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INTRODUCTION |
Allosteric transitions of neurotransmitter binding sites remain
poorly understood, despite increased efforts in recent years to map
protein domains important for ligand recognition and ion channel
activation. It is likely that amino acid residues other than those that
mediate initial contact with agonist will be important for inducing
gating transitions. Characterization of receptor-ligand interactions
using site-directed mutagenesis and photolabeling studies provides
limited information as to the state-dependent nature of
ligand binding domains (1). Nevertheless, identification of all
residues lining the neurotransmitter binding-site, irrespective of the
conformational state of the receptor, represents a critical step to
understanding receptor-ligand interactions at allosteric proteins.
Identification of amino acid residues important in agonist/antagonist
binding at
-aminobutyric acid type A receptors
(GABAAR)1 reveals
that the GABA-binding sites are located at
-
subunit interfaces.
Consistent with the agonist-binding site of nicotinic acetylcholine
receptors (nAChR), the GABA-binding site is formed by amino acid
residues clustered in non-continuous protein segments of
the extracellular amino-terminal domains of adjacent subunits. Multiple
residues have been implicated in the formation of this binding site
using a variety of approaches, including site-directed mutagenesis,
photoaffinity labeling, and the substituted-cysteine accessibility
method (SCAM). These include Phe64, Arg66,
Arg119, and Ile120 of the
1
subunit (2-7), in addition to Tyr97, Leu99,
Tyr157, Thr160, Thr202,
Ser204, Tyr205, Arg207, and
Ser209 of the
2 subunit (8-10). Of these
residues, it is likely that some contact agonist/antagonist molecules
directly, some maintain the overall structure of the binding
site, while others mediate conformational dynamics within the site
during allosteric transitions among the resting, active, and
desensitized states.
The GABAAR
1 subunit segment between
Pro174 and Asp191 is homologous in position to
the putative "loop F" of the nAChR (see Fig. 1) (11).
Studies of this segment of the nAChR
/
and
subunits have
identified negatively charged amino acid residues that influence acetylcholine binding, channel gating, and perhaps potassium ion interactions (see Fig. 1) (12-16). Based on the crystal structure of a
soluble acetylcholine-binding protein (AChBP), a protein homologous to
the extracellular domain of the nAChR, the secondary structure of the
loop F region is predicted to be a random coil (17). Strikingly,
the loop F protein sequence is poorly conserved among all
GABAAR subunit isoforms and other related ligand-gated ion
channel subunits and may represent a unique structural element that
could account for differences in agonist affinity, dimensions of
binding pockets, and access pathways important for receptor-ligand interactions. Therefore, an analysis of the structure and the role(s)
of the
1 subunit Pro174-Asp191
segment in ligand binding and ion channel activation is fundamental for
understanding GABAAR function.
The development of SCAM has proved to be very powerful tool for
identifying residues important for the pharmacology of both agonists
and antagonists. Originally developed to identify the channel-lining
residues of ligand-gated ion channels (18), SCAM has gained widespread
use in the study of the ligand binding domains of these channels (2, 3,
9, 10, 19-25). The method entails introduction of successive cysteine
residues, one at a time, within a protein domain and expression of
recombinant receptors in heterologous systems. Solvent accessibility of
a given cysteine is determined by monitoring changes in function
following application of a sulfhydryl-specific modifying reagent (18).
The role of a given residue in the formation of a ligand binding site
is determined by the ability of both agonists and antagonists to impede
modification of the introduced cysteine by the
sulfhydryl-specific reagent.
Here, we used SCAM to examine the structure, solvent accessibility, and
dynamics of the GABAA receptor
1 subunit
Pro174-Asp191 region, which comprises the
putative loop F of the GABA binding pocket. We demonstrate that this
region is highly accessible and adopts a random coil/turn conformation.
In addition, we identify several residues, Val178,
Val180, and Asp183, that likely participate in
forming part of the GABA-binding pocket. Moreover, we provide evidence
that this region of the receptor undergoes conformational
rearrangements during pentobarbital-mediated gating of the channel. The
results are discussed in terms of a homology model of the
GABAAR agonist binding site, based on the recently solved
crystal structure of the AChBP (17).
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EXPERIMENTAL PROCEDURES |
Mutagenesis and Expression in Oocytes--
Rat cDNAs for the
1 and
2 subunits of the GABAA
receptor were used in this study. The
1 cysteine mutants
were engineered using a recombinant polymerase chain reaction method,
as described previously (2, 10, 26). Cysteine substitutions were made in the
1 subunit at Pro174,
Ala175, Arg176, Ser177,
Val178, Val179, Val180,
Ala181, Glu182, Asp183,
Gly184, Ser185, Arg186,
Leu187, Asn188, Gln189,
Tyr190, and Asp191 (Fig.
1). Cysteine substitutions were verified
by restriction endonuclease digestion and double-stranded DNA
sequencing.

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Fig. 1.
The
Pro174-Asp191 segment
(loop F) of the rat GABAAR
1 subunit is aligned with analogous
regions of the rat GABAAR
2 and 2
subunits and rat nAChR ,
, and subunits. The
numbering reflects the position of the residues in the mature
GABAAR 1 subunit. Residues implicated in
acetylcholine binding are circled and include
Asp180, Glu189, Asp174,
Asp175, and Asn182 (12-14, 16), while
residues that line the GABA-binding site are boxed. Residues
implicated in the interactions of divalent cations are
underlined (15, 46). The asterisks (*) indicate gaps in the
amino acid sequence alignment.
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All wild-type and mutant cDNAs were subcloned into the vector pGH19
(27, 28) for expression in Xenopus laevis
oocytes. Oocytes were prepared as previously described (29). cRNA
transcripts were prepared using the T7 mMessage machine (Ambion).
GABAA receptor
2 and
1 or
1 mutant subunits were co-expressed by injection of cRNA
(200-800 pg/subunit) in a 1:1 ratio (
:
). The oocytes were
maintained in ND96 medium (in mM: 96 NaCl, 2 KCl, 1 MgCl2, 1.8 CaCl2 and 5 HEPES, pH 7.4)and
supplemented with 100 µg/ml gentamicin and 100 µg/ml bovine serum
albumin. Oocytes were used 2-7 days after injection for
electrophysiological recordings.
Two-electrode Voltage Clamp Analysis--
Oocytes under
two-electrode voltage clamp were perfused continuously with ND96 at a
rate of ~5 ml/min. The holding potential was
80 mV. The volume of
the recording chamber was 200 µl. Standard two-electrode voltage
clamp procedures were carried out using a GeneClamp500 Amplifier (Axon
Instruments, Inc.). Borosilicate electrodes were filled with 3 M KCl and had resistances of 0.5-3.0 M
in ND96. Stock
solutions of GABA (Sigma) and SR-95531 (Sigma) were prepared in
water, while N-biotinylaminoethyl methanethiosulfonate (100 mM) (MTSEA-biotin, Biotium, Hayward, CA) was prepared in dimethyl sulfoxide (Me2SO). All compounds were prepared
fresh daily and MTSEA-biotin was diluted appropriately in ND96 such that the final concentration of Me2SO was
2%. This
solvent concentration did not affect recombinant
GABAAR.
To measure the sensitivity to GABA, the agonist (0.0001-1
mM) was applied via gravity perfusion or by pipettor
application (~5-8 s) with a 3-15-min washout period between each
application to ensure complete recovery from desensitization. Peak
GABA-activated current (IGABA) was recorded. To
correct for slow drift in the maximum amplitude of the response as a
function of time, concentration-response data were normalized to a low
concentration of GABA (EC2-EC5). Concentration-response curves were generated for each recombinant receptor, and the data were fit by non-linear regression analysis using
GraphPad Prism software (San Diego, CA; graphpad.com). Data were
fit to the following equation I = Imax/(1 + (EC50/[A])n), where
I is the peak amplitude of the current for a given
concentration of GABA ([A]), Imax
is the maximum amplitude of the current, EC50 is the
concentration required for half-maximal receptor activation, and
n is the Hill coefficient.
To measure the sensitivity to SR-95531, GABA (EC50) was
applied via gravity perfusion followed by a brief (20 s) washout period before co-application of GABA (EC50) and increasing
concentrations of SR-95531. The response to the application of SR-95531
and GABA was normalized to the response elicited by the
agonist alone. Concentration-inhibition curves were generated for each
recombinant receptor, and the data were fit by non-linear
regression analysis using GraphPad Prism software. Data were fit to
the following equation: 1
1/(1 + (IC50/[Ant])n), where
IC50 is the concentration of antagonist ([Ant]) that reduces the amplitude of the GABA-evoked current by 50% and
n is the Hill coefficient. KI values
were calculated using the Cheng-Prussof correction:
KI = IC50/(1 + ([A]/EC50)), where [A] is the concentration of GABA
used in each experiment and EC50 is the concentration of
GABA that elicits a half-maximal response for each receptor (30).
Modification of Introduced Cysteine Residues by
MTSEA-biotin--
MTSEA-biotin was the sulfhydryl-specific reagent
used in this study. It is a relatively impermeant compound (31) with
dimensions (14.5 Å unreacted moiety; 11.2 Å reacted moiety) that are
similar to SR-95531 (13.5 Å) but much longer than GABA (4.5 Å).
Methanethiosulfonate reagents react 109-1010
times faster with the ionized thiolate (RS-) form of cysteine than the
unionized form (32). Based on these properties, it is reasonable to
assume that MTSEA-biotin can occupy the GABA-binding site and that this
reagent will principally modify extracellular cysteine residues that
are solvent-exposed.
Oocytes expressing either wild-type or mutant receptors were activated
by GABA (EC50) at regular intervals until the peak current
amplitude varied by
10% on two consecutive applications. Oocytes
were then allowed to fully recover, after which a high concentration of
MTSEA-biotin (2 mM) was applied (2 min). Following MTSEA-biotin application, cells were washed (5 min) with ND96, after
which GABA (EC50) was again applied to determine the effect of MTSEA-biotin application on IGABA. The effect
of MTSEA-biotin was calculated as the difference in the amplitude of
the IGABA before and after MTSEA-biotin
application as follows: (IGABApre
IGABApost/IGABApre) × 100, where post refers to the amplitude of
IGABA following MTSEA-biotin application and
pre refers to the amplitude of IGABA
prior to exposure to MTSEA-biotin.
Rate of Modification of Introduced Cysteine Residues--
Rates
were measured only for those cysteine mutants that had a >40% change
in IGABA following MTSEA-biotin treatment (2 min, 2 mM). The rate at which MTSEA-biotin modified
introduced cysteine residues was measured using low MTSEA-biotin
concentrations as described previously (3). In general, the
concentration of MTSEA-biotin used was 50 µM, with the
exception of A181C (500 nM) and R186C (5 µM).
The experimental protocol is described as follows: GABA
(EC50) application (5 s); ND96 wash-out (25 s); MTSEA-biotin application (10-20 s); ND96 washout (2.2-2.3 min). The
sequence was repeated until IGABA no longer
changed following the MTSEA-biotin treatment (i.e. the
control reaction had proceeded to apparent completion). The individual
abilities of GABA, SR-95531, and pentobarbital to alter the rate of
cysteine modification by MTSEA-biotin were determined by co-applying
either GABA (5 × EC50), SR-95531 (40 × KI), or an activating concentration of
pentobarbital (500 µM) during the MTSEA-biotin pulse. In
all cases, the wash times were adjusted to ensure that currents
obtained from test pulses of GABA (EC50) following exposure
to high concentrations of GABA, SR-95531, or pentobarbital were
stabilized. This ensured complete wash-out of drugs and that any
reductions in the current amplitude were the result of MTSEA-biotin application.
For all rate experiments, the decrease in IGABA
was plotted as a function of the cumulative time of MTSEA-biotin
exposure and fit to a single-exponential decay function using GraphPad Prism software. A pseudo-first order rate constant
(k1) was determined and the second order
rate constant (k2) was calculated by dividing k1 by the concentration of MTSEA-biotin used in
the assay (33). Second order rate constants were determined using at
least two different concentrations of MTSEA-biotin.
Statistical Analysis--
log (EC50) and log
(KI) values were analyzed using a one-way
analysis of variance, followed by a post-hoc Dunnett's test to determine levels of significance between wild-type and mutant receptors. Differences among the second order
(k2) rates of covalent modification of the
various mutants were assessed using the false positive discovery rate
method (34). This method limited the expected percent of false
positives to 5%. The false positive discovery rate is a more
meaningful measure of error in large screening experiments than the
more traditional approach of limiting the probability of one or more
false positives (also known as experiment-wise error control). Before
analysis, the rates were transformed to a log scale to obtain more
normally distributed residuals. Results are reported in the original
scale. Even using this approach, clear trends in the data did not
always achieve significance as has been noted in other large assays
using SCAM (35).
Structural Modeling--
The mature protein sequences of the rat
1 and
2 subunits were homology-modeled
with a subunit of the AChBP (17). The crystal structure of the AChBP
was downloaded from the Research Collaboratory for Structural
Bioinformatics Protein Data Bank (code 1I9B) and loaded into Swiss
Protein Bank Viewer (SPDBV, ca.expasy.ord/spdbv). The
1
protein sequence from Thr12-Ile227 and the
2 protein sequence from
Ser10-Leu218 were aligned with the AChBP
primary amino acid sequence as depicted in Cromer et al.
(36) and threaded onto the AChBP tertiary structure using the
"Interactive Magic Fit" function of SPDBV. The threaded subunits
were imported into SYBYL (Tripos, Inc., St. Louis, MO) where energy
minimization was carried out (<0.5 kcal/Å). The first 100 iterations
were carried out using Simplex minimization (37) followed by 1000 iterations using the Powell conjugate gradient method (38). A
2/
1 GABA-binding site interface was
assembled by overlaying the monomeric subunits on the AChBP scaffold,
the resulting structure was imported into SYBYL, and energy was
minimized. Our model is quite similar to models recently published for
the nAChR and GABAAR ligand binding domains (36, 39). It is
worth noting that positioning of the
1 subunit
Pro174-Asp191 (loop F) region is inexact since
the
1 subunit has low homology to AChBP sequence in this
region and contains three additional amino acid residues. This region
and other regions with insertions were modeled by fitting structures
from a loop data base.
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RESULTS |
Expression and Functional Characterization of GABAAR
1 Subunit Cysteine Mutants--
Cysteine substitutions
were engineered at eighteen individual
positions in the GABAAR
1 subunit
(Pro174, Ala175, Arg176,
Ser177, Val178,
Val179, Val180, Ala181,
Glu182, Asp183, Gly184,
Ser185, Arg186, Leu187,
Asn188, Gln189, Tyr190, and
Asp191) and co-expressed with wild-type
2
subunits in X. laevis oocytes for functional analysis using
the two-electrode voltage clamp method. Expression of most mutant
subunits produced GABA-activated channels with the exceptions of L187C
and Q189C (Fig. 2 and Table I). The lack of functional
expression of receptors carrying the L187C and Q189C mutations may
indicate a role for these residues in receptor synthesis/assembly as
they are conserved in all
GABAAR and glycine receptor subunits. Expression of D183C
produced a significant 7-fold rightward shift in EC50
relative to wild-type values (EC50 = 1.6 µM).
However, the KI values for the competitive antagonist, SR-95531, for mutant receptors were not significantly different from wild-type values (KI = 330 nM). Hill coefficients were not significantly different
from wild type (Table I). In general, the maximum current amplitude was
1-10 µA for wild-type and mutant receptors, with the exception of
R186C (<300 nA).

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Fig. 2.
A, concentration-response curves of
GABA-activated current for wild-type ( ) and recombinant
1 2 receptors carrying the D183C mutation
( ) expressed in Xenopus oocytes. Data were normalized to
peak IGABA for each experiment. Data represent
the mean ± S.E. of at least three independent experiments.
B, concentration-dependence of SR-95531-mediated reduction
of IGABA (EC50) for wild-type ( )
and recombinant receptors carrying the D183C mutation ( ). Data
represent the mean ± S.E. of at least three independent
experiments. The EC50 values, KI
values, and calculated Hill coefficients are summarized in Table
I.
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Fig. 3.
Summary of the effects of MTSEA-biotin (2 mM) on wild-type and mutant receptors. A,
representative current traces demonstrating the effects of MTSEA-biotin
(2 mM) application on GABA-mediated current
(EC50) at wild-type, and V178C-, V180C-, and
A181C-containing receptors. The arrows in the current traces
represent MTSEA-biotin application (2 min), and the breaks in the
current trace represent the subsequent wash (5 min). B,
summary of the maximum effect of MTSEA-biotin at all receptors. Effect
is calculated as % change = ([IGABApost MTSEA-biotin/IGABApre MTSEA-biotin] 1) × 100. Results represent the mean ± S.E. for three to
six experiments. The closed bars indicate values that were
statistically different from wild-type values (p < 0.05). The pattern of accessibility suggests that this domain of the
1 subunit forms a random turn/coil. Cysteine
substitutions are positions 187 and 189 were not tolerated.
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Table I
Concentration-response data for GABA activation and SR-95531 inhibition
of wild-type and mutant receptors expressed in Xenopus oocytes
Data represent the mean ± S.E. for three to four experiments
(n). Values for EC50 and Hill slopes (nH)
were determined from concentration-response data using non-linear
regression analysis with GraphPad Prism software. Hill slopes and log
(EC50) values were analyzed using a one-way analysis of
variance followed by a Dunnett's test to determine the levels of
significance (*, p < 0.01).
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These data suggest that cysteine substitution within this domain of the
GABAAR
1 subunit protein is well tolerated.
A major assumption of SCAM is that the side chain of the introduced
cysteine is in a similar position as the side chain of the native
residue. Since GABA and SR-95531 bind equally well to both mutant and
wild-type receptors, it is likely that the structures of the receptors
are similar.
Modification of Introduced Cysteine Residues by
MTSEA-biotin--
To define the surface accessibility of the
1 subunit P174C-D191C segment, wild type and mutant
receptors were exposed to MTSEA-biotin (2 mM) for 2 min
(Fig. 3). MTSEA-biotin had no effect on wild-type receptors.
MTSEA-biotin significantly reduced IGABA at
P174C (60.5 ± 1.1%, n = 3), R176C (39.3 ± 6.3%, n = 3), S177C (72.4 ± 1.7%,
n = 3), V178C (88.1 ± 3.2%, n = 4), V180C (65.2 ± 2.0%, n = 4), A181C (76.3 ± 2.0%, n = 4), D183C (46.0 ± 8.7%, n = 6) and R186C (44.8 ± 1.7%, n = 4). MTSEA-biotin potentiated IGABA at
N188C (31.3 ± 10%, n = 3). An
apparent lack of reaction (as in the case of A175C, V179C, E182C, and
D191C) may indicate that no reaction has occurred or that the outcome
of modification is functionally silent. It should be noted that most
residues in this region were modified, although the magnitude of the
effect of modification did not always achieve statistical significance (e.g. G184C, S185C, and Y190C). The pattern of solvent
accessibility is not indicative of either a
-strand or an
-helix,
suggesting that this domain of the GABAAR
1
subunit adopts either a loop or a random coil conformation (Fig.
6).
MTSEA-biotin Rates of Reaction--
The rate at which
MTSEA-biotin reacts with a cysteine side chain depends mainly on
the ionization of the thiol group and the access route to the
engineered cysteine (18). A residue in a relatively open, aqueous
environment will react faster than a residue in a relatively
restrictive, non-polar environment. To gain insight into the
physico-chemical environment of the loop F region of the GABA-binding
site, we determined the reaction rate of MTSEA-biotin with
several accessible cysteine mutants (Fig.
4). The rate MTSEA-biotin modified A181C
was ~400-fold faster than the slowest reacting cysteine mutant,
V180C. The rank order k2 values were A181C > R186C = R176C
S177C > D183C
V180C = V178C (Table II).

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Fig. 4.
Rate of MTSEA-biotin modification of D183C,
V180C, and V178C. A, representative GABA-evoked
(EC50) current traces following successive application
(10-20 s) of MTSEA-biotin (50 µM) on
1(D183C) 2 receptors in the absence and
presence of SR-955531 (40 × KI) and GABA
(5 × EC50). B, sequential application of
MTSEA-biotin reduced the amplitude of subsequent GABA-mediated
(EC50) currents. Data were normalized to the current
measured at t = 0 for each experiment and plotted as a
function of cumulative MTSEA-biotin exposure. Data were fit to a single
exponential function to obtain a pseudo-first order rate constant
(k). Second order rate constants (k2)
were calculated by dividing the pseudo-first order rate constant by the
concentration of MTSEA-biotin used (50 µM). Data points
represent the mean ± S.E. for control ( ), GABA ( ),
SR95531( ) for at least three independent experiments.
k2 values are shown in Table II.
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Table II
Second order rate constants for MTSEA-mediated modification of
accessible cysteine residues in the absence and presence of
SR-95531, GABA, and pentobarbital
Data represent the mean ± S.E. of three to six independent
experiments (n) carried out as described under
"Experimental Procedures." Second order rate constants
(k2) were calculated by dividing the pseudo-first
order rate constant by the concentration of MTSEA-biotin used in the
experiments. The concentrations of MTSEA-biotin used were 50 µM (R176C, V178C, V180C, D183C), 500 nM
(A181C), or 5 µM (R186C). GABA (5 × EC50),
SR-95531, (40 × KI), or pentobarbital (500 µM) was co-applied with MTSEA-biotin to determine their
ability to alter the rate of covalent cysteine modification. (*,
p < 0.05; **, p < 0.01, from
control.)
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Effects of GABA and SR-95531 on MTSEA-biotin Rate
Constants--
To determine whether a given cysteine residue lines the
neurotransmitter binding pocket, the rate of MTSEA-biotin modification of an introduced cysteine is measured in the presence of GABA and the
competitive antagonist, SR-95531. We identify a residue as being within
or near the binding site if the rate of covalent modification of the
introduced cysteine is slowed in the presence of both agonists and
antagonists, which presumably promote different conformational changes
within the site. SR-95531 slowed the rate of modification at V178C,
V180C, and D183C by factors of 3.6, 1.9, and 3.5, respectively (Fig. 4,
Table II). GABA slowed the rate of reaction at R176C, V178C, V180C, and
D183C (2.4-, 1.9-, 1.8-, and 3.5-fold, respectively). Protection of
V178C, V180C, and D183C from covalent modification by MTSEA-biotin by
GABA and SR-95531 suggests that the slowing of the MTSEA-biotin
reaction rate results from steric block rather than allosteric changes induced in the protein. It is interesting to note that R176C was protected only by GABA but not SR-95531. S177C was protected
significantly only by SR-95531. While the effects of GABA failed to
reach statistical significance for this mutant, there was a clear trend
in the data to suggest that GABA also slowed the MTSEA-biotin reaction
rate (Table II, Fig. 5).

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Fig. 5.
Summary of the effects of GABA, SR-95531, and
pentobarbital on MTSEA-biotin second order rate constants. Data
were normalized to control second order rate constants (rate measured
when no other compound was present). Co-application of GABA (5 × EC50) or SR95531 (40 × KI)
slowed reaction of MTSEA-biotin at receptors containing the following
mutations: R176C, V178C and D183C, suggesting that they line the
GABA-binding site. Data represent the mean ± S.E. for at least
three experiments. R176C was protected only by GABA, and while not
significant, there is a clear trend in the data to suggest that S177C
was protected by both agonist and antagonist. The rate of covalent
modification at V180C, A181C, and R186C is significantly altered by
pentobarbital (500 µM). *, p < 0.05.
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Effects of Pentobarbital on MTSEA-biotin Rate
Constants--
At wild-type
1
2 or
1
2
2 GABAAR,
the apparent affinity for direct activation by pentobarbital ranges
from 500-700 µM (8, 10). Further, the mean single
channel conductances elicited by GABA and pentobarbital are not
different, suggesting that the open states produced by both ligands is
similar (40). Moreover, mutations that compromise the affinity of GABA
have thus far not affected the affinity or efficacy of barbiturates (8,
10), suggesting that the actions of pentobarbital are mediated from a
site distinct from the GABA-binding site. Therefore, pentobarbital can
be used as a pharmacological tool to assess gating-induced changes in
the GABA-binding site. The rate of modification at R186C was slowed
3.2-fold in the presence of pentobarbital, while the rates of covalent
modification at V180C and A181C were accelerated 1.4- and 2.3-fold,
respectively (Table II, Fig. 5). Thus, these residues act as reporters
of barbiturate-mediated channel gating.
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DISCUSSION |
Structure of the GABA Binding Pocket--
Previous work has
shown that the GABA binding pocket is composed of aromatic
(
1Phe64,
2Tyr97,
2Tyr157,
2Tyr205), hydroxylated
(
2Thr160,
2Thr202,
2Ser204,
2Ser209), and charged amino acid residues
(
1Arg66,
2Arg207). Here, our data demonstrating that
GABA and SR-95531 protect V178C, V180C, and D183C also indicate that
residues in loop F are near the agonist-binding site. An additional
residue, Arg176, may be important for interactions with the
agonist alone as modification of R176C was protected by GABA and not
SR-95531. Barbiturate-mediated receptor activation did not alter MTSEA
modification of R176C, suggesting that the observed slowing of the
derivatization of R176C by GABA was a function of steric block, as
opposed to channel-gating phenomena. Ligands of divergent chemical
structure such as GABA and SR-95531 likely have different contact
points within the GABA-binding site (3). However, the amino acid
residues identified here need not be contact points for
agonist/antagonist molecules, but they may be important for stabilizing
the structure of the GABA-binding site or mediating local movements
important for activation and/or desensitization.
When mapped onto a homology model of the GABA binding site, these
residues appear to be located at the putative entrance of the binding
site (Fig. 6). Using this model, we
measured distances between loop F GABA-binding site residues and core
GABA-binding regions. For example, approximate distances (

, in
Å) include the following: Asp183-Phe200
(9.0), Asp183-Thr202 (16.0),
Asp183-Tyr205 (15.0), and
Asp183-Arg207 (12.0); (

,in Å)
Asp183-Phe64 (12.0)
Asp183-Arg66 (9.0). Whether these distances
reflect the binding site in a resting, open, or desensitized state is
unknown. The AChBP was crystallized in an ill-defined state, lacks an
ion channel, and shows little cooperativity in ligand binding (39, 41).
In addition, the loop F region was not well defined in the AChBP structure (17).

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Fig. 6.
A, model of the GABA-binding site
at the   subunit interface illustrating the random coil
structure of the 1 subunit loop F protein segment.
Regions colored cyan correspond to cysteine mutants that
were not accessible to MTSEA-biotin modification, and those residues
that were accessible are colored yellow. B,
GABA-binding site residues Val178 and Val180
(red) and Asp183 (blue) are
illustrated. C, position of Asp183 in relation
to other core GABA-binding site residues
1Phe64 and 1Arg66
from loop D (yellow), in addition to
2Arg207 and
2Tyr205 of loop C (red). Shown
also is the predicted theoretical distance (12.0 Å) between
2Arg207 and
1Asp183. The predicted distances between
1Asp183 and other core binding site residues
are summarized under "Discussion."
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Previous work has demonstrated that the nAChR loop F is involved in
agonist binding. Using a chemical cross-linker, Czajkowski and Karlin
identified several negatively charged residues in loop F
(
Asp180,
Glu182, and
Glu189) within 9 Å of the
Cys192/Cys193 loop of the
subunit (13).
These data suggest that, at least in some cases, the loop F domain of
the
subunit is in close proximity to residues on the
subunit
that are within the core of the ACh-binding site. In addition, recent
studies have shown that naturally occurring mutations in the loop F
protein chain of the
subunit (D175N, N182Y) alter ACh microscopic
binding affinity and channel gating (16).
Structural Rearrangements during Gating
Transitions--
Allosteric proteins such as ligand-gated ion
channels cycle through a number of affinity states, including a low
affinity resting state, an active open channel state of moderate
affinity and two desensitized states of high and very high affinity,
respectively (42). During these state transitions, a molecule of GABA
likely contacts a number of different residues. Residues important in the initial docking of the ligand may be different than residues involved in stabilizing ligand binding in open and desensitized states.
It is likely that the GABA-binding site undergoes a series of
transitions in which alternate domains of the protein are brought into
closer contact with the ligand during active and desensitized states.
It is equally possible that ligand interactions with amino acids in the
inactive state are entirely different from those in the active and
desensitized states (1), further complicating analysis of agonist
binding segments.
Methanethiosulfonate reagents can be used as reporter molecules to
detect agonist- or drug-induced changes in protein regions that are
distant from the agonist or modulator binding site. GABA-induced structural rearrangements have been reported in the
benzodiazepine-binding site (19) and in the
1 subunit
M2-M3 loop (43). The allosteric modulators, diazepam and propofol,
induce changes in the
1 subunit M3-spanning segment (35,
44). In addition, we have previously demonstrated movements within the
GABA-binding site in response to pentobarbital gating of the channel
(3, 10).
To test the hypothesis that movement of loop F is a plausible ion
channel activation mechanism (14), we measured the rate of covalent
modification of accessible amino acid residues in the presence of
pentobarbital (500 µM). The ability of pentobarbital to
alter the rates of modification of the loop F segment provides an
indirect measure of changes that occur within this region of the
binding cleft in the transition from the resting to the
active/desensitized states. Co-application of pentobarbital and
MTSEA-biotin should capture a receptor state that differs from that
captured by application of MTSEA-biotin alone. Pentobarbital-mediated
acceleration of the rate of modification at V180C (a GABA-binding site
residue) and A181C and the concomitant slowing of the rate of
modification of R186C indicate that Val180 and
Ala181 move to a more accessible environment, while
Arg186 becomes less accessible. These data demonstrate that
the loop F region of the GABA binding site undergoes conformational
rearrangements during receptor activation and/or desensitization. Other
movements within the binding site may also be needed to trigger channel gating. For example, rotations and/or tilting movements of the
2 subunit may move the loop C region of the
GABA-binding site closer to
1 subunit binding segments
(45).
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CONCLUSIONS |
SCAM analysis has enabled us to identify novel residues of the
1 subunit (Val178, Val180, and
Asp183) that contribute to forming the GABA-binding site.
Further, we provide evidence that the domain defined by
Pro174-Asp191 adopts a random coil/turn
conformation. Barbiturate-mediated channel activation suggests that
this segment of the protein undergoes conformational movements during
channel gating. We speculate that this loop of the protein is a dynamic
element that may move closer to the core of the binding site during
allosteric transitions to higher affinity states. While this is a
plausible channel-gating mechanism, corroboration of these SCAM
observations will require studies using chemical cross-linkers to
understand the relative positions of amino acids in this domain during
the transduction of agonist binding to channel opening and desensitization.