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Research ArticleNEUROPHARMACOLOGY

Differential Actions of Antiparkinson Agents at Multiple Classes of Monoaminergic Receptor. I. A Multivariate Analysis of the Binding Profiles of 14 Drugs at 21 Native and Cloned Human Receptor Subtypes

Mark J. Millan, Lisa Maiofiss, Didier Cussac, Valérie Audinot, Jean-A. Boutin and Adrian Newman-Tancredi
Journal of Pharmacology and Experimental Therapeutics November 2002, 303 (2) 791-804; DOI: https://doi.org/10.1124/jpet.102.039867

Abstract

Because little comparative information is available concerning receptor profiles of antiparkinson drugs, affinities of 14 agents were determined at diverse receptors implicated in the etiology and/or treatment of Parkinson's disease: human (h)D1, hD2S, hD2L, hD3, hD4, and hD5 receptors; human 5-hydroxytryptamine (5-HT)1A, h5-HT1B, h5-HT1D, h5-HT2A, h5-HT2B, and h5-HT2Creceptors; hα1A-, hα1B-, hα1D-, hα2A-, hα2B-, hα2C-, rat α2D-, hβ1-, and hβ2-adrenoceptors (ARs); and native histamine1 receptors. A correlation matrix (294 pKi values) demonstrated substantial “covariance”. Correspondingly, principal components analysis revealed that axis 1, which accounted for 76% variance, was associated with the majority of receptor types: drugs displaying overall high versus modest affinities migrated at opposite extremities. Axis 2 (7% of variance) differentiated drugs with high affinity for hD4 and H1 receptors versus hα1-AR subtypes. Five percent of variance was attributable to axis 3, which distinguished drugs with marked affinity for hβ1- and hβ2-ARs versus hD5and 5-HT2A receptors. Hierarchical (cluster) analysis of global homology generated a dendrogram differentiating two major groups possessing low versus high affinity, respectively, for multiple serotonergic and hD5 receptors. Within the first group, quinpirole, quinerolane, ropinirole, and pramipexole interacted principally with hD2, hD3, and hD4receptors, whereas piribedil and talipexole recognized dopaminergic receptors and hα2-ARs. Within the second group, lisuride and terguride manifested high affinities for all sites, with roxindole/bromocriptine, cabergoline/pergolide, and 6,7-dihydroxy-N,N-dimethyl-2-ammotetralin (TL99)/apomorphine comprising three additional subclusters of closely related ligands. In conclusion, an innovative multivariate analysis revealed marked heterogeneity in binding profiles of antiparkinson agents. Actions at sites other than hD2 receptors likely participate in their (contrasting) functional profiles.

In Parkinson's disease, the progressive degeneration of nigrostriatal dopaminergic pathways is associated with diverse motor symptoms, including rigidity, tremor, bradykinesia, and postural instability (Jenner, 1995). In addition, patients present, often precociously, sensory and cognitive-attentional deficits together with depressed mood (Jenner, 1995). Despite increasing interest in neuroprotective strategies, Parkinson's Disease is principally treated by administration of the dopamine (DA) precursorl-dihydroxyphenylalanine (l-DOPA) (Bezard et al., 2001). However, there is evidence, albeit contentious, thatl-DOPA exacerbates damage to dopaminergic neurons (Zou et al., 1999). Furthermore, l-DOPA displays variable pharmacokinetics, elicits dyskinesias and autonomic side effects, poorly improves certain motor symptoms, is largely ineffective against cognitive and mood deficits, and loses efficacy upon prolonged administration (Bezard et al., 2001). Abrupt transitions between “on” and “off” phases are particularly distressing to patients (Jenner, 1995). In light of these observations, the management of Parkinson's Disease by drugs directly stimulating postsynaptic DA receptors is of interest (Jenner, 1995; Montastruc et al., 1999). Such dopaminergic agents possess neuroprotective properties, mediated by both dopaminergic (autoreceptor) and nondopaminergic mechanisms (Zou et al., 1999) and elicit less marked dyskinesia (Uitti and Ahlskog, 1996;Rascol et al., 2000). Furthermore, they may improve mood and cognitive function (Weddell and Weiser, 1995; Nagaraja and Jayashree, 2001). In addition to adjunctive therapy, recent studies support the long-term efficacy of dopaminergic agonists in monotherapy, thereby delaying the introduction of l-DOPA (Rascol et al., 2000). Nevertheless, “sleep-attacks”, sedation, and both psychiatric and cardiovascular side effects complicate utilization of dopaminergic agonists (Friedman and Factor, 2000).

The above-mentioned panoply of desirable and undesirable actions varies among antiparkinson agents (Uitti and Ahlskog, 1996). Such differences likely reflect contrasting patterns of interactions at sites other than dopamine D2 receptors (Uitti and Ahlskog, 1996). D3 receptors are of particular interest, although it remains controversial as to whether their engagement contributes to therapeutic and/or psychiatric and motor side effects (Millan et al., 2000b; Joyce, 2001). Activation of D4 receptors does not, on the other hand, participate in the improvement of Parkinson's Disease (Newman-Tancredi et al., 1997; Oak et al., 2000). Although D1receptor agonists display antiparkinson activity in experimental models, their clinical efficacy upon long-term administration remains uncertain, and their stimulation is not obligatory for therapeutic activity (Jenner, 1995; Gulwadi et al., 2001). Furthermore, the relative roles of D1 versus closely related D5 sites remain unclear (seeDiscussion).

Inasmuch as 1) Parkinson's Disease is aggravated by degeneration of locus coeruleus-derived adrenergic and raphe-derived serotonergic pathways (Brefel-Courbon et al., 1998; Jellinger, 1999); and 2) adrenergic and serotonergic mechanisms modulate dopaminergic transmission, motor behavior, mood, and cognitive function (Meneses, 1999; Millan et al., 2000c), it is important to consider potential actions of antiparkinson agents at adrenoceptors (ARs) and 5-HT receptors. Although surprisingly little information is available, talipexole and 6,7-dihydroxy-N,N-dimethyl-2-ammotetralin (TL99) are known to possess agonist properties at native α2-ARs (Horn et al., 1982; Meltzer et al., 1989). In contrast, blockade of α2-ARs by piribedil reinforces frontocortical adrenergic, dopaminergic, and cholinergic transmission and favorably influences mood and cognitive-attentional function (Millan et al., 2000c, 2001a; Maurin et al., 2001; Nagaraja and Jayashree, 2001; Gobert et al., 2002). In addition to antagonist actions at α2- and α1-ARs, bromocriptine reveals pronounced affinity for 5-HT1A receptors (McPherson and Beart, 1983; Jackisch et al., 1985; Uitti and Ahlskog, 1996). Other antiparkinson agents known to recognize 5-HT1Aand/or 5-HT2A receptors are lisuride, terguride, and roxindole (Jackson et al., 1995; Uitti and Ahlskog, 1996).

The purpose of the present studies was to consolidate these fragmentary data by evaluating the actions of 14 dopaminergic agonists (antiparkinson agents) at multiple classes of monoaminergic receptor. In addition, actions at muscarinic (M1) sites and histamine (H)1 sites were evaluated in light of 1) their role in the control of motor behavior, mood, and cognition (Bacciottini et al., 2001; Brown et al., 2001); 2) alterations in histaminergic and cholinergic transmission in Parkinson's Disease (Jellinger, 1999; Anichtchik et al., 2000); and 3) the use of anticholinergic agents for management of refractory tremor (Wilms et al., 1999). The strategy adopted was as follows. First, using competition binding assays, drug affinities were determined at recombinant, stably transfected, human receptors as well as at rat α2D-ARs1and at native H1 receptors. Second, to facilitate analysis of the extensive database and comparisons of drug profiles, a correlation matrix was constructed: data were subjected to principle components analysis (PCA) and then drugs were classified by hierarchical (cluster) analysis in accordance with their overall homology. This innovative multivariate approach to drug comparisons has the advantage that it is not founded upon specific hypotheses requiring testing via post hoc, inferential statistics. Rather, by fully and simultaneously exploring total variance, it permits the objective identification and interpretation of hidden patterns not revealed by visual inspection or drug-by-drug/receptor-by-receptor comparisons (Krzanowski, 2000; Millan et al., 2000a; Carlsson et al., 2001). Third, as described in the accompanying articles (Newman-Tancredi et al., 2002a,b), efficacies of antiparkinson agents were determined at (the majority of) monoaminergic receptor subtypes incorporated into these multivariate analyses.

Materials and Methods

Determination of Drug Affinities.

Procedures used for the determination of drug affinities have been described in detail previously (Newman-Tancredi et al., 1997; Millan et al., 2001a). They are summarized in Tables 1,2, and3. Isotherms were subjected to nonlinear regression analysis by use of the program PRISM (GraphPad Software, San Diego, CA) to yield IC50 values. These were subsequently transformed intoKi values according to the Cheng-Prussof equation Ki = IC50/(1 +L/Kd), where Lcorresponds to the radioligand concentration andKd to its dissociation constant.

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Table 1

Competition binding conditions at recombinant, human dopaminereceptors

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Table 2

Competition binding conditions at recombinant, human hα1-, hα2-, and hβ-adrenoceptors and at rat rα2-adrenoceptors

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Table 3

Competition binding conditions at recombinant, human serotonin (5-HT) receptors, at recombinant, human hM1 and at native histamine H1 receptors

Multivariate Analysis: Principal Components Analysis.

The database used for multivariate analysis comprised the affinities (“parameters”) for 14 drugs at (21) separate receptors (“variables”) indicated in Tables 4,5, and 6. (pKi values of <5.0 were considered as 5.0 for these analyses.) Because all parameters are intrinsically equivalent, they were not transformed (“standardized”): pKi values are the negative logarithmic expression of affinities. After construction of a correlation matrix (Pearson product-moment coefficients) across all parameters (Table 7), the database was subjected to PCA (Krzanowski, 2000) using SPAD-3, a computer program developed by the Centre International de Statistiques et d'Informatiques Appliquées (St. Mandé, France). This generates a “multidimensional space” of 21 axes from the database, with all axes mathematically “perpendicular” to each other. The first axis, principal component (PC)1, represents the linear combination of all parameters (affinities) in the data set that accounts for the maximal possible variance. Correspondingly, loading values (correlation coefficients) in Table 8 indicate the contribution of individual parameters to PC1. Successive axes (PC2 onwards) account for progressively less variance. PCs 1 to 3, which accounted for a substantial majority of variance (see Results), were two-dimensionally represented in scatter diagrams (“biplots”) upon which drugs were superimposed together with the parameters underlying their dispersion.

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Table 4

Affinities (pKi values) of antiparkinson agents at recombinant, human dopamine receptors

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Table 5

Affinities (pKi values) of antiparkinson agents at recombinant human hα1-, hα2-, and hβ-adrenoceptors and at native, rat rα2D-ARs

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Table 6

Affinities (pKi values) of antiparkinson agents at serotonin h5-HT1 and h5-HT2 receptor subtypes and at native histamine H1 receptors

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Table 7

Correlation matrix of the interrelationship between drug affinities (pKi values) at multiple classes of dopamine receptor, adrenoceptor, serotonin receptor, and at H1 receptors

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Table 8

Loading values for individual variables onto principal components (PC) 1, 2, and 3.

Multivariate Analysis: Hierarchical Cluster Analysis.

After PCA, and likewise exploiting SPAD-3, drugs were hierarchically (“cluster”) classified in accordance with their overall homology to yield a binary dendrogram (Krzanowski, 2000). Using an “agglomeration” algorithm, the array of drugs was progressively (“hierarchically”) fused into subclusters and clusters until it comprised a single group. With the formation of each successive cluster, the loss of “objective function value” (information) was constrained as much as possible, that is, the intragroup compared with intergroup variance was minimized. The length of bars between pairs of drugs in the two-dimensional dendrogram reflects their dissimilarity, that is, the shorter the distance, the more closely related the pairs of drugs. Nodes on the dendrogram therefore represent the consecutive aggregation of two individual elements (drugs or drug clusters).

Radar Plots.

“Radar” representations of binding profiles at certain key receptors were constructed to further visualize similarities and differences in drug binding profiles.

Drugs.

Pramipexole dihydrochloride, piribedil hydrochloride, and ropinirole were synthesized by Institut de Recherches Servier (Paris, France). Lisuride maleate and terguride were donated by Schering (Berlin, Germany); bromocriptine, (−)-quinpirole, pergolide, and TL99 were purchased from Sigma/RBI (Natick, MA); apomorphine hydrochloride was purchased from Sigma (St. Quentin Fallavier, France); and roxindole was donated by Merck (Darmstadt, Germany) and talipexole (BHT-920) by Boehringer Ingelheim GmbH (Ingelheim, Germany). Cabergoline was obtained from Farmitalia Carlo Erba (Rueil-Malmaison, France). Quinelorane dihydrochloride was a gift from Eli Lilly & Co. (Indianapolis, IN).

Results

General Comments.

In view of the large number of drugs and binding sites examined, a detailed text description of all (∼300) interactions cannot be presented below. Full data are shown in Tables 4to 7.

Dopamine hD2S, hD2L, hD3, and hD4 Receptors.

There was a substantial (5000-fold) range in drug affinities at hD2S receptors (Table4).2 For example, the affinity of cabergoline was very pronounced compared with that of pramipexole. At hD2L receptors (which possess a 29 amino acid insert in the third intracellular loop), affinities of drugs likewise varied broadly and were similar to those at hD2S sites. There was likewise marked (∼1000-fold) variability in drug affinities at hD3 sites. The ratio of drug affinities at hD3 compared with hD2L and hD2S sites differed considerably from modest (e.g., cabergoline and pergolide) to pronounced (e.g., pramipexole). The variation in drug affinities at hD4 receptors was also striking (∼400-fold). Certain drugs displayed considerably higher affinities at hD4 versus hD2S/hD2L sites (such as apomorphine), whereas others showed modest differences (such as piribedil) or a marked preference for hD2S/hD2L sites (such as bromocriptine).

Dopamine hD1 and hD5 Receptors.

Drug affinities for hD1 sites were substantially lower than for hD2S and hD2Lreceptors: apomorphine and cabergoline showed the least and most pronounced difference, respectively (Table 4). There was ∼200-fold variability in drug affinities at hD1 sites with certain agents, including pramipexole, displaying negligible affinity. For all drugs manifesting significant affinity for hD1 receptors, affinities were higher at hD5 receptors. This difference was mild for certain drugs, such as bromocriptine, and pronounced for others, such as pergolide.

hα1A-, hα1B-, and hα1D-ARs.

For each drug, affinities at hα1A-, hα1B-, and hα1D-ARs were similar (Table5). Affinities varied over a ∼10,000 range from negligible (e.g., pramipexole) through intermediate (e.g., apomorphine) to pronounced (e.g., bromocriptine).

rα2D-, hα2A-, hα2B-, and hα2C-ARs.

There was considerable (>10,000) variability in drug affinities for hα2A- and rα2D-ARs, ranging from quinerolane (negligible) to lisuride (very high), with piribedil, talipexole, and several other drugs showing intermediate values (Table 5). Only cabergoline revealed (slightly) higher affinity for rα2D- versus hα2A-ARs. No drug clearly differentiated hα2-AR subtypes, although pramipexole showed negligible affinity for hα2C- versus hα2A- and hα2B-ARs. Bromocriptine and roxindole were the only drugs to show similar or weaker affinities at hα2A- compared with hα1-AR subtypes.

hβ1- and hβ2-ARs.

Only four ligands (lisuride, terguride, bromocriptine, and roxindole) displayed significant affinity for hβ1-ARs (Table 5). Bromocriptine and roxindole showed similar affinity at hβ2-ARs, whereas lisuride and terguride revealed higher affinity for hβ2- compared with hβ1-ARs. Compared with hα2-ARs, affinities at hβ1- and hβ2-ARs were relatively weak for all drugs, and only lisuride and terguride approached affinities seen at hα1-ARs.

h5-HT1A Receptors.

There was substantial (10,000-fold) variation in drug affinities at h5-HT1A receptors varying from quinerolane (<5.0) to roxindole (9.9) (Table 6). Several other agents, such as bromocriptine and apomorphine, showed marked affinity for h5-HT1A sites although others, such as piribedil and talipexole, showed only modest affinities.

h5-HT1B and h5-HT1D Receptors.

Several drugs, including piribedil and talipexole, failed to recognize h5-HT1B receptors, although others, such as cabergoline and pergolide, displayed modest affinities (Table 6). At structurally related h5-HT1D receptors, affinities were generally elevated compared with h5-HT1B receptors, notably for cabergoline and pergolide, whereas these sites were not recognized by piribedil and talipexole.

h5-HT2A, h5-HT2B, and h5-HT2CReceptors.

For closely related h5-HT2A, h5-HT2B, and h5-HT2Creceptors, binding profiles were generally comparable (Table 6). However, certain agents, including cabergoline and pergolide, showed substantially lower affinity for h5-HT2C versus h5-HT2A and h5-HT2Breceptors. No drug clearly differentiated h5-HT2Afrom h5-HT2B sites. There was marked (>100-fold) variability in drug affinities at h5-HT2A, h5-HT2B, and h5-HT2Creceptors in each case: piribedil, talipexole, and pramipexole, for example, showed low affinities compared with apomorphine, bromocriptine, and, in particular, cabergoline and pergolide.

H1 Receptors.

Affinities of drugs at H1 receptors varied from negligible (for example, apomorphine, bromocriptine, piribedil, and pramipexole) to modest (for example, terguride and lisuride) (Table 6).

Interrelationship among Binding Sites: Correlation Matrix.

An important and general feature of the correlation matrix was the lack of negative correlation coefficients, that is, in no case was high affinity at one receptor associated with low affinity at a second site (Table 7). This feature was reflected in numerous statistically significant correlation coefficients among pairs of receptors (Table 8). Some were unsurprising, such as between hD2S and hD2L receptors, among hα1-AR and hα2-AR subtypes and between h5-HT2A and h5-HT2C receptors. More notably, there were high correlation coefficients between affinities at hD2S and hD2L receptors on the one hand, and h5-HT2A, h5-HT2B, and h5-HT2Creceptors on the other. Furthermore, hD5, h5-HT2C, and h5-HT2A sites were well correlated. Similarly, high correlation coefficients were observed between hD2 receptors and α1- and α2-AR subtypes. On the other hand, affinities at hD4 receptors were poorly correlated with affinities at hD2S, hD2L, and hD3 receptors, as well as other sites with the exception of H1receptors. H1 receptors were themselves distinguished by relatively poor (and, in certain cases, nonsignificant) correlation coefficients with other receptor types.

Principle Components Analysis.

Application of PCA to the pKi values revealed that almost 90% of variance could be accounted for by three axes: PC1, PC2, and PC3 (Figs. 1, 2, and 3; Table 8). That is, a reduction of “dimensionality” from 21 to a “subspace” of three axes preserved almost the entire variance in the data. This permitted the construction of bidimensional “biplots” (1/2, 1/3, and 2/3) upon which both the drugs and the variables that contributed to their dispersion could be projected (Figs. 1-3).

Figure 1
Figure 1

Principle component analysis of drug interactions at multiple binding sites examined herein: axes (principal components) 1 and 2. The database (pKi values) comprised 14 drugs and 21 binding sites indicated in Tables 4 to 6. These values (a total of 294) were simultaneously analyzed in a “polydimensional” space, as described under Materials and Methods. Top (scatter diagram), plots the distribution of each parameter (specific binding sites) as a function of its contribution to the first two principle components (axes), which accounted for 76.27 and 6.53% of variance, respectively. Reflecting extensive, positive “covariance” indicated in Table 8, all parameters (vectors) clustered in the same direction along axis 1. Within the plot, the “circle of correlation” is depicted. The degree of correlation among specific parameters is revealed by projection of vectors onto this circle, and by the angle between pairs of vectors, which is inversely correlated to their degree of correlation (Table 8). For example, in the bottom left quadrant, all three α1-AR subtypes are highly intercorrelated, whereas they are poorly correlated to hD4 receptors located in the upper quadrant (Table 8). The tips of the vectors, when vertically or horizontally projected onto PC1 and PC2, respectively, yield loading values indicated in Table 8. Bottom, drugs are superimposed upon PCs 1 and 2. S, 5-HT.

Figure 2
Figure 2

Principle component analysis of drug affinities at multiple binding sites examined herein: axes (principal components) 1 and 3. Top, distribution of each parameter (specific binding sites) as a function of principle components (axes) 1 and 3, which accounted for 76.27 and 5.4% of variance, respectively. Bottom, drugs are superimposed upon PCs 1 and 2. See the legend to Fig. 4 andResults for further details. S, 5-HT

Figure 3
Figure 3

Principle component analysis of drug affinities at multiple binding sites examined herein: axes (principal components) 2 and 3. Top, distribution of each parameter (specific binding sites) as a function of principle components (axes) 2 and 3, which accounted for 6.53 and 5.4% of variance, respectively. Bottom, drugs are superimposed upon PCs 2 and 3. See the legend to Fig. 4 andResults for further details. S, 5-HT.

The majority of variance (76.3%) could be attributed to PC1. Upon projection of drugs onto the biplot, they distributed along its entire length with lisuride and terguride defining one extremity and quinerolane, quinpirole, pramipexole, and ropinirole the other. (Note that orthogonal dispersion along PC2 is not relevant to the notion of clustering along PC1.) TL99, piribedil, and talipexole migrated close to the latter group, whereas roxindole, cabergoline, bromocriptine, and pergolide were located near to lisuride and terguride. Superimposition of the 21 variables upon PC1 revealed that all were situated on, and contributed to, its leftward extension. This observation is in line with the high degree of correlation among pKi values (Table 8) and indicates that PC1 is a composite axis to which numerous variables cojointly contribute. Accordingly, the “loading values” (correlation coefficients) for the majority of variables onto PC1 were generally high, with hD2S/hD2L and hD1 receptors yielding the most pronounced values (Table 8). Consistent with the relatively low correlation coefficients of hD4 and H1 receptors to other variables, their participation in PC1 was minor. This is indicated in Table 8 by their comparatively modest loading values onto PC1. In line with the absence of negative correlation coefficients in the correlation matrix, no variables were located at the opposite extremity of PC1 (Figs. 4 and 5). This contribution of multiple variables to PC1 explains the important role of lisuride and terguride in its determination inasmuch as they presented high affinities for all receptors. In contrast, drugs located at the opposite extremity displayed modest or low affinities. Accordingly, other drugs were situated between the two limits of PC1 as a function of the magnitude of their overall affinities.

Figure 4
Figure 4

Hierarchical (cluster) classification of overall drug homology based upon binding profiles at all receptors. The database (pKi values) exploited for generation of the dendrograms is given in Tables 4 to 6. Note that the distance between two individual drugs is inversely proportional to their overall homology. That is, drugs situated adjacently present very similar binding profiles, whereas those widely separated show substantially different binding profiles. The chemical class of each drug is indicated.

Figure 5
Figure 5

“Radar” representations of the binding profiles of (closely related) pairs of drugs at certain receptor types. In each radar plot, the two drugs depicted show broadly similar profiles. Affinities are indicated in pKi values. Thus, the greater the distance from the central node of the radar plot, the higher the drug affinity for a specific binding site. Plots of quinpirole and quinelorane are not shown for reasons of space: they presented very similar profiles close to those of pramipexole and ropinirole.

Axis PC2 accounted for 6.5% of variance. In line with the comparatively low correlation coefficients of hD4and H1 sites versus hα1-AR subtypes (Table 7), they defined its two extremes. Accordingly, hD4/H1 sites and hα1-AR subtypes displayed, respectively, positive and negative loading values for this axis (Table 8). The location of bromocriptine at one limit of PC2 (Figs. 1 and 3) corresponds to its ∼1,000-fold lower affinity at H1 and D4 receptors versus α1-AR subtypes. Quinelorane and TL99 were dissociated from bromocriptine at the other extreme in line with their more pronounced affinity for H1 and hD4 versus hα1-AR subtypes. The other drugs were distributed in accordance with this schema.

PC3 contributed 5.1% of variance to the data. The projections of variables indicate that hβ2/hβ1-ARs and H1 receptors on the one hand, and hD5, h5-HT2A, and h5-HT2B receptors on the other, primarily underlay distribution of drugs along this axis. Correspondingly, the loading values of hβ2/hβ1-ARs and H1 receptors onto PC3 were ∼0.4 and positive, whereas those of h5-HT2A and hD5 receptors were similar but negative (Table8). The location of cabergoline and pergolide at one limit of the axis (Figs. 2 and 3) reflects, thus, their markedly (>100-fold) higher affinity for h5-HT2A and hD5 sites compared with H1 receptors and hβ1/hβ2-ARs. The position of lisuride at the opposite extreme, on the other hand, reflects its comparatively more pronounced affinity for hβ1- and hβ2-ARs as well as H1 receptors.

Hierarchical (Cluster) Analysis of Global Drug Homology.

From the dendrogram of overall drug homology generated by analysis of the total database, several drug clusters not apparent from inspection of the biplots could be recognized (Fig.4). It is pragmatic to comment the dendrogram in a direction opposite to that of its mathematical construction, and the most striking separation between drugs was at the first “node”, which yielded two major subdivisions.

The first major group comprised quinpirole, quinelorane, ropinirole, pramipexole, piribedil, and talipexole, whereas the second comprised lisuride, terguride, roxindole, bromocriptine, cabergoline, pergolide, TL99, and apomorphine. Compared with drugs in the second group, drugs in the first group displayed low affinities for multiple classes of 5-HT receptor, and low affinities for hD5compared with hD2S/hD2Lreceptors. Drugs in this first cluster also showed low affinity for hD1 and H1 receptors and negligible affinity for hβ1- and hβ2-ARs, although this feature was also seen in certain drugs in the second major cluster. Within the first group, a marked similarity was apparent between quinelorane and quinpirole, and between pramipexole and ropinirole, which comprised two closely related subclusters. The other two agents, piribedil and talipexole, could be distinguished by their more pronounced affinities at hα1-AR subtypes as well as at hα2A-ARs, hα2C-ARs, and, less markedly, hα2B-ARs.

Within the second major subdivision, lisuride and terguride revealed high affinities at all sites, notably, at h5-HT2Aand h5-HT2C receptors, all subtypes of dopamine receptor and hβ1- and hβ2-ARs. Roxindole and bromocriptine constituted a closely related subcluster showing a similar overall pattern of affinities, notably sharing high affinity for hα1-AR subtypes. Overall, roxindole showed higher affinities, although this difference was only marked for hD4 receptors. An additional pair of ligands displaying similar receptor binding profiles was formed by cabergoline and pergolide, with the former showing higher affinities at most sites. Both revealed low affinities for H1 receptors and hβ1- and hβ2-ARs. The final couple of closely related drugs was TL99 and apomorphine, which showed less pronounced affinities at most sites than other drugs in this division.

Radar Plots.

The radar representations of Fig.5 complement the dendrogram in exemplifying similarities and differences among various drugs at specific receptor types discussed above.

Discussion

hD2S and hD2L Receptors.

Although benzamides display contrasting affinities at hD2Lcompared with hD2S receptors, other classes of antagonist show similar affinity; likewise, all agonists examined to date (including several antiparkinsonian agents) revealed comparable affinities for these sites (Leysen et al., 1993). The present observations extend such reports in demonstrating similar affinities of numerous antiparkinson drugs at hD2S versus hD2L sites. Such information is important because 1) D2S versus D2L sites present differential patterns of post-translational processing, coupling, regulation, and localization; 2) D2Sautoreceptors modulate DA release and may contribute to neuroprotective properties of antiparkinson agents; and 3) postsynaptic D2S and (predominant) hD2Lsites, perhaps via contrasting interactions with D1 receptors, differentially control motor function (Zou et al., 1999; Usiello et al., 2000).

hD3 and hD4 Receptors.

Comparisons of affinities at hD3 versus hD2 sites should be made cautiously in the light of multiple affinity states of the latter (Mierau et al., 1995;Coldwell et al., 1999; Perachon et al., 1999). Nevertheless, the high potency of all agents for hD3 sites underscores their potential relevance to beneficial and/or undesirable properties of antiparkinson drugs (Millan et al., 2000b; Joyce, 2001). The modest correlation coefficients of hD4 to hD2S/hD2L/hD3receptors indicate distinctive structure-activity relationships, in line with the discovery of many selective hD4receptor antagonists. Bromocriptine and piribedil displayed modest affinity, and antagonist properties (Newman-Tancredi et al., 2002a), at hD4 receptors indicating, as discussed elsewhere, that their stimulation is not mandatory for clinical efficacy (Rondot and Ziegler, 1992; Jenner, 1995; Newman-Tancredi et al., 1997). Indeed, blockade of D4 receptors may improve cognitive-attentional processing (Oak et al., 2000).

hD1 and hD5 Receptors.

Surprisingly, affinities were well correlated between hD1 and hD2S/hD2L sites, suggesting that structure-activity relationships are less distinct than might be imagined. Joint D1/D2receptor stimulation may improve therapeutic efficacy for drugs such as apomorphine and pergolide (Jenner, 1995; Markham and Benfield, 1997;Perachon et al., 1999; Aizman et al., 2000). Functional interactions among (partially colocalized) D1 and D3 receptors are also of importance in the actions of l-DOPA and other antiparkinson agents (Karasinska et al., 2000; Joyce, 2001). Nevertheless, the low affinities of clinically effective drugs, such as pramipexole and ropinirole, at hD1 sites support the notion that their engagement is not requisite for therapeutic efficacy. Although we corroborate the preference of apomorphine for hD5versus hD1 sites (Sunahara et al., 1991;Demchyshyn et al., 2000), we found (∼5-fold) higher affinities of apomorphine, bromocriptine, lisuride, and pergolide at hD5 receptors compared with these studies. One factor underlying this difference may be the use of Chinese hamster ovary versus COS-7 cells. Indeed, Kimura et al. (1995) (using GH4C1 cells) similarly concluded that the cell line confers distinctive binding properties to hD1 and hD5 receptors. D5 sites are of significance in several respects: 1) multivariate analyses revealed that hD5 affinities discriminate antiparkinson agents; 2) D5 receptors are situated on striatal dopaminergic, cholinergic, and GABAergic neurons (Ciliax et al., 2000); and 3) antisense probes against D5 and D1 receptors potentiated and inhibited, respectively, induction of rotation by D1/D5 agonists in unilateral substantia nigra-lesioned rats (Dziewczapolski et al., 1998). Differential modulation of motor function is supported by the contrasting phenotypes of mice lacking D5 versus D1 receptors and their distinctive patterns of localization (Sibley, 1999; Ciliax et al., 2000).

hα2 and hα1-ARs.

The observations herein amplify isolated studies (Uitti and Ahlskog, 1996) of antiparkinson agents at rα1- and rα2-ARs in demonstrating that many recognize hα1- and hα2-AR subtypes. The present data thus complement reports of the weak (agonist) interaction of pramipexole with rα2-ARs (Mierau et al., 1995) and of actions of apomorphine and bromocriptine at hippocampal rα2-ARs (Jackisch et al., 1985). Furthermore, the high affinity of TL99 for hα2-AR subtypes amplifies observations with native rα2-ARs (Martin et al., 1983). Of particular interest, whereas talipexole behaves as an agonist at α2-ARs (Meltzer et al., 1989), piribedil manifests antagonist properties. Correspondingly, in contrast to talipexole, piribedil reinforces corticolimbic adrenergic and cholinergic transmission (Millan et al., 2000c, 2001a;Gobert et al., 2002), actions contributing to its favorable influence upon cognitive function and mood (Brefel-Courbon et al., 1998; Bezard et al., 2001; Maurin et al., 2001; Nagaraja and Jayashree, 2001). Extending work with native α1-ARs, bromocriptine, lisuride, terguride, and roxindole displayed high affinities at hα1-AR subtypes (McPherson and Beart, 1983; Uitti and Ahlskog, 1996). Potent blockade of α1-ARs may interfere with the influence of antiparkinson agents upon motor performance and perturb cardiovascular function (Hieble et al., 1995; Millan et al., 2000).

hβ1 and hβ2-ARs.

The finding that several drugs recognize hβ1- and hβ2-ARs is of interest. First, β1/β2-ARs are excitatory to corticostriatal glutamatergic afferents (Niittykoski et al., 1999). Second, they activate dopaminergic, adrenergic, and serotonergic pathways in cortex and nucleus accumbens (Millan et al., 2000; Tuinstra and Cools, 2000). Third, stimulation of β1/β2-ARs enhances cognitive function and improves mood (O'Donnell et al., 1994). Fourth, stimulation and blockade of central β1/β2-ARs elicits and blocks tremor, respectively (Wilms et al., 1999).

h5-HT Receptors.

Although all ligands showed some affinity for h5-HT1A receptors, extending studies of native sites (Uitti and Ahlskog, 1996), marked differences among antiparkinson agents were seen at 5-HT2 receptor subtypes. High affinities of lisuride, terguride, cabergoline, and pergolide at h5-HT2A (and h5-HT2C) receptors underpin studies showing that ergot-related compounds interact with native “5-HT2” receptors (Beart et al., 1986; Uitti and Ahlskog, 1996; Markham and Benfield, 1997;Fariello, 1998). Interestingly, their marked serotonergic affinities were mimicked by the structurally distinct roxindole and apomorphine (Uitti and Ahlskog, 1996; Newman-Tancredi et al., 1999). Actions of antiparkinson drugs at 5-HT2A/2C sites may, as discussed in the accompanying article (Newman-Tancredi et al., 2002b), influence motor function and mood.

H1 and Muscarinic Receptors.

Lisuride interacts with rat H1 sites (Beart et al., 1986), an observation extended here to a further species and other drugs. Such actions at H1 receptors are of potential importance. First, H1 receptors modulate motor function, and inhibit and enhance striatal dopaminergic and cholinergic transmission, respectively (Bacciottini et al., 2001; Brown et al., 2001). Second, they influence arousal and cognition (Brown et al., 2001). Third, H1 receptor blockade encourages sleep and elicits sedation, a troublesome symptom of treated and untreated parkinsonian patients (Brown et al., 2001; Friedman and Factor, 2000). Fourth, rats sustaining 6-hydroxydopamine lesions of the substantia nigra and Parkinson's Disease patients show an increase in striatal histaminergic innervation (Anichtchik et al., 2000). Reflecting functional interplay among dopaminergic and cholinergic networks in basal ganglia, muscarinic antagonists suppress tremor and dyskinesias provoked by l-DOPA, although side effects compromise their utilization (Wilms et al., 1999; Bezard et al., 2001). However, antiparkinson agents tested herein did not occupy cloned, human M1 receptors (for all drugs, pKi values of <6.0).

Hierarchical (Cluster) Analysis.

High versus low affinities at multiple 5-HT and hD5 receptors underpinned a major subdivision of agents into two groups. This association is intriguing because “selective” hD1/hD5 receptor ligands show pronounced affinity for h5-HT2A and h5-HT2C receptors (Millan et al., 2001b). Of drugs not interacting with serotonergic receptors, the data support experimental use of quinpirole and quinelorane as selective D2-like receptor agonists. Furthermore, inasmuch as the receptor profiles of ropinirole and pramipexole were very similar, they should display common functional effects distinguishable from those of cabergoline and roxindole and from older agents such as bromocriptine and apomorphine. As regards piribedil and talipexole, which likewise recognized dopaminergic but not serotonergic receptors, it is important to emphasize their opposite antagonist and agonist properties at α2-ARs, respectively; indeed, piribedil seems to be unique in simultaneously activating D2/D3 receptors and blocking α2-ARs without markedly interacting with 5-HT receptors (Newman-Tancredi et al., 2002a,b). On the contrary, among ligands with pronounced serotonergic properties, cabergoline and roxindole were remarkably similar to pergolide and bromocriptine, respectively. Terguride and TL99, on the other hand, closely resembled lisuride and apomorphine, respectively. Certain closely related drugs possess similar structures, for example, pergolide and cabergoline. However, ropinirole/pramipexole and piribedil/talipexole presented similar binding profiles despite their chemical distinctiveness. Thus, chemical structure does not provide a satisfactory basis for prediction of receptor binding profiles.

Principal Component Analysis.

The compound nature of PC1, which accounted for 76% variance, reflects marked correlation among receptors. That is, with the exception of hD4 and H1 receptors, all receptor types made a pronounced contribution to PC1 (Table 8). In accordance with its generally high affinity, lisuride defined one extremity of PC1 in distinction to drugs of modest affinity, such as quinpirole, which migrated at the opposite limit. PC2 and PC3, nevertheless, proved discriminant in dissociating bromocriptine from TL99 based on low and high affinities, respectively, for H1/hD4 receptors versus α1-ARs. Furthermore, cabergoline was located at one limit of PC3 on the basis of higher affinity for hD5 and h5-HT2A versus hβ1/hβ2-ARs and H1 receptors, whereas lisuride (high affinity at β1/β2-ARs and H1 receptors) defined the opposite extremity. Thus, PCA identified several receptors contributing to diversity in the binding profiles of antiparkinson agents. Within this framework, PCA also provided insights into relationships among the drug themselves as a function of their affinities at above-mentioned and other sites. For example, reflecting their pronounced affinities for virtually all sites, lisuride and terguride comprised a subset of drugs (clustered together) when projected onto PC1, PC2, and PC3, whereas piribedil and talipexole were likewise adjacent to each other across all PCs, corresponding to their mixed dopaminergic-adrenergic profiles in the absence of serotonergic affinities.

General Discussion.

Several general features of this novel multivariate approach should be evoked. First, although multivariate techniques have been used for evaluation of biochemical abnormalities in schizophrenia (Carlsson et al., 2001) and characterization of drug pharmacokinetic profiles (Ette et al., 2001), this is their first systematic utilization for characterization of drug receptor-binding profiles. Whereas pairwise drug/drug and site/site comparisons can be misleading, multivariate strategies simultaneously analyze the entire database in a multidimensional space permitting hypothesis-free exploration of similarities and differences as a function of overall binding profiles. Although both drugs and variables must be selected, substantial databases (as herein) minimize the risk that an involuntary “bias” may distort analyses. Second, a precondition for multivariate procedures is a homogeneous and extensive database incorporating many variables and drugs. Although onerous to generate, the database can be subsequently exploited for studies of other drugs under equivalent conditions. For example, in the search for antiparkinson agents presenting novel, binding profiles differing from known agents. Third, integration of in vivo parameters would be of considerable interest (Millan et al., 2000). Fourth, multivariate analyses assume that drugs behave in an identical manner at specific receptor types. This is appropriate for structure-activity relationships focusing on drug potency but neglects potential differences in efficacy. This important issue was addressed by investigations of coupling (Newman-Tancredi et al., 2002a,b), although currently, there is no solution to the integration of contrasting drug actions (agonist versus antagonist properties) into multivariate analyses. Fifth, similarities and differences in overall binding profiles of drugs provide a framework for interpretation of their contrasting functional profiles in vivo. Multivariate analyses facilitate, thus, predictions of the beneficial and deleterious actions of novel drugs and would be most appropriately performed before their therapeutic evaluation. Indeed, it would be of considerable interest to undertake direct therapeutic comparisons of drugs possessing contrasting receptorial profiles, for example, of antiparkinson agents behaving essentially as dopaminergic agonists compared with those displaying pronounced activity at serotonergic and/or adrenergic receptors. In focusing on specific parameters, such as dyskinesias, depressive symptoms, and memory, such studies could provide key clinical information concerning the drugs in question and, more generally, clarify the significance of particular classes of monoaminergic receptor in the control of motor function, cognition, and mood in Parkinson's disease.

Concluding Comments.

This comprehensive, multivariate analysis of binding profiles of diverse antiparkinson agents revealed marked and unexpected heterogeneity, a conclusion amplified by efficacy studies (Newman-Tancredi et al., 2002a,b). These observations of similarities and differences among antiparkinson agents provide a framework for improved interpretation of their experimental and clinical actions, and for a more thorough understanding of the functional significance of individual classes of monoaminergic receptor in Parkinson's disease. A multivariate strategy could instructively be applied to other agents, such as antidepressants and antipsychotics, for which actions at multiple classes of receptor are likewise critical in determining their functional profiles.

Acknowledgments

We thank M. Soubeyran for secretarial assistance, and V. Pasteau, L. Verrièle, L. Marini, C. Chaput, M. Touzard, and V. Dubreuil for technical assistance.

Footnotes

  • ↵1 Rat α2D-ARs are the rodent homolog of human hα2A-ARs, to which they show marked differences as concerns affinities of certain drug classes (Hieble et al., 1995).

  • ↵2 A more detailed discussion of the actions of drugs at hD2S, hD2L, hD3, and hD4 receptors, multiple classes of α1- and α2-AR and multiple subtypes of 5-HT receptor is to be found in the accompanying articles, which document drug efficacies at these sites.

  • DOI: 10.1124/jpet.102.039867

  • Abbreviations:
    DA
    dopamine
    l-DOPA
    l-dihydroxyphenylacetic acid
    h
    human
    AR
    adrenoceptor
    5-HT
    5-hydroxytryptamine
    TL99
    6,7-dihydroxy-N,N-dimethyl-2-ammotetralin
    H
    histamine
    M1
    muscarinic
    PCA
    principle component analysis
    PC
    principle component
    • Received June 12, 2002.
    • Accepted July 22, 2002.

References

  1. ↵
    1. Aizman O,
    2. Brismar H,
    3. Uhlen P,
    4. Zettergren E,
    5. Levey AI,
    6. Forssberg H,
    7. Greengard P,
    8. Aperia A
    (2000) Anatomical and physiological evidence for D1 and D2 dopamine receptor colocalization in neostriatal neurons. Nat Neurosci 3:226–230.
    OpenUrlCrossRefPubMed
  2. ↵
    1. Anichtchik OV,
    2. Rinne JO,
    3. Kalimo H,
    4. Panula P
    (2000) An altered histaminergic innervation of the substantia nigra in Parkinson's disease. Exp Neurol 163:20–30.
    OpenUrlCrossRefPubMed
  3. ↵
    1. Bacciottini L,
    2. Passami MB,
    3. Mannaioni PF,
    4. Blandina P
    (2001) Interactions between histaminergic and cholinergic systems in learning and memory. Behav Brain Res 124:183–194.
    OpenUrlCrossRefPubMed
  4. ↵
    1. Beart PM,
    2. McDonald D,
    3. Cincotta M,
    4. De Vries DJ,
    5. Gundlach AL
    (1986) Selectivity of some ergot derivatives for 5-HT1 and 5-HT2 receptors of rat cerebral cortex. Gen Pharmacol 17:57–62.
    OpenUrlPubMed
  5. ↵
    1. Bezard E,
    2. Brotchie JM,
    3. Gross CE
    (2001) Pathophysiology of l-Dopa-induced dyskinesia: potential for new therapies. Nat Rev Neurosci 2:577–588.
    OpenUrlCrossRefPubMed
  6. ↵
    1. Brefel-Courbon C,
    2. Thalamas C,
    3. Peyro-Saint-Paul H,
    4. Senard JM,
    5. Montastruc JL,
    6. Rascol O
    (1998) α2-Adrenoceptor antagonists: a new approach to Parkinson's disease. CNS Drugs 10:189–207.
    OpenUrlCrossRef
  7. ↵
    1. Brown RE,
    2. Stevens DR,
    3. Haas HL
    (2001) The physiology of brain histamine. Prog Neurobiol 63:637–672.
    OpenUrlCrossRefPubMed
  8. ↵
    1. Carlsson A,
    2. Waters N,
    3. Holm-Waters S,
    4. Tedroff J,
    5. Nilsson M,
    6. Carlsson ML
    (2001) Interactions between monoamines, glutamate and GABA in schizophrenia: new evidence. Annu Rev Pharmacol 41:237–260.
    OpenUrlCrossRefPubMed
  9. ↵
    1. Ciliax BJ,
    2. Nash N,
    3. Heilman C,
    4. Sunahara R,
    5. Bartney A,
    6. Tiberi M,
    7. Rye DB,
    8. Caron MG,
    9. Niznik HB,
    10. Levey AI
    (2000) Dopamine D5 receptor immunolocalization in rat and monkey brain. Synapse 37:125–145.
    OpenUrlCrossRefPubMed
  10. ↵
    1. Coldwell MC,
    2. Boyfield I,
    3. Brown T,
    4. Hagan JJ,
    5. Middlemiss DN
    (1999) Comparison of the functional potencies of ropinirole and other dopamine receptor agonists in human D2(long), D3 and D4.4 receptors expressed in chinese hamster ovary cells. Br J Pharmacol 127:1696–1702.
    OpenUrlCrossRefPubMed
  11. ↵
    1. Demchyshyn LL,
    2. McConkey F,
    3. Niznik HB
    (2000) Dopamine D5 receptor agonist high affinity and constitutive activity profile conferred by carboxyl-terminal tail sequence. J Biol Chem 275:23446–23455.
    OpenUrlAbstract/FREE Full Text
  12. ↵
    1. Dziewczapolski G,
    2. Menalled LB,
    3. Garcia MC,
    4. Mora MA,
    5. Gershanik OS,
    6. Rubinstein M
    (1998) Opposite roles of D1 and D5 dopamine receptors in locomotion revealed by selective antisense oligonucleotides. Neuroreport 9:1–5.
    OpenUrlPubMed
  13. ↵
    1. Ette EI,
    2. Williams P,
    3. Sun H,
    4. Fadiran E,
    5. Ajayi FO,
    6. Onyiah LC
    (2001) The process of knowledge discovery from large pharmacokinetic data sets. J Clin Pharmacol 41:25–34.
    OpenUrlCrossRefPubMed
  14. ↵
    1. Fariello RG
    (1998) Pharmacodynamic and pharmacokinetic features of cabergoline. Drugs 56:10–16.
  15. ↵
    1. Friedman JH,
    2. Factor SA
    (2000) Atypical antipsychotics in the treatment of drug-induced psychosis in Parkinson's disease. Mov Disord 15:201–211.
    OpenUrlCrossRefPubMed
  16. ↵
    1. Gobert A,
    2. Di Cara B,
    3. Cistarelli L,
    4. Millan MJ
    (2002) The antiparkinsonian agent, piribedil, increases extracellular levels of acetylcholine (ACh) in frontal cortex of freely-moving rats: a dialysis study in the absence of cholinesterase inhibitors. 32th Society for Neuroscience Meeting (USA), in press.
  17. ↵
    1. Gulwadi AG,
    2. Korpinen CD,
    3. Mailman RB,
    4. Nichols DE,
    5. Sit SY,
    6. Taber MT
    (2001) Dinapsoline: characterization of a D1 dopamine receptor agonist in a rat model of Parkinson's disease. J Pharmacol Exp Ther 296:338–344.
    OpenUrlAbstract/FREE Full Text
  18. ↵
    1. Hieble JP,
    2. Bondinell WE,
    3. Ruffolo RR
    (1995) α- and β-Adrenoceptors: from the gene to the clinic. 1. Molecular biology and adrenoceptor subclassification. J Med Chem 38:3416–3442.
    OpenUrl
  19. ↵
    1. Horn AS,
    2. De Vries J,
    3. Dijkstra D,
    4. Mulder AH
    (1982) Is TL-99 a selective presynaptic dopamine receptor agonist. Eur J Pharmacol 83:35–45.
    OpenUrlCrossRefPubMed
  20. ↵
    1. Jackisch R,
    2. Moll S,
    3. Feuerstein TJ,
    4. Hertting G
    (1985) Dopaminergic modulation of hippocampal noradrenaline release. Naunyn-Schmiedeberg's Arch Pharmacol 330:105–113.
    OpenUrlCrossRefPubMed
  21. ↵
    1. Jackson DM,
    2. Mohell N,
    3. Georgiev J,
    4. Bengtsson A,
    5. Larsson LG,
    6. Magnusson O,
    7. Ross SB
    (1995) Time course of bromocriptine induced excitation in the rat: behavioural and biochemical studies. Naunyn-Schmiedeberg's Arch Pharmacol 351:146–155.
    OpenUrlPubMed
  22. ↵
    1. Jellinger KA
    (1999) Post mortem studies in Parkinson's disease - is it possible to detect brain areas for specific symptoms. J Neural Transm 56:1–29.
  23. ↵
    1. Jenner P
    (1995) The rationale for the use of dopamine agonists in Parkinson's disease. Neurology 45:S6–S12.
    OpenUrlCrossRefPubMed
  24. ↵
    1. Joyce JN
    (2001) Dopamine D3 receptors as a therapeutic target for antipsychotic and antiparkinsonian drugs. Pharmacol Ther 90:231–259.
    OpenUrlCrossRefPubMed
  25. ↵
    1. Karasinska JM,
    2. George SR,
    3. El-Ghundi M,
    4. Fletcher PJ,
    5. O'Dowd BF
    (2000) Modification of dopamine D1 receptor knockout phenotype in mice lacking both dopamine D1 and D3 receptors. Eur J Pharmacol 399:171–181.
    OpenUrlCrossRefPubMed
  26. ↵
    1. Kimura K,
    2. Sela S,
    3. Bouvier C,
    4. Grandy DK,
    5. Sidhu A
    (1995) Differential coupling of D1 and D5 dopamine receptors to guanine nucleotide binding proteins in transfected GH4C1 rat somatomammotrophic cells. J Neurochem 64:2118–2124.
    OpenUrlPubMed
  27. ↵
    1. Krzanowski WJ
    (2000) Principles of multivariate analysis. Oxford Statistical Sci Series 22:1–586.
  28. ↵
    1. Leysen JE,
    2. Gommeren W,
    3. Mertens J,
    4. Luyten WHML,
    5. Pauwels PJ,
    6. Ewert M,
    7. Seeburg P
    (1993) Comparison of in vitro binding properties of a series of dopamine antagonists and agonists for cloned human dopamine D2S and D2L receptors and for D2 receptors in rat striatal and mesolimbic tissues using [125I] 2′-iodospiperone. Psychopharmacology 110:27–36.
    OpenUrlCrossRefPubMed
  29. ↵
    1. Markham A,
    2. Benfield P
    (1997) Pergolide: a review of its pharmacology and therapeutic use in Parkinson's disease. CNS Drugs 7:328–340.
    OpenUrlCrossRef
  30. ↵
    1. Martin GE,
    2. Jones JH,
    3. Bendesky RJ
    (1983) Different actions of TL-99 and 3-PPP in producing contraversive turning in the 6-OHDA-lesioned rat. Eur J Pharmacol 92:275–278.
    OpenUrlCrossRefPubMed
  31. ↵
    1. Maurin B,
    2. Baunez C,
    3. Bonhomme C,
    4. Chezaubernard C,
    5. Nieoullon A,
    6. Amalric M
    (2001) Cognitive deficits in 6-OHDA lesioned rats are improved by chronic treatment with the dopamine agonist piribedil. Behav Pharmacol 12:S63.
    OpenUrl
  32. ↵
    1. McPherson GA,
    2. Beart A
    (1983) The selectivity of some ergot derivatives for α1- and α2-adrenoceptors of rat cerebral cortex. Eur J Pharmacol 91:363–369.
    OpenUrlCrossRefPubMed
  33. ↵
    1. Meltzer LT,
    2. Wiley JN,
    3. Heffner TG
    (1989) The α2-adrenoceptor antagonists idazoxan and yohimbine can unmask the postsynaptic dopamine agonist effects of B-HT 920. Eur J Pharmacol 170:105–107.
    OpenUrlCrossRefPubMed
  34. ↵
    1. Meneses A
    (1999) 5-HT system and cognition. Neurosci Biobehav Rev 23:1111–1125.
    OpenUrlCrossRefPubMed
  35. ↵
    1. Mierau J,
    2. Schneider FJ,
    3. Ensinger HA,
    4. Chio CL,
    5. Lajiness ME,
    6. Huff RM
    (1995) Pramipexole binding and activation of cloned and expressed dopamine D2, D3 and D4 receptors. Eur J Pharmacol 290:29–36.
    OpenUrlCrossRefPubMed
  36. ↵
    1. Millan MJ,
    2. Brocco M,
    3. Rivet JM,
    4. Audinot V,
    5. Newman-Tancredi A,
    6. Maiofiss L,
    7. Queriaux S,
    8. Despaux N,
    9. Peglion JP,
    10. Dekeyne A
    (2000a) S18327 (1-{2-[4-(6-fluoro-1,2-benzisoxazol-3-yl)piperid-1-yl}3-phenyl imidazolin-2-one), a novel, potential antipsychotic displaying marked antagonist properties at α1- and α2-adrenergic receptors: II. Functional profile and a multiparametric comparison with haloperidol, clozapine and 11 other antipsychotic agents. J Pharmacol Exp Ther 292:54–66.
    OpenUrlAbstract/FREE Full Text
  37. ↵
    1. Millan MJ,
    2. Cussac D,
    3. Milligan G,
    4. Carr C,
    5. Audinot V,
    6. Gobert A,
    7. Lejeune F,
    8. Rivet JM,
    9. Brocco M,
    10. Duqueyroix D,
    11. Nicolas JP,
    12. Boutin JA,
    13. Newman-Tancredi A
    (2001a) Antiparkinson agent piribedil displays antagonist properties at native, rat and cloned, human α 2-adrenoceptors: cellular and functional characterization. J Pharmacol Exp Ther 297:876–887.
    OpenUrlAbstract/FREE Full Text
  38. ↵
    1. Millan MJ,
    2. Dekeyne A,
    3. Rivet JM,
    4. Dubuffet T,
    5. Lavielle G,
    6. Brocco M
    (2000b) S33084, A novel, potent, selective and competitive antagonist at dopamine D3-receptors: II. Functional and behavioral profile compared with GR218,231 and L741,626. J Pharmacol Exp Ther 293:1063–1073.
    OpenUrlAbstract/FREE Full Text
  39. ↵
    1. Millan MJ,
    2. Lejeune F,
    3. Gobert A
    (2000c) Reciprocal autoreceptor and heteroreceptor control of serotonergic, dopaminergic and noradrenergic transmission in the frontal cortex: relevance to the actions of antidepressant agents. J Psychopharmacol 14:114–138.
    OpenUrlAbstract/FREE Full Text
  40. ↵
    1. Millan MJ,
    2. Newman-Tancredi A,
    3. Quentric Y,
    4. Cussac D
    (2001b) The “selective” dopamine D1 receptor antagonist, SCH23390, is a potent and high efficacy agonist at cloned human serotonin2C receptors. Psychopharmacology 156:58–62.
    OpenUrlCrossRefPubMed
  41. ↵
    1. Montastruc JL,
    2. Rascol O,
    3. Senard JM
    (1999) Treatment of Parkinson's disease should begin with a dopamine agonist. Mov Disord 14:725–730.
    OpenUrlCrossRefPubMed
  42. ↵
    1. Nagaraja D,
    2. Jayashree S
    (2001) Randomized study of the dopamine receptor agonist piribedil in the treatment of mild cognitive impairment. Am J Psychiatry 158:1517–1519.
    OpenUrlCrossRefPubMed
  43. ↵
    1. Newman-Tancredi A,
    2. Audinot V,
    3. Chaput C,
    4. Verrièle L,
    5. Millan MJ
    (1997) [35S]Guanosine 5′-O-(3-thio)triphosphate binding as a measure of efficacy at human recombinant dopamine D4.4 receptors: actions of antiparkinson and antipsychotic agents. J Pharmacol Exp Ther 282:181–191.
    OpenUrlAbstract/FREE Full Text
  44. ↵
    1. Newman-Tancredi A,
    2. Cussac D,
    3. Audinot V,
    4. Millan MJ
    (1999) Actions of roxindole at recombinant human dopamine D2, D3 and D4 and serotonin 5-HT1A, 5-HT1B and 5-HT1D receptors. Naunyn-Schmiedeberg's Arch Pharmacol 359:447–453.
    OpenUrlCrossRefPubMed
  45. ↵
    1. Newman-Tancredi A,
    2. Cussac D,
    3. Audinot V,
    4. Nicolas JP,
    5. De Ceuninck F,
    6. Boutin JA,
    7. Millan MJ
    (2002a) Differential actions of antiparkinson agents at multiple classes of monoaminergic receptor. II. Agonist and antagonist properties at subtypes of dopamine “D2-like receptor' and α1/α2-adrenoceptor. J Pharmacol Exp Ther 303:805–814.
    OpenUrlAbstract/FREE Full Text
  46. ↵
    1. Newman-Tancredi A,
    2. Cussac D,
    3. Quentric Y,
    4. Touzard M,
    5. Verrièle L,
    6. Carpentier N,
    7. Millan MJ
    (2002b) Differential actions of antiparkinson agents at multiple classes of monoaminergic receptor. III. Agonist and antagonist properties at serotonin, 5-HT1 and 5-HT2, receptor subtypes. J Pharmacol Exp Ther 303:815–822.
    OpenUrlAbstract/FREE Full Text
  47. ↵
    1. Niittykoski M,
    2. Ruotsalainen S,
    3. Haapalinna A,
    4. Larson J,
    5. Sirviö J
    (1999) Activation of muscarinic M3-like receptors and β-adrenoceptors, but not M2-like muscarinic receptors or α1-adrenoceptors, directly modulates corticostriatal neurotransmission in vitro. Neuroscience 90:95–105.
    OpenUrlCrossRefPubMed
  48. ↵
    1. Oak JN,
    2. Oldenhof J,
    3. Van Tol HHM
    (2000) The dopamine D4 receptor: one decade of research. Eur J Pharmacol 405:303–327.
    OpenUrlCrossRefPubMed
  49. ↵
    1. O'Donnell J,
    2. Frith S,
    3. Wilkins J
    (1994) Involvement of beta-1 and beta-2 adrenergic receptors in the antidepressant-like effects of centrally administered isoproterenol. J Pharmacol Exp Ther 271:246–254.
    OpenUrlAbstract/FREE Full Text
  50. ↵
    1. Perachon S,
    2. Schwartz JC,
    3. Sokoloff P
    (1999) Functional potencies of new antiparkinson drugs at recombinant human dopamine D1, D2 and D3 receptors. Eur J Pharmacol 366:293–300.
    OpenUrlCrossRefPubMed
  51. ↵
    1. Rascol O,
    2. Brooks DJ,
    3. Korczyn AD,
    4. De Deyn PP,
    5. Clarke CE,
    6. Lang AE
    (2000) A five-year study of the incidence of dyskinesia in patients with early Parkinson's disease who were treated with ropirinole or levodopa. N Engl J Med 18:1484–1491.
  52. ↵
    1. Rondot P,
    2. Ziegler M
    (1992) Activity and acceptability of Trivastal in Parkinson's disease: a multicenter study. J Neurol 239:528–534.
    OpenUrl
  53. ↵
    1. Sibley DR
    (1999) New insights into dopaminergic receptor function using antisense and genetically altered animals. Annu Rev Toxicol 39:313–341.
  54. ↵
    1. Sunahara RK,
    2. Guan HC,
    3. O'Dowd BF,
    4. Seeman P,
    5. Laurier LG,
    6. Ng G,
    7. Goerge SR,
    8. Torchia J,
    9. Van Tol HHM,
    10. Niznik HB
    (1991) Cloning of the gene for a human dopamine D5 receptor with higher affinity for dopamine than D1. Nature (Lond) 350:614–619.
    OpenUrlCrossRefPubMed
  55. ↵
    1. Tuinstra T,
    2. Cools AR
    (2000) Newly synthesized dopamine in the nucleus accumbens is regulated by β-adrenergic, but not α-adrenergic, receptors. Neuroscience 98:743–747.
    OpenUrlCrossRefPubMed
  56. ↵
    1. Uitti RJ,
    2. Ahlskog JE
    (1996) Comparative review of dopamine receptor agonists in Parkinson's disease. CNS Drugs 5:369–388.
    OpenUrlCrossRef
  57. ↵
    1. Usiello A,
    2. Baik JH,
    3. Rougé-Pont F,
    4. Picetti R,
    5. Dierich A,
    6. LeMeur M,
    7. Piazza PV,
    8. Borrelli E
    (2000) Distinct functions of the two isoforms of dopamine D2 receptors. Nature (Lond) 408:199–203.
    OpenUrlCrossRefPubMed
  58. ↵
    1. Weddell RA,
    2. Weiser R
    (1995) A double-blind cross-over placebo-controlled trial of the effects of bromocriptine on psychomotor function, cognition and mood in de novo patients with Parkinson's disease. Behav Pharmacol 6:81–91.
    OpenUrlCrossRefPubMed
  59. ↵
    1. Wilms H,
    2. Sievers J,
    3. Deuschl G
    (1999) Animal models of tremor. Mov Disord 14:557–571.
    OpenUrlCrossRefPubMed
  60. ↵
    1. Zou L,
    2. Jankovic J,
    3. Rowe DB,
    4. Xie W,
    5. Appel SH,
    6. Le W
    (1999) Neuroprotection by pramipexole against dopamine and levodopa-induced cytotoxicity. Life Sci 64:1275–1285.
    OpenUrlCrossRefPubMed
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Research ArticleNEUROPHARMACOLOGY

Differential Actions of Antiparkinson Agents at Multiple Classes of Monoaminergic Receptor. I. A Multivariate Analysis of the Binding Profiles of 14 Drugs at 21 Native and Cloned Human Receptor Subtypes

Mark J. Millan, Lisa Maiofiss, Didier Cussac, Valérie Audinot, Jean-A. Boutin and Adrian Newman-Tancredi
Journal of Pharmacology and Experimental Therapeutics November 1, 2002, 303 (2) 791-804; DOI: https://doi.org/10.1124/jpet.102.039867
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