Characterization of the non-competitive antagonist binding site of the NMDA receptor in dark Agouti rats

Characterization of the non-competitive antagonist binding site of the NMDA receptor in dark Agouti rats

Life Sciences 75 (2004) 1405 – 1415 www.elsevier.com/locate/lifescie Characterization of the non-competitive antagonist binding site of the NMDA rece...

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Life Sciences 75 (2004) 1405 – 1415 www.elsevier.com/locate/lifescie

Characterization of the non-competitive antagonist binding site of the NMDA receptor in dark Agouti rats WenLin Sun a, William D. Wessinger b,* a

Program in Neural Sciences, Department of Psychology, Indiana University, 1101 E. 10th Street, Bloomington, IN 47405, USA b Department of Pharmacology and Toxicology, College of Medicine, University of Arkansas for Medical Sciences, 4301 W. Markham Street, Slot 611, Little Rock, AR 72205, USA Received 4 September 2003; accepted 24 November 2003

Abstract The ability of non-competitive NMDA antagonists and other selected compounds to inhibit [3H]MK-801 binding to the NMDA receptor in brain membranes was evaluated in female, dark Agouti rats. In homologous competition binding studies the average apparent affinity (KD) of [3H]MK-801 for its binding site was 5.5 nM and the binding site density (Bmax) was 1.83 pmol/mg protein. Inhibition of [3H]MK-801 binding by non-competitive NMDA antagonists was best described with a one-site competition model and the average Hill coefficients were 1. A series of eight non-competitive NMDA antagonists inhibited [3H]MK-801 binding with the following rank order of affinity (Ki, nM): MK-801 (5.5) > dexoxadrol (21.5) z TCP (24.2) > phencyclidine (100.8) > (+)-SKF 10,047 (357.7) > dextrorphan (405.2) > ketamine (922.2) > dextromethorphan (2913). These inhibition binding constants determined in dark Agouti rat brain membranes were significantly correlated ( P = 0.0002; r2 = 0.95) with previously reported values determined in Sprague-Dawley rats [Wong et al., 1988, J. Neurochem, 50, 274 – 281]. Despite significant differences in metabolic capability between these strains, the central nervous system NMDA receptor ion channel shares similar characteristics. D 2004 Elsevier Inc. All rights reserved. Keywords: Receptor binding; NMDA receptor; Non-competitive NMDA antagonists; MK-801; Dizocilpine; Dark Agouti rats; Strain comparison

Introduction The effects of phencyclidine (PCP) and other non-competitive NMDA antagonists have been shown to differ across rodent strains. Strain differences have most frequently been examined in mice. For * Corresponding author. Tel.: +1-501-686-5514; fax: +1-501-686-5521. E-mail address: [email protected] (W.D. Wessinger). 0024-3205/$ - see front matter D 2004 Elsevier Inc. All rights reserved. doi:10.1016/j.lfs.2003.11.035

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example, A/J mice are more sensitive to the locomotor stimulating effects of PCP than C57BL/6J or BALB/cByJ mice, while locomotor activity of C57BL/6ByJ mice is relatively unaffected by PCP. The development of tolerance with repeated PCP dosing also varies across strains (Xu and Domino, 1994). Similarly, the CBA mouse strain is more sensitive to the effects of the non-competitive NMDA antagonists, MK-801, PCP and ketamine, than the NMRI and C57 strains (Liljequist, 1991). Marked differences in the ability of MK-801 to elicit ‘‘popping behavior’’ among inbred mouse strains (Deutsch et al., 1997) have been reported. Such differences in response to non-competitive NMDA antagonists have been used to infer differences in the NMDA receptor complex mediating these drug effects (Deutsch et al., 1997; Liljequist, 1991). Studies comparing the characteristics of the NMDA receptor ion-channel binding site across species or strains are few in number and offer conflicting results. Among vertebrates (guinea pig and chicken), the rank order of potency for compounds that inhibit brain [3H]TCP binding is highly correlated, but differs significantly from the rank order determined in the sea anemone (Vu et al., 1990). In human brain and Sprague-Dawley rat brain the affinity of [3H]TCP for its binding site within the NMDA receptor channel is similar, but the binding site density (Bmax) is about 12 times higher in rat brain (Vignon et al., 1989). Likewise, differences in the density of [3H]MK-801 binding sites, but no differences in KD, are described for two mouse lines selectively bred for differential sensitivity to ethanol (Wilson and Collins, 1996). In contrast, a study comparing [3H]MK-801 binding to the suprachiasmatic nucleus in rat and hamster brains found differences in both KD and Bmax across these species (Hartgraves and Fuchs, 1994). Dextromethorphan, a non-competitive NMDA antagonist with low affinity for the ion-channel binding site, is used in many over-the-counter cold and cough medications as an antitussive. Over the years there have been sporadic reports of its use at higher doses as a drug of abuse (e.g., Banerji and Anderson, 2001; Bem and Peck, 1992) and there are numerous internet sites that provide information about its recreational abuse (Banerji and Anderson, 2001). Identifying mechanisms that contribute to its abuse is difficult because dextromethorphan is rapidly metabolized to an active metabolite, dextrorphan (Barnhart, 1980), by hepatic cytochrome P450 CYP2D6 (Ku¨pfer et al., 1986). Metabolism in most rat strains follows the same pathway, except the O-demethylation of dextromethorphan is mediated by CYP2D1, an orthologue of human CYP2D6 sharing a 71% amino acid sequence homology (Soucek and Gut, 1992). In contrast, the dark Agouti rat strain, lacking the ability to express CYP2D1 (Larrey et al., 1984; Matsunaga et al., 1989) does not form dextrorphan as the major metabolite. Consequently, dark Agouti rats could serve as a useful model to separate the actions dextromethorphan from those of dextrorphan. The present study was conducted in dark Agouti rats to provide a basis for understanding the effects of these drugs relative to the effects of other non-competitive NMDA antagonists. Using brain membranes from dark Agouti rats, we investigated the ability of a series of non-competitive NMDA antagonists and other compounds to compete with [3H]MK-801 binding at the ion-channel site of the NMDA receptor. Our results are compared to results obtained in Sprague-Dawley rats in previous studies (Wong et al., 1988).

Methods These studies conformed to the animal use protocols approved by the University of Arkansas for Medical Sciences Institutional Animal Care and Use Committee and in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals (NIH Publications No. 8023,

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revised 1978). The American Association for the Accreditation of Laboratory Animal Care accredited the animal housing and laboratory facilities. Membrane preparations Female, dark Agouti rats were purchased from B & K Universal, Inc. (Freemont, CA) and housed in a vivarium for at least two weeks prior to use. The rats (150–170 g body weight) were decapitated and the brains were rapidly removed. After removing the cerebellum, the rest of the brain was quickly frozen and stored for at least 48 h at 140 jC. To make crude synaptic membrane preparations, individual brains were thawed at room temperature, and then homogenized (Tekmar SDT100EN tissue homogenizer, Cincinnati, OH; speed setting 7) for 30 s in 15 volumes (15 ml/g brain tissue) of ice-cold 0.32 M sucrose. Following a low-speed centrifugation (1,000  g, 4 jC, 10 min), the supernatant and buffy coat were decanted and centrifuged at 45,000  g (4 jC, 20 min). The resulting pellet was washed by re-suspension in 50 volumes of 50 mM TrisHCl (pH 7.4, 4 jC) and centrifugation (45,000  g, 4 jC, 20 min) two times. The final pellet was re-suspended in 15 volumes of 5 mM TrisHCl (pH 7.4, 4 jC). After determining the protein concentration (Coomassie protein assay, Pierce Chemical Co., Rockford, IL), the tissue preparation was diluted to a final concentration of approximately 1.25 mg protein/ml for use in the binding assays. Binding assays All binding assays were conducted in 5 mM TrisHCl buffer (pH 7.4, 25 jC). In preliminary studies (data not shown), equilibrium conditions were attained within a 4-h incubation period. Binding reactions were initiated by adding 200 Al of brain membrane homogenate to test tubes containing 100 Al of 20 nM [3H]MK-801 and 200 Al of assay buffer (with or without various concentrations of competing drugs). In the incubation mixture, the final concentration of [3H]MK-801 was approximately 4 nM and the protein concentration was about 0.5 mg/ml. After a 4-h incubation at 25 jC, the reaction was terminated by adding 5 ml of ice-cold TrisHCl followed by rapid filtration (Brandel M-24R cell harvester, Gaithersburg, MD) onto glass-fiber filters (Whatman GF/B, Brandel). Filters were soaked in 0.05% polyethylenimine for at least two h before use to minimize nonspecific binding. Filtered membranes were quickly rinsed three times with 3 ml of icecold buffer and then placed into 7-ml plastic scintillation vials. Five ml of scintillation fluid (Ecoscint A, National Diagnostics, Atlanta, GA) was added and the vials were vigorously shaken. After soaking overnight, the bound radioactivity associated with the filtered membranes was quantified by liquid scintillation spectrometry (Packard Instrument Co., model 1900 counter, Downers Grove, IL). Data and statistical analysis For most of the competing ligands studied, 4–5 separate experiments were performed. Each experiment employed brain membranes from a different rat and examined 8–10 inhibitor concentrations in triplicate. Competition binding data were analyzed using nonlinear regression curve-fitting procedures (GraphPad Prism v.3.0, GraphPad Software, Inc., San Diego, CA). The appropriateness of one-site competition models with a constant slope ( 1) or variable slope, or a two-site competition model were evaluated with an F-test ( P z 0.05). The ‘‘best fit model’’ was defined as the simplest model that adequately described the data. In addition to the F-tests described, models were evaluated to ensure that the fitted parameters were

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logically acceptable. For example, a more complicated model would be rejected if any parameter estimates fell outside of the data range, if there were extremely wide confidence limits or, in the case of two-site model, if the fractional component of either site was very small (e.g. < 0.15) (Motulsky, 1999). The top and bottom asymptotes determined by nonlinear regression analysis were compared to experimentally determined total binding (radioligand binding in the absence of competitor) and nonspecific binding (binding in the presence of saturating concentrations of competing drug) using a paired t-test. For competition studies using unlabeled MK-801 as the inhibitor, a nonlinear regression curve was fit to a homologous competition model (GraphPad Prism) to determine the apparent affinity (KD) and receptor number (Bmax). Bmax values in dpm were converted to pmol/mg protein, using the experimentally determined protein concentrations. For studies using other inhibitors, the inhibition constant, Ki, was calculated from IC50 values using the Cheng–Prusoff equation (Cheng and Prusoff, 1973). Because limited amounts of (+)-pentazocine and 3-methoxymorphinan were available, only four concentrations (0, 10 AM, 100 AM and 1 mM) were studied in a single experiment for each compound. Preliminary studies with morphine and fluoxetine indicated that these compounds did not substantially inhibit [3H]MK-801 binding except at very high concentrations, thus these experiments were also not repeated. For these four ligands, the zero inhibitor concentration was entered into the nonlinear regression curve fitting analyses as a very low inhibitor concentration (0.01 nM) to help define the upper plateaus of the competition binding curves. A one-site competition model (slope constrained to 1) was used to obtain the parameter estimates. The binding parameters are presented as the averaged values along with the 95% confidence limits (CL) or the standard error of the mean (SEM). For parameters estimated from the log-concentration axis (i.e. IC50, Ki and KD) averages were calculated as the geometric mean (Kenakin, 1977). Representative data shown in the figures were from the individual assay with an IC50 closest to the averaged value for the experiment. Drugs and chemicals (+)-[3H]MK-801 (25 Ci/mmol) was purchased from American Radiolabeled Chemicals, Inc. (St. Louis, MO). Non-radiolabeled MK-801 ((5R,10S)-(+)-5-methyl-10,11-dihydro-5H-dibenzo[a,d]cyclohepten5,10-imine hydrogen maleate or dizocilpine maleate)) was provided by Merck Sharp & Dohme Research (Rahway, NJ). The National Institute on Drug Abuse (Bethesda, MD) provided phencyclidine hydrochloride (1-(1-phenylcyclohexyl)piperidine hydrochloride or PCP), 1-[1-(2-thienyl)cyclohexyl]piperidine hydrochloride (TCP), (+)-3-methoxymorphinan hydrochloride, (+)-N-allylnormetazocine hydrochloride ((+)-SKF 10,047), (+)-pentazocine succinate and dexoxadrol hydrochloride. Dextromethorphan hydrobromide and dextrorphan tartrate were purchased from RBI (Natick, MA). Fluoxetine hydrochloride was provided by Eli Lilly (Indianapolis, IN) and ketamine hydrochloride was obtained from Parke-Davis (Ann Arbor, MI). Morphine sulfate was purchased from Mallinkrodt Chemicals (St. Louis, MO). Other reagents used in these experiments were purchased from commercial vendors.

Results The results from four experiments in female dark Agouti rat brains using unlabeled MK-801 (0.1 nM–3 AM) to compete with [3H]MK-801 binding indicated that [3H]MK-801 binds with high affinity to

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Fig. 1. Competition for [3H]MK-801 binding to brain membranes from dark Agouti rats with various concentrations of unlabelled MK-801. Shown are data from a representative experiment, one of four conducted. Each point is the mean ( F SD) of values determined in triplicate. The line was obtained by fitting a homologous competition model to the competition binding data using nonlinear regression analysis (Prism, GraphPad Software).

a single binding site. The binding data was best fit ( F-test, P > 0.05) using a constant slope ( 1), onesite competition model. The average goodness of fit or R2 (F SEM) was 0.996 (0.002). The top and bottom plateau estimates from the model did not significantly differ (t-test, P > 0.05) from the

Fig. 2. The effects of selected non-competitive NMDA antagonists to inhibit the binding of [3H]MK-801 to brain membranes from dark Agouti rats. The individual sets of data points are from a representative experiment with points determined in triplicate (mean F SD, but note that the error bars are often obscured by the symbols). The inhibitors shown are PCP, a highly abusable dissociative anesthetic; TCP, a potent PCP analog; ketamine, a therapeutic dissociative anesthetic that is increasingly abused; and dexoxadrol, a substituted dioxolane that exhibits PCP-like actions. The best-fit line was determined by fitting a onesite competition model to the competition binding data using non-inear regression (Prism, GraphPad Software). The reported Ki values and 95% CL (Table 1) are the mean of 4 – 5 determinations with each inhibitor.

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experimentally derived values for total and for nonspecific binding determined in the presence of zero or excess (100 AM) unlabeled MK-801, respectively. Nonspecific binding was approximately 7% of total binding. The IC50 (95% CL) was 9.59 nM (8.23–11.17 nM). An homologous competition model was used to estimate the affinity and density of the [3H]MK-801 binding site (Motulsky, 1999). The average apparent KD (95% CL) was 5.48 nM (4.03–7.44 nM) and the average apparent Bmax (95% CL) was 1.83 pmol/mg protein (1.78–1.88 pmol/mg protein). Fig. 1 shows a representative competition-binding curve for MK-801. The dissociative anesthetics PCP (1 nM–30 AM), TCP (0.3 nM–10 AM) and ketamine (10 nM–300 AM) all dose-dependently inhibited [3H]MK-801 binding to brain membranes from female dark Agouti rats (Fig. 2). All of the competition binding curves for the dissociative anesthetics (n = 4 for each inhibitor) were best fit to the one-site competition model (slope = 1) with resulting average R2 values ( F SEM)) being 0.999 ( < 0.001), 0.999 (0.001) and 0.997 (0.001) for PCP, TCP and ketamine, respectively. In all cases the fitted top and bottom asymptotes were not significantly different (t-test, P > 0.05) from the respective measures of total binding or nonspecific binding in the presence of 100 AM PCP or TCP, or 1 mM ketamine. The average apparent Ki for the most potent inhibitor, TCP, was 24.2 nM. The Ki for PCP was 100.8 nM and the Ki for ketamine was 922.2 nM. The Ki values for all the effective inhibitors, along with the 95% CL, are summarized in Table 1. Dexoxadrol, a substituted dioxolane, had a slightly higher affinity (Ki = 21.5 nM) for the binding site labeled by [3H]MK-801 than any other inhibitor tested (Fig. 2). The competition binding curves (n = 5) for dexoxadrol (1 nM–30 AM) were similar to those obtained with the dissociative anesthetics. The binding data from three of the five experiments were best fit to the constant slope ( 1) one-site competition model (F-test, P > 0.05). The other two binding curves were best fit with a variable slope model (F-test, P = 0.026 or 0.008) yielding Hill coefficients of 1.09 and 1.12. Nevertheless, the Table 1 Inhibition constants (Ki F 95% CL) determined from competition binding curves of [3H]MK-801 binding in dark Agouti rat brain membranes. For comparison, Ki values determined in Sprague-Dawley rats (Wong et al., 1988) are also shown Dark Agoutia

Sprague-Dawleyc

Inhibitors

Ki, nM

95% CL

Ki, nM

MK-801 Dexoxadrol TCP PCP (+)-SKF 10,047 Dextrorphan Ketamine Dextromethorphan 3-Methoxymorphinan (+)-Pentazocine

5.5 21.5 24.2 100.8 357.7 405.2 922.2 2913.4 1689b 7674b

4.0 – 7.4 18.9 – 24.5 16.6 – 35.4 80.1 – 126.8 308.2 – 415.2 277.0 – 592.9 787.7 – 1079.4 2429.4 – 3493.0 1608 – 1775 7203 – 8176

3 31 14 42 317 222 1090 ND ND ND

ND = not determined. a Kis were calculated from IC50 values using the Cheng – Prusoff equation (Cheng and Prusoff, 1973). The mean Kis and 95% CLs were calculated by averaging the log Kis determined in 4 – 5 separate experiments, except as noted. b Ki was determined in a single experiment. The 95% CL is the confidence limit associated with the Ki parameter estimated by nonlinear regression analysis. c Data from Sprague-Dawley rats was originally published by Wong et al. (1988) and used here with permission of Dr. Wong and Blackwell Publishing, Ltd.

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mean Hill slope for the dexoxadrol experiments did not differ significantly from 1 (one sample t-test, P > 0.05). The overall average goodness of fit ( F SEM) was 0.998 ( < 0.001). The curve fit plateaus did not differ from the maximum and minimum binding determined experimentally. The benzomorphan compounds, (+)-SKF 10,047 and (+)-pentazocine, dose-dependently inhibited [3H]MK-801 binding. Competition binding curves (n = 5) for (+)-SKF 10,047 (3 nM–100 AM) were best fit with one-site competition models (Fig. 3). Four of the competition binding curves were best fit with the constant slope ( 1) model ( F-test, P > 0.05), but the remaining case was best fit with a variable slope model ( F-test, P = 0.018) and had a Hill coefficient of 0.90. Overall, however, the Hill slopes for the (+)-SKF 10,047 experiments did not significantly differ from 1 (one sample t-test, P > 0.05). The average goodness of fit ( F SEM) was 0.997 (0.001). The top asymptote did not differ significantly from the total binding determined in the absence of inhibitor (t-test, P > 0.05), but the bottom curve-fit asymptote was significantly greater (t-test, P = 0.03) than the nonspecific binding determined in the presence of excess (+)-SKF 10,047 (1 mM). The average Ki for (+)-SKF 10,047 was 357.7 nM. (+)-Pentazocine was only evaluated at four inhibitor concentrations in a single experiment. A fixed-slope, one-site competition model resulted in an excellent curve fit (R2 > 0.999). The estimated Ki was 1689 nM and the 95% CL of the parameter estimate was 1608–1775 nM. The antitussive dextromethorphan and its primary and minor metabolites, dextrorphan and 3methoxymorphinan, respectively, all dose-dependently inhibited [3H]MK-801 binding (Fig. 3). Dextrorphan and dextromethorphan were each evaluated in four experiments using inhibitor concentrations ranging from 3 nM to 300 AM. Of the morphinans, dextrorphan was the most potent inhibitor. Only one of the four competition binding curves for dextrorphan was best modeled with the fixed-slope, one-site

Fig. 3. Effects of selected non-competitive NMDA antagonists to inhibit the binding of [3H]MK-801 to brain membranes from dark Agouti rats. The individual sets of data points are from a representative experiment with points determined in triplicate (mean F SD, but note that the error bars are often obscured by the symbols). The inhibitors shown are dextromethorphan, a widely used antitussive that is subject to some abuse; dextrorphan, a primary and active metabolite of dextromethorphan; 3methoxymorphinan, a minor metabolite; and (+)-SKF 10,047, a benzomorphan sigma ligand. The best-fit line was determined by fitting a one-site competition model to the competition binding data using non-linear regression (Prism, GraphPad Software). The reported Ki values and 95% CL are the mean of 4 determinations with each inhibitor, except for 3-methoxymorphinan for which a single experiment was conducted.

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competition model ( F-test, P > 0.05). The remaining three curves were better fit with the variable-slope model ( F-test, P = 0.003, 0.005 or 0.04). One of these fit a two site model significantly better ( F-test, P = 0.001); however, one of the binding sites described by the two-site model had such a small fraction of the receptors (approximately 14%) that the IC50 was not considered reliable (Motulsky, 1999). Therefore, the less complex model (one site, variable slope) was used to interpret this experiment. Despite three of four experiments being best fit by the variable slope model, as a group the Hill coefficients were not significantly different from the theoretical 1 (one sample t-test, P > 0.05) expected for single site drugreceptor kinetics. Likewise, the fitted top and bottom plateau estimates did not differ from those determined in the absence of inhibitor or measured in the presence of 1 mM of dextrorphan (t-tests, P > 0.05). The average goodness of fit, R2 ( F SEM), was 0.999 ( < 0.001). The average Ki for dextrorphan was 405.2 nM. The dextromethorphan competition-binding curves (n = 4) were all best fit to a fixedslope, one-site model. The average R2 ( F SEM) was 0.999 ( < 0.001) and the top and bottom plateaus did not differ from those determined experimentally (1 mM dextromethorphan was used for nonspecific binding). The average Ki for dextromethorphan inhibition of [3H]MK-801 was 2913 nM. The ability of 3methoxymorphinan to inhibit [3H]MK-801 binding was only evaluated in one experiment at four concentrations. When fit to a fixed-slope, one-site competition model the R2 was >0.999 and the Ki was 1689 nM. The [3H]MK-801 binding site does not appear to interact significantly with opioids such as morphine or the antidepressant, fluoxetine. The competition binding curves for morphine and fluoxetine could not be fit to the fixed-slope, one-site competition binding model. Inspection of the binding curves suggested the IC50s would be >100 AM. All of the non-competitive NMDA antagonists were effective competitors of the specific binding of 3 [ H]MK-801 and had Hill coefficients not significantly different from unity. The rank order for inhibiting [3H]MK-801 binding was: MK-801 > dexoxadrol z TCP > PCP > (+)-SKF 10,047 > dextrorphan > ketamine > dextromethorphan. The Kis are summarized in Table 1. Also shown in Table 1 are previously published Ki values determined in Sprague-Dawley rats under similar experimental conditions (Wong et al., 1988). There was a clear correlation between the affinities of compounds that inhibited [3H]MK-801 binding in female dark Agouti rat brains and in Sprague-Dawley rat brains (Pearson correlation analysis, P = 0.0002; correlation coefficient, r = 0.98).

Discussion The results from competition experiments in female dark Agouti rat brains were consistent with previous observations that MK-801 binds to a single high-affinity binding site (Burke et al., 1995; Wong et al., 1986, 1988). In the present study, homologous competition binding techniques yielded values for KD and Bmax (5.5 nM and 1.8 pmol/mg protein, respectively) that are very similar to those reported in male (Burke et al., 1995; Wong et al., 1988) or female (Wessinger, 1995) Sprague-Dawley rat brains using saturation binding techniques. Only drugs known to act as non-competitive NMDA antagonists were effective competitors of [3H]MK-801 binding. Most of the non-competitive NMDA antagonists inhibited [3H]MK-801 binding in a manner best described by a fixed-slope ( 1) one-site competition binding model. Dexoxadrol, dextrorphan and (+)-SKF 10,047 were the only competing ligands for which the variable-slope, onesite competition model provided a better fit in some experiments. While this suggests that the binding

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interactions of these ligands with the [3H]MK-801 binding site may differ from simple mass-action kinetics, the strength of this observation is tempered by the fact that the mean Hill coefficients for these drugs did not differ from the theoretical 1 expected for uncomplicated interactions between and drug and a single receptor. These results, while interesting, should be replicated, perhaps in experiments with additional inhibitor concentrations to better define possible binding variations, before they should be taken to have biological significance. In all cases, the goodness of fit values indicated excellent curve fits with R2 values near unity. Furthermore, the top and bottom curve plateaus predicted by nonlinear regression curve fitting analyses were nearly always in good agreement with the empirically determined maximum and minimum binding seen in the absence or presence of excess inhibitor, respectively. Dextromethorphan inhibited the binding of [3H]MK-801 with relative low affinity (Ki, 2913 nM) compared to the affinity of its active metabolite, dextrorphan (Ki, 405 nM). Similar differences in affinity between these two morphinans, ranging from approximately 6.5- to 8.0-fold, have also been reported in Sprague-Dawley rats for inhibition of [3H]MK-801 binding (Jaffe et al., 1989) and for inhibition of [3H]dextrorphan binding (Franklin and Murray, 1992; Roth et al., 1996). Newman et al. (1996) examined the inhibition of [3H]TCP binding by a series of dextromethorphan analogs. Dextrorphan, the most potent competitor tested (Ki, 460 nM) was about 8-fold more potent than dextromethorphan (Ki, 3500 nM); these results are in good agreement with the present study. The minor dextromethorphan metabolite, 3-methoxymorphinan (termed nordextromethorphan in that study) was equipotent to dextrorphan with a Ki of 487 nM (Newman et al., 1996). In contrast, 3-methoxymorphinan inhibited [3H]MK-801 binding with an intermediate affinity (Ki, 1689 nM) in the present study. Dextromethorphan is conventionally described as a non-competitive NMDA antagonist in the literature. However, it should be kept in mind that it has a complex pharmacology and that a number of its actions may be unrelated to its binding to the NMDA receptor (Tortella et al., 1989). For example, in some studies dextromethorphan has been shown to be much more effective in potentiating opiate analgesia than predicted on the basis of its affinity for the NMDA receptor ion channel (e.g. Chaplan et al., 1997; Plesan et al., 1998). Additionally, the antitussive actions of dextromethorphan appear to be best related to its affinity at sigma binding sites (Kamei et al., 1993; Kotzer et al., 2000). Fluoxetine and morphine, which have not been demonstrated to be active at the NMDA receptor ion channel, were very poor competitors of [3H]MK-801 binding. The Kis for these drugs were estimated to be in excess of 100 AM. The methods used for the preparation of brain membranes in the present study were similar to those used by Wong et al. (Wong et al., 1988) for Sprague-Dawley rats, with which our results are directly compared. More extensive tissue preparation techniques, involving the use of multiple freeze/thaw cycles, the addition of detergents, and/or the use of more cycles of re-suspension and centrifugation (washing) to prepare the so-called ‘‘well-washed’’ tissue preparation, would have required the addition of endogenous modulators such as L-glutamate and L-glycine back into the membrane preparation in order to stimulate binding. The elimination these binding modulators followed by addition of maximally stimulating concentrations would likely have masked differences in NMDA receptors due to strain dependent differences in the levels of endogenous modulators, although this possibility was not directly investigated. The previous studies reported by Wong et al. (1988) used cerebral cortical membranes and thus were also similar to the present studies that utilized whole brain (minus cerebellum) homogenates in this respect. Our findings of the similarities of the NMDA receptor ion-channel binding site in dark Agouti

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and Sprague-Dawley rats does not preclude the possibility that there might be regional differences in this binding site between rat strains. There was an excellent correlation in the ability of the non-competitive NMDA antagonists to inhibit [3H]MK-801 binding between dark Agouti and Sprague-Dawley rat strains. This observation, coupled with evidence that these inhibitors compete with [3H]MK-801 at a single site, and that the affinity and density of this binding site are similar in both strains support the hypothesis that these very different rat strains have similar, if not identical NMDA receptors. This, in turn, supports the notion that dark Agouti rats, because they lack CYP2D1 that mediates the metabolic conversion of dextromethorphan to dextrorphan, may be useful for investigating the actions of these drugs independently. Acknowledgements A portion of these results were presented at the 64th Annual Scientific Meeting of the College of Problems of Drug Dependence, Quebec City, 2002 and in abstract form (Wessinger and Sun, 2002). Supported by a grant from the National Institute on Drug Abuse (DA-10358) and a Graduate Student Research Grant from the University of Arkansas for Medical Sciences (WLS). References Banerji, S., Anderson, I.B., 2001. Abuse of Coricidin HBP Cough & Cold tablets: episodes recorded by a poison center. American Journal of Health-System Pharmacists 58, 1811 – 1814. Barnhart, J.W., 1980. The urinary excretion of dextromethorphan and three metabolites in dogs and humans. Toxicology and Applied Pharmacology 55, 43 – 48. Bem, J.L., Peck, R., 1992. Dextromethorphan. An overview of safety issues. Drug Safety 7 (3), 190 – 199. Burke, T.F., Buzzard, S., Wessinger, W.D., 1995. [3H]MK-801 binding to well-washed rat brain membranes following cessation of chronic phencyclidine treatment. Pharmacology Biochemistry and Behavior 51 (2/3), 435 – 438. Chaplan, S.R., Malmberg, A.B., Yaksh, T.L., 1997. Efficacy of spinal NMDA receptor antagonism in formalin hyperalgesia and nerve injury evoked allodynia in the rat. Journal of Pharmacology and Experimental Therapeutics 280 (2), 829 – 838. Cheng, Y., Prusoff, W.H., 1973. Relationship between the inhibition constant (KI) and the concentration of inhibitor which causes 50 percent inhibition (I50) of an enzymatic reaction. Biochemical Pharmacology 22, 3099 – 3108. Deutsch, S.I., Rosse, R.B., Mastropaolo, J., 1997. Behavioral approaches to the functional assessment of NMDA-mediated neural transmission in intact mice. Clinical Neuropharmacology 20 (5), 375 – 384. Franklin, P.H., Murray, T.F., 1992. High affinity [3H]dextrorphan binding in rat brain is localized to a noncompetitive antagonist site of the activated N-methyl-D-aspartate receptor-cation channel. Molecular Pharmacology 41, 134 – 146. Hartgraves, M.D., Fuchs, J.L., 1994. NMDA receptor binding in rodent suprachiasmatic nucleus. Brain Research 640 (1-2), 113 – 118. Jaffe, D.B., Marks, S.S., Greenberg, D.A., 1989. Antagonist drug selectivity for radioligand binding sites on voltage-gated and N-methyl-D-aspartate receptor-gated Ca2 + channels. Neuroscience Letters 105, 227 – 232. Kamei, J., Iwamoto, Y., Misawa, M., Kasuya, Y., 1993. Effects of rimcazole, a specific antagonist of j sites, on the antitussive effects of non-narcotic antitussive drugs. European Journal of Pharmacology 242, 209 – 211. Kenakin, T., 1977. Molecular Pharmacology: A Short Course. Blackwell Science, Cambridge, MA. Kotzer, C.J., Hay, D.W.P., Dondio, G., Giardina, G., Petrillo, P., Underwood, D.C., 2000. The antitussive activity of y-opioid receptor stimulation in guinea pigs. Journal of Pharmacology and Experimental Therapeutics 292 (2), 803 – 809. Ku¨pfer, A., Schmed, B., Pfaff, G., 1986. Pharmacogenetics of dextromethorphan O-demethylation in man. Xenobiotica 16, 421 – 433. Larrey, D., Distlerath, L.M., Dannan, G.A., Wilkerson, G.R., Guengerich, F.P., 1984. Purification and characterization of the rat

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