N-n-alkylnicotinium analogs, a novel class of nicotinic receptor antagonists: Interaction with α4β2* and α7* Neuronal nicotinic receptors

Article abstract of DOI:10.1124/jpet.102.043349

The current study demonstrates that N-n-alkylnicotinium analogs with increasing n-alkyl chain lengths from 1 to 12 carbons have varying affinity (K_i = 90 nM-20 μM) for S-(-)-[³H]nicotine binding sites in rat striatal membranes. A linear relationship was observed such that increasing n-alkyl chain length provided increased affinity for the α4β2* nicotinic acetylcholine receptor (nAChR) subtype, with the exception of N-n-octylnicotinium iodide (NONI). The most potent analog was N-n-decylnicotinium iodide (NDNI; K_i = 90 nM). In contrast, none of the analogs in this series exhibited high affinity for the [³H]methyllycaconitine binding site, thus indicating low affinity for the α7* nAChR. The C₈ analog, NONI, had low affinity for S-(-)-[³H]nicotine binding sites but was a potent inhibitor of S-(-)-nicotine-evoked [³H]dopamine (DA) overflow from superfused striatal slices (IC₅₀ = 0.62 μM), thereby demonstrating selectivity for the nAChR subtype mediating S-(-)-nicotine-evoked [³H]DA overflow (α3α6β2* nAChRs). Importantly, the N-n-alkylnicotinium analog with highest affinity for the α4β2* subtype, NDNI, lacked the ability to inhibit S-(-)-nicotine-evoked [³H]DA overflow and, thus, appears to be selective for α4β2* nAChRs. Furthermore, the present study demonstrates that the interaction of these analogs with the α4β2* subtype is via a competitive mechanism. Thus, selectivity for the α4β2* subtype combined with competitive interaction with the S-(-)-nicotine binding site indicates that NDNI is an excellent candidate for studying the structural topography of α4β2* agonist recognition binding sites, for identifying the antagonist pharmacophore on the α4β2* nAChR, and for defining the role of this subtype in physiological function and pathological disease states.

Full text of DOI:10.1124/jpet.102.043349

0022-3565/03/3041-400–410$7.00
THE JOURNAL OF PHARMACOLOGY AND EXPERIMENTAL THERAPEUTICS
Copyright © 2003 by The American Society for Pharmacology and Experimental Therapeutics
JPET 304:400–410, 2003
Vol. 304, No. 1
43349/1030966
Printed in U.S.A.
N-n-Alkylnicotinium Analogs, a Novel Class of Nicotinic
Receptor Antagonists: Interaction with ␣4␤2* and ␣7* Neuronal
Nicotinic Receptors
LINCOLN H. WILKINS, JR., VLADIMIR P. GRINEVICH,1 JOSHUA T. AYERS,2 PETER A. CROOKS, and LINDA P. DWOSKIN
College of Pharmacy, University of Kentucky, Lexington, Kentucky
Received August 16, 2002; accepted September 20, 2002
ABSTRACT
The current study demonstrates that N-n-alkylnicotinium ana- the nAChR subtype mediating S-(Ϫ)-nicotine-evoked [3H]DA
logs with increasing n-alkyl chain lengths from 1 to 12 carbons overflow (␣3␣6␤2* nAChRs). Importantly, the N-n-alkylnico-
have varying affinity (Ki ϭ 90 nM–20 ␮M) for S-(Ϫ)-[3H]nicotine tinium analog with highest affinity for the ␣4␤2* subtype, NDNI,
binding sites in rat striatal membranes. A linear relationship was lacked the ability to inhibit S-(Ϫ)-nicotine-evoked [3H]DA over-
observed such that increasing n-alkyl chain length provided flow and, thus, appears to be selective for ␣4␤2* nAChRs.
increased affinity for the ␣4␤2* nicotinic acetylcholine receptor Furthermore, the present study demonstrates that the interac-
(nAChR) subtype, with the exception of N-n-octylnicotinium tion of these analogs with the ␣4␤2* subtype is via a compet-
iodide (NONI). The most potent analog was N-n-decylnico- itive mechanism. Thus, selectivity for the ␣4␤2* subtype com-
tinium iodide (NDNI; Ki ϭ 90 nM). In contrast, none of the bined with competitive interaction with the S-(Ϫ)-nicotine
analogs in this series exhibited high affinity for the [3H]methyl- binding site indicates that NDNI is an excellent candidate for
lycaconitine binding site, thus indicating low affinity for the ␣7* studying the structural topography of ␣4␤2* agonist recognition
nAChR. The C8 analog, NONI, had low affinity for S-(Ϫ)-[3H]ni- binding sites, for identifying the antagonist pharmacophore on
cotine binding sites but was a potent inhibitor of S-(Ϫ)-nicotine- the ␣4␤2* nAChR, and for defining the role of this subtype in
evoked [3H]dopamine (DA) overflow from superfused striatal physiological function and pathological disease states.
slices (IC50 ϭ 0.62 ␮M), thereby demonstrating selectivity for
Neuronal nicotinic acetylcholine receptors (nAChRs) are
members of a ligand-gated ion channel family of receptors,
consisting of transmembrane proteins of pentameric struc-
ture with potentially diverse composition (Anand et al.,
1991). S-(Ϫ)-Nicotine activates all the known subtypes of
nAChRs, although with varying affinities (Parker et al.,
1998). Heteromeric nAChRs exist as combinations of ␣ and ␤
subunits; however, the exact subunit composition, stoichiom-
etry, and arrangement of the subunits of native nAChRs
have not been elucidated conclusively (Lukas et al., 1999).
Great functional diversity is suggested by the identifica-
tion of 12 genes encoding ␣2–␣10 and ␤2–␤4 subunits, and
from results of in situ hybridization studies revealing dis-
crete, but overlapping, CNS distribution of mRNAs encoding
these subunits (Wada et al., 1989; Dineley-Miller and
Patrick, 1992; Se´gue´la et al., 1993; Le Nove`re et al., 1996). In
addition to heteromeric nAChRs, homomeric nAChRs also
are present in the CNS and are believed to consist of ␣7, ␣8,
or ␣9 subunits; the ␣7* nAChR is one of the most abundant
nAChR subtypes in brain (Wada et al., 1989; Flores et al.,
1992). The ␣7* nAChR subtype is sensitive to inhibition by
␣-bungarotoxin and methyllycaconitine (MLA) (Schoepfer et
al., 1990; Orr-Urtreger et al., 1997; Davies et al., 1999);
[3H]MLA has been reported to be a useful radioligand for
probing this nAChR subtype (Davies et al., 1999).
This study was supported by National Institutes of Health Grants DA00399
and DA10934.
1
Current address: Targacept, Inc., 200 East First Street; Suite 300, Win-
ston-Salem NC 27101-4165.
2
Current address: AstraZeneca, 1800 Concord Pike, P.O. Box 15437, Wil-
mington DE 19850-5437.
Article, publication date, and citation information can be found at
http://jpet.aspetjournals.org.
DOI: 10.1124/jpet.102.043349.
The ␣4␤2* subtype is also a predominant nAChR in the
CNS and is probed by high- affinity S-(Ϫ)-[3H]nicotine bind-
ABBREVIATIONS: nAChR, nicotinic acetylcholine receptor; CNS, central nervous system; ANOVA, analysis of variance; DH␤E, dihydro-␤-
erythroidine; [3H]MLA, [3H]methyllycaconitine; NDNI, N-n-decylnicotinium iodide; DA, dopamine; SAR, structure-activity relationship; NDDNI,
N-n-dodecylnicotinium iodide; NENI, N-ethylnicotinium iodide; NHpNI, N-n-heptylnicotinium iodide; NHxNI, N-n-hexylnicotinium iodide; NMNI,
N-methylnicotinium iodide; NnBNI, N-n-butylnicotinium iodide; NNNI, N-n-nonylnicotinium iodide; NONI, N-n-octylnicotinium iodide; NPNI,
N-n-propylnicotinium iodide; NPeNI, N-n-pentylnicotinium iodide; NUNI, N-n-undecylnicotinium iodide; PEI, polyethylenimine; ء, putative nicotinic
acetylcholine receptor subtype designation.
400

nAChR Subtype Selectivity of N-n-Alkylnicotinium Antagonists
401
ing. Binding of S-(Ϫ)-[3H]nicotine to nAChRs in homogenates
Materials and Methods
of rodent brain is reversible and stereospecific, and repre-
sents a single class of high-affinity sites located at the inter-
face of the ␣/␤ subunits (Lippiello et al., 1987; Reavill et al.,
1988; Zhang and Nordberg, 1993). Greater than 90% of high-
affinity S-(Ϫ)-[3H]nicotine binding sites are immunoprecipi-
tated with anti-␤2 antibody (Whiting and Lindstrom, 1987;
Flores et al., 1992). Furthermore, mice lacking the ␤2 sub-
unit do not exhibit high-affinity S-(Ϫ)-[3H]nicotine binding
(Zoli et al., 1998). Taken together, these results strongly
suggest that ␣4␤2* is the nAChR subtype probed by S-(Ϫ)-
[3H]nicotine binding in brain.
nAChR subunit composition is an important factor that de-
termines the relative affinity of nAChR antagonists at the
S-(Ϫ)-[3H]nicotine binding site (Harvey and Luetje, 1996; Har-
vey et al., 1996; Chavez-Noriega et al., 1997). The relative
inhibitory potency of the classic nAChR antagonist, dihydro-␤-
erythroidine (DH␤E), at multiple recombinant nAChRs has
provided insight into the contribution of ␣ and ␤ subunits to
Materials. DH␤E, S-(Ϫ)-nicotine di-d-tartrate, HEPES, Tris-
[hydroxymethyl]aminomethane hydrochloride (Trizma HCl), Tris[hy-
droxymethyl]aminomethane base (Trizma), and polyethylenimine
(PEI) were purchased from Sigma/RBI (Natick, MA). R-(ϩ)-Nicotine
was purchased from Toronto Research Chemicals (Toronto, ON,
Canada). S-(Ϫ)-[3H]Nicotine (S-(Ϫ)[N-methyl-3H]; specific activity,
80 Ci/mmol and (Ϯ)-[3H]methyllycaconitine ([1␣,4(S),6␤,14␣,16␤]-
20-ethyl-1,6,14,16-tetramethoxy-4[[[2-([3-3H]methyl-2,5-dioxo-1-
pyrrolidinyl)benzoyl]oxy]methyl]aconitane-7,8-diol); specific acti-
vity, 25.4 Ci/mmol; [3H]MLA) were purchased from PerkinElmer Life
Sciences (Boston, MA) and Tocris Cookson Ltd. (Bristol, U.K.), re-
spectively. Scintillation cocktail 3a70B was purchased from Re-
search Products International Corp. (Mt. Prospect, IL). Remaining
chemicals used in the buffers were obtained from Fisher Scientific
(Pittsburgh, PA). N-Methylnicotinium iodide (NMNI), N-n-
propylnicotinium iodide (NPNI), N-n-butylnicotinium iodide (Nn-
BNI), and NONI were prepared as described by Crooks et al. (1995).
N-Ethylnicotinium iodide (NENI), N-n-pentylnicotinium iodide (NP-
eNI), N-n-hexylnicotinium iodide (NHxNI), N-n-heptylnicotinium io-
antagonist sensitivity. DH␤E inhibition of agonist-induced cur- dide (NHpNI), N-n-nonylnicotinium iodide (NNNI), NDNI, N-n-
undecylnicotinium iodide (NUNI), and N-n-dodecylnicotinium iodide
(NDDNI) were prepared from S-(Ϫ)-nicotine and the appropriate
n-alkyl iodide using the general procedure described by Rui et al.
(2002). All compounds were fully characterized by elemental analy-
sis and determined to be free from S-(Ϫ)-nicotine utilizing spectro-
scopic (1H and 13C nuclear magnetic resonance, and fast atom bom-
bardment mass spectroscopy), thin layer chromatographic (silica
gel), and combustion analysis procedures. Structures of the N-n-
alkylnicotinium analogs are shown in Fig. 1.
rents in Xenopus oocytes afforded the following rank order of
sensitivity of expressed rat nAChRs: ␣4␤4 Ͼ ␣4␤2 ϭ ␣3␤2 Ͼ
␣2␤2 Ͼ ␣2␤4 ϾϾ ␣3␤4 (Harvey and Luetje, 1996; Harvey et al.,
1996). Similarly, the rank order for DH␤E inhibition of ex-
pressed human nAChR was ␣4␤4 Ͼ ␣4␤2 Ͼ ␣2␤2 ϭ ␣3␤2 ϭ
␣2␤4 ϾϾ ␣3␤4 (Chavez-Noriega et al., 1997). As such, both ␣
and ␤ subunit N-terminal binding domains are important for
sensitivity to DH␤E (Harvey and Luetje, 1996; Harvey et al.,
1996). With respect to native receptors in rat brain, [3H]DH␤E
competitively binds to nAChRs with high affinity (Kd ϳ10 nM;
Williams and Robinson, 1984). Taken together, these results
indicate that DH␤E binds to agonist recognition sites on ␣4␤2*
native nAChR receptors.
Recently, exciting developments in drug discovery have
indicated that nAChR agonists may be useful for the treat-
ment of cognitive dysfunction, neurodegeneration, and other
CNS diseases (Lloyd and Williams, 2000; Glennon and
Dukat, 2000). However, relatively little attention has focused
on the development of nAChR antagonists as drug candi-
dates (Dwoskin et al., 2000; Dwoskin and Crooks, 2001). Our
Subjects. Male Sprague-Dawley rats (200–250 g) were obtained
from Harlan Laboratories (Indianapolis, IN) and were housed two
per cage with free access to food and water in the Division of Labo-
ratory Animal Resources at the College of Pharmacy, University of
Kentucky. Experimental protocols involving animals were in strict
accordance with the National Institutes of Health Guide for the Care
and Use of Laboratory Animals and were approved by the Institu-
tional Animal Care and Use Committee at the University of Ken-
tucky.
S-(؊)-[3H]Nicotine Saturation Binding. For each experiment,
striata from two to four rats were homogenized using a Tekmar
Polytron in 10 volumes of ice-cold modified Krebs-HEPES buffer (20
mM HEPES, 118 mM NaCl, 4.8 mM KCl, 2.5 mM CaCl2, 1.2 mM
previous research has discovered a new class of nAChR an- MgSO4, pH 7.5). Homogenates were incubated (5 min at 37°C) and
centrifuged (29,000g for 20 min at 4°C). Tissue pellets were resus-
pended in 10 volumes of ice-cold Milli-Q water (Millipore Corp.,
Bedford, MA), incubated (5 min at 37°C), and centrifuged (29,000g
for 20 min at 4°C). The tissue pellets were again resuspended in 10
volumes of ice-cold 10% Krebs-HEPES buffer, then incubated and
centrifuged as described. Final tissue pellets were stored at Ϫ70°C in
fresh 10% Krebs-HEPES buffer until use. Upon assay, pellets were
resuspended in 10% Krebs-HEPES buffer, incubated, and centri-
fuged as previously described. Final pellets were resuspended in 2.0
ml of ice-cold Milli-Q water, and the amount of protein (ϳ200 ␮g of
protein/100 ␮l of membrane suspension) was determined (Bradford,
1976).
tagonists resulting from N-n-alkylation of the S-(Ϫ)-nicotine
molecule (Dwoskin et al., 1999). These S-(Ϫ)-nicotine analogs
exhibit potent and competitive inhibition of the nAChR sub-
type (␣3␣6␤2* subtype) mediating S-(Ϫ)-nicotine-evoked do-
pamine (DA) release from dopaminergic nerve terminals in
striatum (Wilkins et al., 2002). Structure-activity relation-
ships (SARs) reveal that analogs with N-n-alkyl chains rang-
ing from C7 to C12 were the most potent antagonists of native
␣3␣6␤2* nAChRs. The C10 analog, N-n-decylnicotinium io-
dide (NDNI), was unique in this respect, since it did not
inhibit S-(Ϫ)-nicotine-evoked DA release. To determine the
nAChR-subtype selectivity of this new class of N-n-alkylni-
cotinium antagonists, the current study evaluated the ability
of these antagonists to inhibit high-affinity S-(Ϫ)-[3H]nico-
tine binding to rat striatal membranes (␣4␤2* subtype) and
to inhibit [3H]MLA binding to rat whole brain membranes
(␣7* subtype). Analog affinity was compared with that of the
classic antagonist, DH␤E, and the mechanism of interaction
of two N-n-alkylnicotinium analogs, NDNI and N-n-octylni-
cotinium iodide (NONI), with ␣4␤2* nAChRs was also deter-
mined.
Saturation binding of S-(Ϫ)-[3H]nicotine was performed in dupli-
cate in a final volume of 200 ␮l of Krebs-HEPES buffer containing
250 mM Tris (pH 7.5, at 4°C). Reactions were initiated by addition of
100 ␮l of membrane suspension to tubes containing 50 ␮l of Krebs-
HEPES buffer and 50 ␮l of S-(Ϫ)-[3H]nicotine (0.625–20 nM, final
concentration). Nonspecific binding at each S-(Ϫ)-[3H]nicotine con-
centration was determined in duplicate in the presence of 10 ␮M
S-(Ϫ)-nicotine. Following incubation (90 min at 4°C), reactions were
terminated by dilution with ice-cold Krebs-HEPES buffer followed by
immediate filtration through Whatman GF/B glass fiber filters (pre-
soaked in 0.5% PEI) using a Brandel cell harvester (Biomedical

402
Wilkins et al.
Fig. 1. Structures of S-(Ϫ)-nicotine, N-n-alkylnicotinium
analogs, methyllycaconitine (MLA) and dihydro-␤-eryth-
roidine (DH␤E). Note that the 2Ј S configuration of the
S-(Ϫ)-nicotine molecule is preserved in all of the N-n-
alkylnicotinium analogs. R ϭ n-alkyl substituent.
Research and Development Laboratories, Inc., Gaithersburg, MD). GF/B glass fiber filters (presoaked in 0.5% PEI) using the cell har-
Filters were rinsed three times with 3 ml of ice-cold Krebs-HEPES vester. Filters were processed and radioactivity was determined as
buffer and transferred to scintillation vials, 3 ml of scintillation previously described.
cocktail were added, and radioactivity was determined by liquid
scintillation spectroscopy (Tri-Carb 2100 TR Liquid Scintillation An- striatum, and cerebellum) was homogenized in 20 volumes of ice-cold
alyzer, PerkinElmer Life Sciences). hypotonic buffer (2 mM HEPES, 14.4 mM NaCl, 0.15 mM KCl, 0.2
Inhibition of [3H]MLA Binding. Whole rat brain (minus cortex,
Inhibition of S-(؊)-[3H]Nicotine Binding. Striatal membranes mM CaCl2, and 0.1 mM MgSO4, pH 7.5). Homogenates were incu-
were prepared as previously described. Inhibition of specific S-(Ϫ)- bated at 37°C for 10 min and centrifuged (25,000g for 15 min at 4°C).
[3H]nicotine binding by synthetic N-n-alkylnicotinium analogs was Pellets were washed three times by resuspension in 20 volumes of
assessed using a previously described method (Crooks et al., 1995). the same buffer, followed by centrifugation using the above param-
Briefly, assays were performed in triplicate in a final volume of 200 eters. Final pellets were resuspended in incubation buffer to provide
␮l of Krebs-HEPES buffer containing 250 mM Tris buffer (pH 7.5, ϳ150 ␮g of protein/100 ␮l membrane suspension. Binding assays
4°C). Reactions were initiated by the addition of 100 ␮l of membrane were performed in duplicate, in a final vol of 250 ␮l of incubation
suspension to tubes containing 50 ␮l of Krebs-HEPES buffer or one buffer, containing 20 mM HEPES, 144 mM NaCl, 1.5 mM KCl, 2 mM
of at least seven concentrations (0.1 nM–1 mM, final concentration) CaCl2, 1 mM MgSO4, and 0.05% bovine serum albumin, pH 7.5.
of S-(Ϫ)-nicotine, R-(ϩ)-nicotine, DH␤E or N-n-alkylnicotinium an- Assays were initiated by the addition of 100 ␮l of membrane suspen-
alog and 50 ␮l of S-(Ϫ)-[3H]nicotine (3 nM, final concentration). sion to 150 ␮l of sample containing 2.5 nM [3H]MLA and one of at
Nonspecific binding was determined in triplicate in the presence of least six concentrations (30 nM–100 ␮M, final concentration) of
10 ␮M S-(Ϫ)-nicotine. Following incubation (90 min at 4°C), reac- analog, and incubated for 2 h at room temperature. Nonspecific
tions were terminated by dilution of samples with ice-cold Krebs- binding was determined in the presence of 10 ␮M MLA. Assays were
HEPES buffer followed by immediate filtration through Whatman terminated by dilution with 3 ml of ice-cold incubation buffer fol-

nAChR Subtype Selectivity of N-n-Alkylnicotinium Antagonists
403
lowed by immediate filtration through Schleicher and Schuell data were expressed as specific [3H]MLA bound as a percentage of
(Keene, NH) #32 glass fiber filters (presoaked with 0.5% PEI) using control, and plotted as a function of log analog concentration. Data were
the cell harvester. Filters were processed as described above in the
fit by a one-site binding competition model, using nonlinear least-
S-(Ϫ)-[3H]nicotine binding assay.
squares regression, such that Y ϭ Bt ϩ ((Tp Ϫ Bt)/(1 ϩ 10X Ϫ log IC )),
50
Mechanism of Analog Inhibition of S-(؊)-[3H]Nicotine
Binding. Striatal membrane homogenates were prepared as previ-
ously described. Saturation of specific S-(Ϫ)-[3H]nicotine binding
was determined in the absence and presence of three concentrations
of NDNI or NONI. Reactions were initiated by addition of 100 ␮l of
membrane suspension to tubes containing 50 ␮l S-(Ϫ)-[3H]nicotine
(0.625–20 nM, final concentration) and 50 ␮l of Krebs-HEPES buffer
(control, i.e., absence of analog) or one of three concentrations of
NDNI or NONI. Concentrations of NDNI (0.6, 2, and 6 ␮M) and
NONI (0.66, 2.2, and 22 ␮M) were chosen based on results obtained
from the inhibition isotherms. Nonspecific binding at each S-(Ϫ)-
[3H]nicotine concentration was determined in duplicate in the pres-
ence of 10 ␮M S-(Ϫ)-nicotine. Following incubation (90 min at 4°C),
reactions were terminated and filters processed as previously de-
scribed.
where Y ϭ specific [3H]MLA binding (percentage of control), X ϭ log
[[3H]MLA], Bt ϭ minimum [3H]MLA binding (held constant at a value
of 0), Tp ϭ the [3H]MLA binding density, and log IC50 ϭ log [analog],
which decreased [3H]MLA receptor occupancy by 50%. Analog affinity
constants (Ki values) were calculated using the equation, Ki ϭ IC50/(1 ϩ
concentration of [3H]MLA/Kd), where IC50 ϭ the concentration of ana-
log inhibiting [3H]MLA binding by 50%, and Kd ϭ the [3H]MLA disso-
ciation constant (1.93 nM) determined from initial saturation binding
experiments (Cheng and Prusoff, 1973).
The mechanism of analog interaction with high-affinity S-(Ϫ)-
[3H]nicotine binding sites was assessed. Saturation binding of S-(Ϫ)-
[3H]nicotine was assessed in the absence and presence of three
concentrations of NDNI and NONI. Minimum binding was held
constant at a value of zero, and simple slope sigmoid fits were used
since the F statistic revealed that the variable slope did not provide
a significantly better fit to the data. For each analog, the saturation
isotherms were assessed for parallelism by comparing simple and
variable slope sigmoid curve fit. The saturation isotherms did not
reach a clear asymptotic maximum in the presence of the highest
concentrations of analog. No significant differences between maxi-
mum S-(Ϫ)-[3H]nicotine binding values extrapolated from curve fits
to the data at each NDNI or NONI concentration were found by
one-way ANOVA (NDNI, F3,14 ϭ 0.929, p ϭ 0.46; NONI, F3,16 ϭ 1.61,
p ϭ 0.24). Therefore, the mean extrapolated value for maximum
S-(Ϫ)-[3H]nicotine binding was used as the maximum binding con-
stant. To further assess the mechanism of analog interaction with
high-affinity receptors, saturation data were also analyzed using
Scatchard analysis. Mean specific S-(Ϫ)-[3H]nicotine binding data
were transformed and fit by linear regression, and Bmax and Kd
values were derived. Apparent Kd values were transformed to the
respective negative log (Ϫlog Kd) value for parametric statistical
analysis. One-way ANOVAs of Bmax and Ϫlog Kd values were used to
determine effects of analog concentration on S-(Ϫ)-[3H]nicotine bind-
ing parameters.
Analysis of S-(؊)-[3H]Nicotine Binding Data. For S-(Ϫ)-
[3H]nicotine saturation binding isotherms, specific S-(Ϫ)-[3H]nico-
tine binding was expressed as femtomoles per milligram of protein
and plotted as a function of S-(Ϫ)-[3H]nicotine concentration. Data
were fitted by one- and two-site hyperbolic functions using weighted
(1/Y2 minimized), nonlinear least-squares regression, since the non-
weighted fit minimizing Y2 was not unique. One-site binding was
modeled using the equation, Y ϭ (Bmax ⅐ X)/(Kd ϩ X), where Y ϭ
specific S-(Ϫ)-[3H]nicotine binding, X ϭ S-(Ϫ)-[3H]nicotine concen-
tration, Bmax ϭ maximum binding density, and Kd ϭ the dissociation
binding constant. Two-site binding was modeled using the equation,
Y ϭ (Bmax1 ⅐ X)/(Kd1 ϩ X) ϩ (Bmax2 ⅐ X)/(Kd2 ϩ X), where Bmax1 and
Bmax2 ϭ maximum binding density for sites 1 and 2, respectively,
and Kd1 and Kd2 ϭ dissociation binding constants for sites 1 and 2,
respectively. Fits were compared using the F statistic, and the one-
site model was chosen unless the two-site model provided a signifi-
cantly (p Ͻ 0.05) better fit.
Specific S-(Ϫ)-[3H]nicotine binding was also plotted as a function
of log S-(Ϫ)-[3H]nicotine concentration. To obtain the Bmax and Kd
values, nonlinear regression was performed using a variable-slope
sigmoid function, holding minimum specific binding (Bt) at a con-
To further verify the mechanism of analog interaction with high
affinity S-(Ϫ)-[3H]nicotine binding sites, the binding affinities de-
rived from saturation analyses in the absence and presence of three
concentrations of NDNI or NONI were negative log transformed
(Ϫlog Kd) and plotted as a function of analog concentration (Lew and
Angus, 1995). Three nonlinear regression models were fit to the data.
The basic equation was a mathematical equivalent of a Schild re-
gression indicative of competitive binding inhibition, Y ϭ Ϫ1 ⅐ log
stant value of zero, such that
Y ϭ Bt ϩ ((Tp Ϫ Bt)/(1 ϩ
10(log EC ϪX) ⅐ n)) where Y ϭ specific S-(Ϫ)-[3H]nicotine binding, X ϭ
log S-(Ϫ)-[3H]nicotine concentration, Bt and Tp ϭ minimum and
maximum specific S-(Ϫ)-[3H]nicotine binding densities, respectively,
log EC50 ϭ log S-(Ϫ)-[3H]nicotine concentration at 50% receptor
occupancy, and nH ϭ the Hill slope factor, an index of binding
cooperativity. Simple linear regression on the Scatchard-trans-
formed data were performed, such that Y ϭ mX ϩ b, where Y ϭ B/F,
X ϭ B, m ϭ slope, and b ϭ extrapolated Y-intercept. The Bmax value
was obtained from the extrapolated X-intercept value, and the Kd
value was obtained from Ϫ1/slope.
50
((X ⅐ 1e-6) ϩ (10log K )) Ϫ P, where Y ϭ Ϫlog Kd for specific S-(Ϫ)-
b
[3H]nicotine binding in the absence or presence of analog, X ϭ
concentration of analog (micromolar), log Kb ϭ the logarithm of
analog binding inhibition constant derived from S-(Ϫ)-[3H]nicotine
binding inhibition isotherms, and P ϭ the negative logarithm of the
constant C (Ϫlog C), where C ϭ 0.50 fractional receptor occupancy in
the absence and presence of analog). A “power departure” model was
also used to fit the data and was defined by the equation Y ϭ Ϫ1 ⅐ log
Analyses of Analog Binding Inhibition Data. For N-n-alkyl-
nicotinium analog inhibition of S-(Ϫ)-[3H]nicotine binding, data were
expressed as specific S-(Ϫ)-[3H]nicotine bound as a percentage of
control and plotted as a function of log analog concentration. Data
were fit by a variable slope model, using nonlinear least-squares
(((X ⅐ 1e-6)slope) ϩ (10log K )) Ϫ P. The power departure model differed
b
IC50ϪX)
⅐
regression, such that Y ϭ Bt ϩ ((Tp Ϫ Bt)/(1 ϩ 10)(log
n)),
from the basic equation by inclusion of a variable slope factor. A
where Y ϭ specific S-(Ϫ)-[3H]nicotine binding, X ϭ log [S-(Ϫ)-[3H]ni-
cotine], Bt and Tp ϭ minimum and maximum specific S-(Ϫ)-[3H]ni-
cotine binding densities, respectively, log IC50 ϭ log[compound],
which decreased S-(Ϫ)-[3H]nicotine receptor occupancy by 50%, and
n ϭ the pseudo-Hill coefficient. Analog affinity constants (Ki values)
were calculated using the equation, Ki ϭ IC50/(1 ϩ concentration of
S-(Ϫ)-[3H]nicotine/Kd), where IC50 ϭ the concentration of analog
inhibiting S-(Ϫ)-[3H]nicotine binding by 50% and Kd ϭ the S-(Ϫ)-
[3H]nicotine dissociation constant determined from initial saturation
binding experiments (Cheng and Prusoff, 1973).
“quadratic departure” model was also used and was defined by the
equation Y ϭ Ϫ1 ⅐ log((X ⅐ 1e-6) ⅐ (1 ϩ ((slope ⅐ (X ⅐ 1e-6))/(10log K ))) ϩ
b
(10log K )) Ϫ P. In addition to inclusion of the variable slope factor, the
b
quadratic departure equation allows for the detection of more com-
plex interactions with the binding site, such as a nonequilibrium
steady state and/or heterogeneity of the receptor population. The
basic equation defining competitive interaction was chosen as the
best fit model, unless one of the more complex models provided a
significantly (p Ͻ 0.05) better fit to the data. Regression and statis-
tical analyses were performed using the commercially available soft-
For N-n-alkylnicotinium analog inhibition of [3H]MLA binding, ware packages Prism v3.0 (GraphPad Software, Inc., San Diego, CA),

404
Wilkins et al.
whereas more complex statistical analyses were preformed using 3. Comparisons were made between simple- and variable-
SPSS standard v9.0 (SPSS Science, Chicago, IL).
slope sigmoid curve fits to the data for each compound and
were found not different, with exceptions of DH␤E (F1,5
Correlation of N-n-Alkylnicotinium Inhibition of S-(؊)-
[3H]Nicotine Binding to Striatal Membranes and S-(؊)-Nico-
tine-Evoked [3H]DA Overflow from Superfused Striatal
Slices. To evaluate the nAChR subtype selectivity of this novel
series of analogs, log IC50 values for each analog to inhibit S-(Ϫ)-
nicotine-evoked [3H]DA overflow, which were obtained from a previ-
ous report (Wilkins et al., 2002), were plotted as a function of the log
IC50 values derived from S-(Ϫ)-[3H]nicotine binding inhibition
curves (Fig. 2). Pearson’s analysis of these data was used to detect
ϭ
18.5, p Ͻ 0.05) and S-(Ϫ)-nicotine (F1,6 ϭ 28.9, p Ͻ 0.05),
suggesting a more complex interaction of these two com-
pounds with S-(Ϫ)-[3H]nicotine binding sites. Inhibition pa-
rameters and slope factors are provided in Table 1. Similar to
the reference compounds, the N-n-alkylnicotinium analogs
completely inhibited S-(Ϫ)-[3H]nicotine binding. S-(Ϫ)-Nico-
tine had the highest affinity (Ki ϭ 0.8 nM) of the compounds
the presence of a significant correlation between these nAChR sites. tested. R-(ϩ)-Nicotine had an affinity (Ki ϭ 49 nM) ϳ60-fold
lower than that of S-(Ϫ)-nicotine, indicating a high degree of
enantioselectivity for nicotine at high-affinity S-(Ϫ)-[3H]ni-
Results
cotine binding sites. Analog affinities varied across a 230-fold
S-(؊)-[3H]Nicotine Saturation Binding. Binding of
range (Ki values ranged from 93 nM to 20 ␮M; Table 1). From
S-(Ϫ)-[3H]nicotine to rat striatal membranes was saturable
the series, the C10 analog NDNI exhibited the greatest affin-
and specific (Fig. 2). Nonspecific binding was ϳ12% of total
binding at a S-(Ϫ)-nicotine concentration approximating the
Kd. A one-site hyperbolic model provided the best fit to the
data, suggesting that equilibrium binding of S-(Ϫ)-[3H]nico-
tine represents interaction with a single population of bind-
ing sites. Values for affinity (Kd, 95% confidence interval) and
maximum density (Bmax Ϯ S.E.M.) were 1.94 (1.36, 2.51) nM
and 97.6 (Ϯ4.7) fmol/mg protein, respectively. Variable slope
sigmoid fit (R2 ϭ 0.995) of specific S-(Ϫ)-[3H]nicotine binding
as a function of log S-(Ϫ)-[3H]nicotine concentration provided
similar estimates for Kd and Bmax of 1.56 (0.92, 2.64) nM and
89.8 (Ϯ5.9) fmol/mg protein, respectively, with a Hill coeffi-
cient of 0.963 (r2 ϭ 1). Linear regression (r2 ϭ 0.948) of the
Scatchard-transformed data provided similar estimates of Kd
and Bmax values of 1.94 (1.31, 2.56) nM and 98.1 (Ϯ5.2)
fmol/mg protein (Fig. 2, inset).
ity, with a Ki value of 93 nM, which was not different from
either the C12 analog NDDNI (Ki ϭ 140 nM) or DH␤E (Ki ϭ
143 nM). The remaining synthetic analogs exhibited lower
affinities, with an overall rank order of the compounds test-
ed: S-(Ϫ)-nicotine Ͼ R-(ϩ)-nicotine Ͼ NDNI ϭ NDDNI ϭ
DH␤E Ͼ NHxNI Ͼ NNNI ϭ NENI ϭ NHpNI Ͼ NMNI Ͼ
NnBNI Ͼ NONI ϭ NPNI (Table 1).
N-n-Alkylnicotinium Analog Inhibition of [3H]MLA
Binding. Results from full concentration-response curves for
the analogs to inhibit [3H]MLA binding revealed that only
four analogs (NENI, NHxNI, NHpNI, and NONI) at the
highest concentration of 100 ␮M inhibited binding by greater
than 50% of total specific binding (Table 2). Based on these
results, Ki values were obtained for NENI, NHxNI, NHpNI,
and NONI from one-site competition models of the data (Ta-
ble 2). None of the analogs in this series exhibited high
affinity for [3H]MLA binding sites.
N-n-Alkylnicotinium Analog Inhibition of Specific
S-(؊)-[3H]Nicotine Binding. Inhibition curves for N-n-al-
kylnicotinium analogs as well as the reference compounds
S-(Ϫ)-nicotine, R-(ϩ)-nicotine, and DH␤E are shown in Fig.
Fig. 3. Inhibition of specific S-(Ϫ)-[3H]nicotine binding to striatal mem-
branes by N-n-alkylnicotinium analogs: comparison with DH␤E, S-(Ϫ)-
nicotine, and R-(ϩ)-nicotine. S-(Ϫ)-[3H]Nicotine binding is expressed as a
percentage of binding in the absence of analog (control, CON). Curves are
variable-slope sigmoid fits to mean data. For visual clarity, standard
errors are not illustrated; however, variability obtained is indicated in
Table 1. Symbols in legend for S-(Ϫ)-nicotine, R-(ϩ)-nicotine, and DH␤E
are connected by dashed rather than solid lines. Legend (top to bottom)
also provides rank order of affinity from highest to lowest. Numbers
inside parentheses indicate n-alkyl chain length. Data represent the
mean of n ϭ 4–6 independent observations from triplicate measurements
at each concentration.
Fig. 2. Saturation binding of S-(Ϫ)-[3H]nicotine to rat striatal mem-
branes. Binding curves showing specific (F) and nonspecific (E) S-(Ϫ)-
[3H]nicotine binding. Inset, Scatchard plot of specific S-(Ϫ)-[3H]nicotine
binding. Data represent the mean Ϯ S.E.M. of at least four independent
observations.

nAChR Subtype Selectivity of N-n-Alkylnicotinium Antagonists
405
TABLE 1
Inhibition of specific S-(Ϫ)-͓3H͔nicotine binding to rat striatal membranes by novel N-n-alkylnicotinium analogs: comparison with reference
compounds DH␤E, S-(Ϫ)-nicotine, and R-(ϩ)-nicotine
IC50 values were derived from variable-slope, sigmoid curve fits to the mean data from four to six independent observations. Ki values were derived from IC50 values using
the Cheng-Prusoff equation.
Compound
n-Alkyl Chain Length
IC50
95% CIa
Ki
95% CI
Slope Factorb
s.e.c
␮M
␮M
NDNI
10
12
6
0.23
0.20, 0.27
0.28, 0.43
1.15, 1.50
1.83, 2.39
1.89, 3.58
4.64, 5.70
6.94, 11.2
24.2, 30.7
45.6, 63.4
38.6, 62.9
0.09
0.08, 0.11
0.11, 0.17
0.46, 0.60
0.73, 0.95
0.76, 1.43
1.85, 2.28
2.77, 4.48
9.70, 12.3
18.2, 25.3
15.4, 25.1
Ϫ0.958
Ϫ0.854
Ϫ0.904
Ϫ1.064
Ϫ1.106
Ϫ1.031
Ϫ0.957
Ϫ1.107
Ϫ0.936
Ϫ1.136
0.066
0.053
0.045
0.045
0.179
0.027
0.047
0.089
0.076
0.112
NDDNI
NHxNI
NNNI
NENI
0.35
1.32
2.09
2.60
5.14
8.82
0.14
0.53
0.84
1.04
2.06
3.53
9
2
NHpNI
NMNI
NnBNI
NPNI
7
1
4
27.2
53.7
49.3
10.9
21.5
19.7
3
NONI
8
DH␤E
NAd
0.36
0.24, 0.53
0.14
0.09, 0.21
Ϫ0.667
0.067
S-(Ϫ)-Nicotine
R-(ϩ)-Nicotine
0
0
0.002
0.12
0.001, 0.004
0.10, 0.15
0.0008
0.05
0.0007, 0.0040
0.04, 0.06
Ϫ0.816
Ϫ0.993
0.029
0.091
a
95% CI ϭ 95% confidence interval.
b
c
Pseudo-Hill coefficient, derived using a variable slope model.
s.e. ϭ standard error of slope factor.
NA ϭ not applicable.
d
TABLE 2
N-n-Alkylnicotinium analog inhibition of specific ͓3H͔MLA binding to rat brain membranes
Ki values were derived from IC50 values using the Cheng-Prusoff equation. IC50 values were derived by fitting a one-site binding competition model to inhibition curves
generated for analogs, which produced Ͼ50% inhibition of the ͓3H͔MLA binding at 100 ␮ M analog.
n-Alkyl
Chain Length
Specific ͓3H͔MLA Binding in the
b
N-n-Alkylnicotinium Analog
Ki
95% CI
a
Presence of 100 ␮M Analog
% of control
␮ M
NMNI
1
2
81.9 Ϯ 7.52
47.8 Ϯ 1.94*
82.1 Ϯ 3.79
94.9 Ϯ 2.95
84.8 Ϯ 3.42*
11.1 Ϯ 3.51*
43.5 Ϯ 4.16*
9.61 Ϯ 2.60*
52.2 Ϯ 7.65*
55.7 Ϯ 15.8
56.7 Ϯ 6.11*
81.6 Ϯ 1.54
Ͼ50
NENI
49.8
32.8,74.1
NPNI
3
Ͼ50
Ͼ50
Ͼ50
NnBNI
NPeNI
NHxNI
NHpNI
NONI
NNNI
NDNI
NUNI
NDDNI
4
5
6
16.4
36.7
12.2
10.9,24.6
27.8,48.5
9.20,16.1
7
8
9
Ͼ50
10
11
12
Ͼ50
Ͼ50
Ͼ50
* p Ͻ 0.05, Student t test, compared with total specific ͓3H͔MLA binding (absence of analog).
a
Values are mean Ϯ S.E.M., n ϭ 3 independent observations from duplicate measurements at each analog concentration.
95% CI ϭ 95% confidence interval.
b
Analog Affinity for S-(؊)-[3H]Nicotine Binding Sites ries of analogs examined, the C10 and C8 analogs, NDNI and
as a Function of n-Alkyl Chain Length. A plot of the log NONI, respectively, represent extremes in affinity for S-(Ϫ)-
transform of the S-(Ϫ)-[3H]nicotine binding inhibition con- [3H]nicotine binding sites. The mechanism by which NDNI
stant (log Ki) as a function of n-alkyl chain length for each and NONI interact with high-affinity S-(Ϫ)-[3H]nicotine
analog is presented in Fig. 4. Linear regression of analog binding sites was determined by assessing shifts in the
affinity (Ki) for S-(Ϫ)-[3H]nicotine binding sites by n-alkyl S-(Ϫ)-[3H]nicotine concentration-binding curves in the pres-
chain length was performed with NONI (C8 analog) included ence of three concentrations of NDNI or NONI relative to
and excluded from the analysis, because the Ki value for control (in the absence of analog). NDNI and NONI concen-
NONI appeared to deviate from the linear trend. With the log trations were chosen based on Ki values determined in the
Ki value for NONI included in the analysis, the linear model previous inhibition studies (Table 2). S-(Ϫ)-[3H]Nicotine sat-
did not provide a good fit to the data (r2 ϭ 0.338), and the uration binding isotherms were observed to be parallel in the
slope of the regression line was not significantly different absence and presence of analog, as evidenced by the better fit
from a value of zero (F1,8 ϭ 7.08, p Ͻ 0.078). When the log Ki of the data to the simple slope sigmoid model compared with
value for NONI was excluded, the linear model provided a the variable slope model (Table 3).
significantly better fit (r2 ϭ 0.560), with a significantly non-
Scatchard transformations of high-affinity S-(Ϫ)-[3H]nico-
zero slope (–0.156; F1,7 ϭ 8.91, p Ͻ 0.05). Therefore, with the tine binding in the absence and presence of NDNI and NONI
exception of NONI, analog affinity varied in a linear fashion are shown in Fig. 5. Values for affinity (Kd) and maximum
with n-alkyl chain length, i.e., affinity increased with in- density (Bmax) were derived from linear regressions of these
creasing chain length.
data (Table 3). One-way ANOVA of the log Kd values ob-
Mechanism of N-n-Alkylnicotinium Analog-Induced tained in the absence and presence of three concentrations of
Inhibition of S-(؊)-[3H]Nicotine Binding. Within the se- each analog indicated a significant decrease in S-(Ϫ)-[3H]ni-

406
Wilkins et al.
bition of S-(Ϫ)-nicotine-evoked [3H]DA overflow and of IC50
values for inhibition of S-(Ϫ)-[3H]nicotine binding was not
significant (Pearson r ϭ 0.255, p Ͼ 0.05). Another correlation
analysis was performed subsequently, in which the data for
NDNI and NONI were excluded as outliers. Upon exclusion
of NDNI and NONI, a significant correlation was obtained
(Pearson r ϭ 0.855, p Ͻ 0.05). Therefore, the lack of correla-
tion observed when data for NDNI and NONI were included
in the analysis suggests that inhibition of S-(Ϫ)-nicotine-
evoked [3H]DA overflow is not well correlated with inhibition
of S-(Ϫ)-[3H]nicotine binding. This interpretation is sup-
ported by the observations that NDNI did not inhibit S-(Ϫ)-
nicotine-evoked [3H]DA overflow but potently inhibited
S-(Ϫ)-[3H]nicotine binding. Also, NONI did not inhibit S-(Ϫ)-
[3H]nicotine binding but potently inhibited nicotine-evoked
[3H]DA overflow. Interestingly, when the correlation analy-
sis was performed excluding NDNI and NONI, a relationship
was revealed suggesting that the remaining analogs interact
with common nAChR sites.
Discussion
The current study demonstrates that N-n-alkylnicotinium
analogs with n-alkyl chain lengths from 1 to 12 carbons,
which have been previously shown to act as antagonists at
␣3␣6␤2* nAChRs mediating S-(Ϫ)-nicotine-evoked [3H]DA
overflow (Wilkins et al., 2002), have varying affinity for
S-(Ϫ)-[3H]nicotine binding sites in striatum. A linear rela-
tionship was observed such that with increasing n-alkyl
chain length, affinity for the ␣4␤2* nAChR subtype in-
Fig. 4. Linear relationship of N-n-alkylnicotinium analog affinity for
S-(Ϫ)-[3H]nicotine binding sites and n-alkyl chain length. When the log Ki
value for NONI was excluded from the analysis, the linear model pro-
vided a significantly better fit (r2 ϭ 0.560) than when NONI was included.
Thus, analog affinity for S-(Ϫ)-[3H]nicotine binding sites in rat striatum
varies in a linear fashion with n-alkyl chain length. Each point represents
the log Ki value derived from nonlinear curve fitting of the inhibition data
shown in Fig. 3. Symbols representing each analog are as indicated in
Fig. 3.
cotine affinity for its binding site (NONI, F3,16 ϭ 30.5, p Ͻ creased. The most potent analog was NDNI (C10 analog; Ki
0.001; NDNI, F3,14 ϭ 21.1, p Ͻ 0.001). One-way ANOVA also value ϭ 90 nM). In contrast, the analogs did not exhibit high
revealed no significant differences in Bmax values (NONI, affinity for [3H]MLA binding sites, indicating low affinity for
F3,16 ϭ 0.07, p ϭ 0.97; NDNI, F3,14 ϭ 0.34, p ϭ 0.80), indi- ␣7* nAChRs. Furthermore, the present study demonstrates
cating that both NDNI and NONI interact with high-affinity that the interaction of these analogs with high affinity S-(Ϫ)-
S-(Ϫ)-[3H]nicotine binding sites in rat striatum via a compet- [3H]nicotine binding sites on the ␣4␤2* subtype is via a
itive mechanism.
competitive mechanism. Importantly, NDNI did not inhibit
To further evaluate the nature of the interaction of NDNI S-(Ϫ)-nicotine-evoked [3H]DA overflow from superfused stri-
and NONI with high-affinity S-(Ϫ)-[3H]nicotine binding atal slices and, thus, appears to be selective for the ␣4␤2*
sites, affinity values for S-(Ϫ)-[3H]nicotine in the absence subtype. In contrast, NONI (C8 analog) had low affinity for
and presence of NDNI or NONI were plotted as a function of S-(Ϫ)-[3H]nicotine binding sites but potently inhibited S-(Ϫ)-
analog concentration and nonlinear regression curves gener- nicotine-evoked [3H]DA overflow (IC50 ϭ 0.62 ␮M), demon-
ated (Fig. 6). In agreement with the Scatchard analysis, a strating selectivity for ␣3␣6␤2* nAChRs mediating S-(Ϫ)-
competitive mode of interaction of each analog with high- nicotine-evoked [3H]DA overflow.
affinity S-(Ϫ)-[3H]nicotine binding sites was indicated by
Affinity and maximum binding density estimates (1.94 nM
best fit of the data to the simple model (NDNI, R2 ϭ 0.952; and 97.6 fmol/mg protein, respectively) obtained from S-(Ϫ)-
NONI, R2 ϭ 0.985). Neither the power departure model [3H]nicotine saturation binding analysis were modeled best
(NDNI, p ϭ 0.40; NONI, p ϭ 0.20) nor the quadratic depar- by a one-site hyperbolic function. Linear Scatchard transfor-
ture model (NDNI, p ϭ 0.33; NONI, p ϭ 0.36) provided a mation and Hill coefficient of 0.963 indicated an interaction
significantly better fit to the data for either NDNI or NONI. with a single class of binding sites. Current parameter esti-
Correlation of N-n-Alkylnicotinium Inhibition of mates were within the range of reported values, using either
S-(؊)-[3H]Nicotine Binding to Striatal Membranes and striatal or whole brain membranes (Kd ϭ 0.4–14 nM; Bmax ϭ
S-(؊)-Nicotine-Evoked [3H]DA Overflow from Super- 55–200 fmol/mg protein; Lippiello et al., 1987; Martino-Bar-
fused Striatal Slices. To evaluate the nAChR subtype se- rows and Kellar, 1987; Reavill et al., 1988). Variability in Kd
lectivity of this series of analogs, data from both the present and Bmax estimates may be attributed to methodological
S-(Ϫ)-[3H]nicotine binding assays and previously reported differences in assays employed (e.g., inclusion of protease or
S-(Ϫ)-nicotine-evoked [3H]DA overflow assays (Wilkins et al., cholinesterase inhibitors in tissue preparation buffers, vari-
2002) were analyzed by correlation analysis, and the results ation in Mg2ϩ and Ca2ϩ concentrations in binding buffers).
are shown in Fig. 7. NDNI did not inhibit S-(Ϫ)-nicotine- Validation of current assay conditions was provided by
evoked [3H]DA overflow and, as such, the highest concentra- comparable Ki values for S-(Ϫ)-nicotine, R-(ϩ)-nicotine,
tion (100 ␮M) examined in the current study was included in and DH␤E (Ki ϭ 0.8, 50, and 140 nM, respectively), as
the correlation analysis. Correlation of IC50 values for inhi- reported by others (Martino-Barrows and Kellar, 1987;

nAChR Subtype Selectivity of N-n-Alkylnicotinium Antagonists
407
TABLE 3
Specific S-(Ϫ)-͓3H͔nicotine binding affinity (Kd) and maximum densities (Bmax) in the absence and presence of the N-n-alkylnicotinium analogs
NDNI and NONI
Parameters were determined from studies using rat striatal membranes. Kd and Bmax values were derived from linear regression analysis of the Scatchard-transformed data
from saturation binding isotherms. F-statistics were calculated for comparison of simple- vs. variable-slope sigmoid curve fits.
Analog
Concentration
Kd
95% CIa
Bmax
S.E.M.
Simple- vs. Variable-Slope Sigmoid Fit F-Statistic
␮ M
nM
fmol/mg protein
NDNI
0
0.6
2
2.15
3.96
5.69
156, 2.75
3.19, 4.72
4.77, 6.62
9.16, 17.5
0.89, 1.45
2.12, 2.97
3.48, 5.07
10.6, 24.6
69.1
79.5
87.3
88.5
62.2
64.9
64.0
57.3
3.4
3.4
3.5
8.6
1.9
2.0
2.8
7.5
F1,5 ϭ 2.64, P ϭ 0.16
F1,7 ϭ 0.76, P ϭ 0.41
F1,7 ϭ 2.33, P ϭ 0.17
F1,6 ϭ 0.18, P ϭ 0.68
F1,7 ϭ 1.45, P ϭ 0.27
F1,7 ϭ 5.30, P ϭ 0.05
F1,7 ϭ 1.26, P ϭ 0.30
F1,8 ϭ 0.08, P ϭ 0.78
6
13.4
NONI
0
1.17
2.55
4.27
0.66
2.2
22
17.6
a
95% CI ϭ 95% confidence interval.
Fig. 6. S-(Ϫ)-[3H]Nicotine affinity (Ϫlog Kd) as a function of NDNI or
NONI concentration. Kd values were derived from nonlinear fits to the
saturation binding isotherms in the absence and presence of three con-
centrations of NDNI or NONI. The simple model of competitive interac-
tion provided the best fit to data sets for each analog.
Inhibition of specific S-(Ϫ)-[3H]nicotine binding by S-(Ϫ)-
nicotine, R-(ϩ)-nicotine, DH␤E, and each N-n-alkylnico-
tinium analog was modeled using a variable-slope sigmoid
equation. With the exception of S-(Ϫ)-nicotine and DH␤E,
slope factors derived were near unity for R-(ϩ)-nicotine and
each of the analogs examined, indicating a simple competi-
tive interaction with high-affinity S-(Ϫ)-[3H]nicotine binding
sites. In contrast, DH␤E and S-(Ϫ)-nicotine exhibited shal-
low slopes (n Ͻ 1), suggesting that these compounds recog-
nize either more than one agonist binding site on a single
␣4␤2* receptor, or more than one conformational state of the
␣4␤2* nAChR, or more than one nAChR subtype. Interest-
ingly, multiple binding sites for [3H]DH␤E in rat cortical
membranes have been detected (Williams and Robinson,
1984), suggesting that DH␤E distinguishes more than one
binding site or more than one state of the ␣4␤2* nAChR. In
the latter study, a pseudo-Hill coefficient of 0.9 for S-(Ϫ)-
Fig. 5. Scatchard transforms of saturation S-(Ϫ)-[3H]nicotine binding
isotherms in the absence and presence of three concentrations of NDNI
(top panel) and NONI (bottom panel). Concentrations of NDNI (0.6, 2 and
6 ␮M) and NONI (0.66, 2.2 and 22 ␮M) were chosen based on Ki values
obtained from inhibition curves shown in Fig. 2. Each point represents
the mean values for n ϭ 4 - 5 independent observations from duplicate
measurements at each concentration of S-(Ϫ)-[3H]nicotine. Values for Kd
and Bmax derived from these linear Scatchard analyses are shown in
Table 3.
Reavill et al., 1988). Thus, the present assay reliably mea- nicotine inhibition of [3H]DH␤E binding was observed, sug-
sured interaction with high-affinity S-(Ϫ)-[3H]nicotine gesting that S-(Ϫ)-nicotine interacts with one of multiple
binding sites in striatum.
[3H]DH␤E sites.

408
Wilkins et al.
tions of analog, with no change in Bmax value. The compe-
titive interaction of NDNI and NONI with high affinity
S-(Ϫ)[3H]nicotine binding sites was assessed further using
the Lew and Angus analysis, which alleviates concern re-
garding variability in the estimate of Bmax. The simple, one-
site model best fit the data, corroborating the interpretation
of a competitive interaction of NDNI and NONI with high-
affinity S-(Ϫ)-[3H]nicotine binding sites. These results sug-
gest that NDNI and NONI competitively interact with either
specific amino acid residues directly involved in S-(Ϫ)-
[3H]nicotine binding or with nearby residues allowing for
steric hindrance of the interaction of S-(Ϫ)-[3H]nicotine with
its high-affinity binding site.
To evaluate nAChR subtype selectivity of the N-n-alkylni-
cotinium analogs, correlation analysis of data from both the
present S-(Ϫ)-[3H]nicotine binding assays and previously re-
ported S-(Ϫ)-nicotine-evoked [3H]DA overflow assays
(Wilkins et al., 2002) revealed that NDNI and NONI stand
out as selective analogs for ␣4␤2* and ␣3␣6␤2* nAChR sub-
types, respectively. NDNI exhibited high affinity for S-(Ϫ)-
[3H]nicotine binding sites but did not inhibit S-(Ϫ)-nicotine-
evoked [3H]DA overflow. On the other hand, NONI was a
potent inhibitor of S-(Ϫ)-nicotine-evoked [3H]DA overflow
but exhibited low affinity for S-(Ϫ)-[3H]nicotine binding
sites. Thus, NDNI and NONI appear to be excellent lead
compounds for probing agonist recognition sites on ␣4␤2*
and ␣3␣6␤2* nAChRs, respectively.
The ␣3␣6␤2* subtype has been suggested to mediate S-(Ϫ)-
nicotine-evoked DA release primarily based on sensitivity to
the ␣3␣6␤2-selective antagonists, neuronal bungarotoxin
(Schulz and Zigmond, 1989; Grady et al., 1992) and ␣-cono-
toxin MII (Cartier et al., 1996). The ␣3␣6␤2 selectivity of
these antagonists is indicated by activity in recombinant
Fig. 7. Lack of correlation of N-n-alkylnicotinium analog inhibition of
S-(Ϫ)-nicotine-evoked [3H]DA overflow from superfused striatal slices
with inhibition of S-(Ϫ)-[3H]nicotine binding to striatal membranes. Each
point represents the log IC50 value derived from nonlinear curve fitting of
the inhibition data for S-(Ϫ)-[3H]nicotine binding (Fig. 3) and for the
S-(Ϫ)-nicotine-evoked [3H]DA overflow (taken from Wilkins et al., 2002).
NDNI did not inhibit S-(Ϫ)-nicotine-evoked [3H]DA overflow, and as
such, the highest concentration (100 ␮M) examined was used in the
Pearson’s correlation analysis. Symbols representing each analog are as
indicated in Fig. 3.
N-Alkylation of the S-(Ϫ)-nicotine molecule converts this systems expressing specific nAChR subtypes (Luetje et al.,
potent agonist into analogs that selectively and competitively 1990; Cartier et al., 1996) and by results from nAChR knock-
interact with ␣4␤2* nAChRs. N-n-Alkylnicotinium analogs out mice studies (Champtiaux et al., 2002; Picciotto and
exhibited affinities for S-(Ϫ)-[3H]nicotine binding sites across Corrigall, 2002). Importantly, ␣-conotoxin MII only partially
an ϳ200-fold concentration range, from ϳ90 nM (NDNI) to inhibited nicotine-evoked DA release (Kulak et al., 1997),
ϳ20 ␮M (NONI). The relationship between analog affinity suggesting the potential involvement of other nAChR sub-
for S-(Ϫ)-[3H]nicotine binding sites was a linear function of types in this response, such as ␣4-, ␤2-, and ␤4-containing
n-alkyl chain length, with the exception of NONI. These nAChRs (Picciotto et al., 1998; Sharples et al., 2000). Rat
N-n-alkylnicotinium analogs are larger molecules than substantia nigra neurons express mRNA for ␣3, ␣4, ␣5, ␣6,
S-(Ϫ)-nicotine, and those with longer chain lengths (C9, C10
,
␣7, ␤2, ␤3, and ␤4 subunits (Wada et al., 1989; Dineley-Miller
and C12) were more potent inhibitors of S-(Ϫ)-[3H]nicotine and Patrick, 1992; Charpantier et al., 1998). Inasmuch as
binding than those with shorter chain lengths (C1–C7). The high levels of ␣6 and ␤3 mRNAs are expressed in substantia
higher affinity of the longer n-alkyl chain analogs may reflect nigra DA neurons (Le Nove`re et al., 1996; Goldner et al.,
a stronger association with agonist binding sites on ␣4␤2* 1997; Charpantier et al., 1998), their potential combination
nAChRs, due to increased lipophilic interaction of the carbon with ␣3 and ␤2 subunits in the mediation of S-(Ϫ)-nicotine-
chain with a hydrophobic amino acid-rich region of the pro- evoked DA release in striatum is probable, but has not been
tein near the binding pocket. As such, this lipophilic interac- established conclusively.
tion may stabilize the analog-receptor complex, thereby in-
creasing the affinity for the agonist recognition site by long- interact with both ␣4␤2* and ␣3␣6␤2* nAChR subtypes, but
chain analogs. not with the ␣7* nAChR subtype. As was observed in the
The current results show that N-n-alkylnicotinium analogs
The mechanism of N-n-alkylnicotinium analog interaction interaction of these analogs with ␣3␣6␤2* (Crooks et al.,
with S-(Ϫ)-[3H]nicotine binding sites was determined using 1995; Wilkins et al., 2002), the current SAR reveals that an
two analogs exhibiting extreme Ki values (Ki ϭ 90 nM and 20 increase in affinity at ␣4␤2* nAChRs is dependent on in-
␮M for NDNI and NONI, respectively). NDNI and NONI creasing n-alkyl chain length. Whereas the current receptor
differ structurally by only two methylene units in the alkyl binding assays do not provide information as to whether
chain length. Scatchard analyses of S-(Ϫ)-[3H]nicotine satu- these N-n-alkylnicotinium analogs function as agonists or
ration binding in the absence and presence of NDNI or NONI antagonists at ␣4␤2* receptors, recently, these analogs have
demonstrated that affinity of S-(Ϫ)-[3H]nicotine for its bind- been observed to inhibit S-(Ϫ)-nicotine-evoked 86Rbϩ efflux
ing sites decreased in the presence of increasing concentra- from preloaded rat thalamic synaptosomes, a functional as-

nAChR Subtype Selectivity of N-n-Alkylnicotinium Antagonists
409
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nism of action (L. H. Wilkins, D. K. Miller, J. T. Ayers, P. A.
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Address correspondence to: Linda P. Dwoskin, Ph.D., College of Phar-
macy, University of Kentucky, Lexington, KY 40536-0082. E-mail:
ldwoskin@uky.edu