallels that in AMPA receptors, for which it was recently shown that the effects of disrupting a cross-lobe interaction, that involves Glu⁴⁰² (equivalent to Glu³⁹⁴ of NR2A) and Thr⁶⁸⁶ (not conserved in NR2A), can be explained as a result of destabilization of an additional agonist-bound closed state (14). This locked state differs from the initial state after ligand binding in that the agonist cannot dissociate from it and, thus, contributes significantly to the apparent affinity of AMPA receptors. Destabilization of the locked state by mutations is therefore seen as an increase in the ligand dissociation rate in a simplified kinetic model similar to the one used here (14). As pointed out in Ref. 14, the stability of the locked state, which is proposed to be the only state from which channel opening can occur, influences also the apparent open probability, although locking is kinetically distinct from gating. As one consequence of this, mutations that destabilize the locked state cause reduced efficacies of partial relative to full agonists. Although we have not performed any experiments with agonists other than glutamate in this study, previous work on NR2B (13) has demonstrated that mutation of Glu³⁸⁷ (homologous to Glu³⁹⁴ studied here) to alanine reduces efficacy of NMDA relative to glutamate (to 28% compared with 71% in WT). A reduction of relative efficacy (to 57%) was also seen with mutation of Tyr⁷⁰⁵ (equivalent to Tyr⁷¹¹ of NR2A) to alanine, and a smaller decrease, although not significant, was seen also for Thr⁴⁸⁸ (Thr⁴⁹⁴ in NR2A) to alanine. Combined with the data presented here, these results suggest that agonist-induced formation of D1D2 interactions near the hinge region may stabilize a hypothetical locked state in NMDA receptors as it does in AMPA receptors.

In contrast to the results obtained for region 1, our data for region 2 mutant receptors show that, in NR2A, formation of D1D2 interactions at the entrance of the binding pocket is kinetically coupled to gating and is of minor importance for ligand binding. Mutations at the homologous positions in NR2B (459 and 662), again, significantly decrease gating efficacy of NMDA relative to L-glutamate (13), but our kinetic analysis for NR2A attributes this to a direct effect on gating (i.e. changes in channel opening or closing rates).

The residues corresponding to Lys⁴⁶⁵ and Asn⁶⁶⁸ are involved in D1D2 interactions also in NR1 (12), but the whole network of interactions on this side of the binding pocket is not conserved in AMPA receptor subunits. Interestingly, in AMPA receptors full and partial agonists have been shown to induce closure of the LBDs to different extents, but agonists of NR1 seem to cause full domain closure independent of their efficacy in triggering gating (12). This difference might be a consequence of the stronger D1D2 interactions in the vicinity of helix F in NMDA receptors. The degree of LBD closure in AMPA receptors may be largely determined by interactions between agonist and residues of the binding domain. In NMDA receptors, however, such interactions might serve only to initiate movement of helix F, which then would "snap" into place, driven by the attractive forces between D1 and D2. In this model of NMDA receptor LBDs as molecular relays, the likelihood of switching to the closed conformation would be influenced by the nature of the agonist (i.e. its efficiency in inducing movement of helix F). In contrast, the likelihood of reopening would be determined by the network of interactions between D1 and D2. In agreement with this model, partial agonists of either NR1 or NR2 have been reported to shift components of single channel shut time (35, 37) but not open time histograms (i.e. to cause slower channel opening), whereas, complementarily, we find that a mutation, N668D, at the D1D2 interface of NR2A has no effect on channel opening but dramatically slows channel closing.

In summary, the data presented here suggest that agonist-induced activation of NMDA receptors proceeds through several kinetically distinct steps and that D1D2 interactions in opposing regions of the LBD with respect to the glutamate binding pocket contribute differentially to stability of the corresponding states.

	FOOTNOTES

 
^* This work was supported by Deutsche Forschungsgemeinschaft Grant LA 1086/4-1 (to B. L.) and by the Hertie-Stiftung (to B. L.). The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

The on-line version of this article (available at http://www.jbc.org) contains supplemental Table 1.

¹ Present address: Friedrich Miescher Institute for Biomedical Research, Basel 4058, Switzerland.

² Present address: MPI for Biophysical Chemistry, Göttingen 37077, Germany.

³ To whom correspondence should be addressed: AG Cellular Neurophysiology, Dept. of Biology, Technical University Darmstadt, Schnittspahnstr. 3, 64287 Darmstadt, Germany. Tel.: 49-69-96769-295; Fax: 49-69-96769-441; E-mail: laube{at}bio.tu-darmstadt.de.

⁴ The abbreviations used are: iGluR, ionotropic glutamate receptor; AMPA, (RS)-2-amino-3-(3-hydroxy-5-methyl-4-isoxazlyl)-propionic acid; LBD, ligand binding domain; MNI, 4-methoxy-7-nitroindoline; NI, 7-nitroindoline; NMDA, N-methyl-D-aspartate; WT, wild type.

	ACKNOWLEDGMENTS

 
We thank Dr. J. E. T. Corrie (National Institute for Medical Research, London, UK) for help with the NI/MNI-caged compounds.

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