Evolution-guided discovery and recoding of
allosteric pathway specificity determinants
in psychoactive bioamine receptors
Gustavo J. Rodrigueza, Rong Yaob, Olivier Lichtargea,b,1, and Theodore G. Wensela,1
aVerna and Marrs Mclean Department of Biochemistry and Molecular Biology and
Medicine, Houston, TX 77030
bDepartment of Molecular and Human Genetics, Baylor College of
Edited by Robert J. Lefkowitz, Duke University Medical Center/Howard Hughes Medical Institute, Durham, NC, and approved March 16, 2010 (received for
review December 22, 2009)
G protein-coupled receptors for dopamine and serotonin control
signaling pathways targeted by many psychoactive drugs. A
puzzle is how receptors with similar functions and nearly identical
binding site structures, such as D2 dopamine receptors and
5-HT2A serotonin receptors, could evolve a mechanism that discri-
neurotransmitters. We used the Difference Evolutionary Trace
(Difference-ET) and residue-swapping to uncover two distinct sets
of specificity-determining sequence positions. One at the ligand-
binding pocket determines the relative affinities for these two
ligands, and a distinct, surprising set of positions outside the
formational rearrangement leading to G protein activation. Thus
interactions via alternate conformational states enforce specificity
independently of the ligand-binding site, such that either one may
be rationally rekeyed to different ligands. The conversion of a
dopamine receptor effectively into a serotonin receptor illustrates
the plasticity of GPCR signaling during evolution, or in pathological
states, and suggests new approaches to drug discovery, targeting
both classes of sites.
allostery ∣ catecholamines ∣ G protein-coupled receptors
and for the effects of therapeutic drugs that target them (1, 2).
The receptors for the neurotransmitters dopamine and serotonin
mediate very different physiological responses to their respective
ligands in regions of the brain where both neurotransmitters
are present. Numerous psychoactive drugs target either the trans-
porters for these ligands (3) or the receptors themselves (4), but
all display limited efficacy and multiple side effects. Remarkably,
the receptors for these functionally distinct neurotransmitters are
predicted, based on 44% sequence identity, to have very similar
structures in their transmembrane (TM) domain, where ligand
binding causes conformational changes that trigger G protein
activation. Biochemical studies of D2 dopamine receptors
(5–8), D2R, and comparisons to crystal structures for the β-adre-
nergic receptor (9, 10), adenosine receptor (11) , and rhodopsin
(12) delineate a set of residues forming the dopamine binding
site, all but three of which are identical in the closely related
5-HT2A serotonin receptor, 5-HT2AR. Thus it seems unlikely
that ligand-contacting residues alone are sufficient to confer
specificity. A full understanding of the mechanism for ligand
discrimination is of intense interest given that 7TMRs make
up about 30% of all therapeutic drugs (13). Currently, most
therapeutic drugs are thought to bind at the orthosteric site,
although many compounds have been shown to bind elsewhere,
at allosteric sites, and to impact ligand binding or receptor
pecificity of ligand recognition by G protein-coupled
receptors (GPCR) is critical both for their biological functions
Here, on the assumption that discrimination between seroto-
nin and dopamine has been important for survival throughout
evolution of metazoan organisms, we used the Evolutionary Trace
(ET) (15) to rank sequence positions in the transmembrane
domain according to their evolutionary importance and identified
a core of residues of high evolutionary importance, including
those specific for the bioamine family, that are in structural
contact with the ligand-binding site through no more than two
intervening residues. Those whose identities differ between
D2R and 5-HT2AR were swapped by site-directed mutagenesis
so that each ETresidue in the 5-HT2AR sequence replaced the
corresponding residue in the D2R. The residue-swapped D2R
constructs, mostly single point mutants, were then tested for their
abilities to activate G proteins in response to dopamine or
serotonin by using a cell-based high-throughput fluorescence
assay. Ligand-binding affinities were also assessed using radioli-
gand competition assays, and cell surface expression levels were
quantified as well, to ensure that each construct was not grossly
misfolded and that similar numbers were available for binding
externally supplied ligands.
Difference Evolutionary Trace Analysis Identified Positions Important
For Bioamine Receptor Activation Mechanism.Initially,ETidentified
one set of residue positions important in all class A GPCR (15)
and, likewise, another set that was important specifically in all
bioamine receptors. The difference between them, as determined
by difference-ET (16, 17) analysis (Fig. 1 and Fig. S1), identified a
in contact with at least one other, and, remarkably, the cluster
surrounds the ligand-binding site, whose position was not consid-
ered in the analysis. Because all of these residues were invariant
between D2R and 5-HT2AR, this bioamine core was then
expanded structurally by up to two shells of evolutionarily impor-
tant contact residues and up to the top 40% of important residues
(Fig. 1E). Of those, a total of 15 residues vary between D2R and
Table S1]. Functional assays verified the hypothesized importance
of all of these residues, as every residue-swapped version of D2R
displayed significantly altered function in one or more assays.
Author contributions: G.J.R., O.L., and T.G.W. designed research; G.J.R. and R.Y. performed
research; G.J.R. and R.Y. contributed new reagents/analytic tools; G.J.R., R.Y., O.L., and
T.G.W. analyzed data; and G.J.R., R.Y., O.L., and T.G.W. wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
1To whom correspondence may be addressed. E-mail: firstname.lastname@example.org or lichtarge@
This article contains supporting information online at www.pnas.org/lookup/suppl/
www.pnas.org/cgi/doi/10.1073/pnas.0914877107PNAS ∣ April 27, 2010 ∣ vol. 107 ∣ no. 17 ∣ 7787–7792
Activation of Gα16in response to dopamine was diminished for
six of the residue swaps: C118S, S193G, T205M, L379F, V381L,
and N418S. Dose-response curves revealed that both the potency
and maximal response to dopamine were diminished for C118S
andS193G, while L379F showedalmost no response to dopamine
(Fig. 2C). Binding affinity for dopamine, as monitored by com-
petition for binding of radiolabeled spiperone (19), an antagonist
that binds with high affinity to all the D2 variants studied except
for V91S, was significantly diminished for four of the residue
swaps with diminished activation, C118S, S193G, L379F,
N418S, and for an additional four residues, V83L, M117F,
Y199F, and L414I (Table S2). Thus 10 of the 15 residue swaps
lead to impaired interactions of D2R with dopamine, indicating
that the corresponding residues in D2R contribute to dopamine
recognition. Because all positions mutated are located within the
transmembrane domains and at least two turns from the cytoplas-
mic face, they are not expected to act through direct alterations in
G protein contacts.
The striking observation that all of the residues with dimin-
ished dopamine binding still bind with high affinity to spiperone
(Table S2) provides further support for the specificity of our
evolution-based approach. Both D2R and 5-HT2AR bind spiper-
one with high affinity, so swapping residues selected for discrimi-
nation between dopamine and serotonin would not be expected
to exclude a common ligand.
Positions Outside the Orthosteric Binding Site Control Specificity For
D2R Activation Without Altering Ligand Affinities. ET-identified
residues also contribute to discrimination against serotonin
responses. The swaps I48T, M117F, N124H, and T205M all
resulted in significantly enhanced responses to serotonin (Fig. 3).
Three different swaps, L41T, F110W, and S193G, all led to
substantial (greater than twofold) increases in affinity for seroto-
nin, and three others, M117F, C118S, and T205M, increased
serotonin affinity by at least 40%. One swap, V91S had its most
dramatic effect when paired with I48T; as described below, this
double mutation yielded dramatic enhancement of serotonin
responsiveness above that displayed by I48T alone. Thus all 15
residue swaps enhanced interactions with serotonin, or dimin-
ished interactions with dopamine, or both (SI Text and Table S3).
In sharp contrast to the results obtained with ET residues
ranked as highly important is the lack of effect of swapping less
important residues. From among 111 transmembrane residues
that are different between D2R and 5-HT2AR, we selected five
residues that met our distance criteria but ranked in the lowest
20th percentile of evolutionary importance and made the corre-
sponding sequence swaps: I105K, A188N, V191L, I195K, and
S409N. Despite their nonconservative character, all of them
yielded dopamine responses similar to those of wild-type D2R,
and none of them yielded enhanced serotonin responsiveness
(Fig. S2). Thus ET rank is a strong predictor of the likelihood
that a residue contributes substantially to ligand specificity.
Because the I48T substitution results in enhanced serotonin
responsiveness without diminished dopamine responsiveness,
we tested the possibility that this substitution simply renders
D2R more promiscuous with respect to ligand discrimination
using natural and synthetic ligands. No effect of this mutation
was observed for responses to histamine, isoproterenol (β-adre-
nergic agonist), quinpirole (D2R agonist), or DOI (2,5-di-
methoxy-4-iodoamphetamine, a partial agonist for 5-HT2AR),
supporting the idea that the evolutionary selection of this
serotonin (Fig. S3).
To test whether the enhanced serotonin responsiveness is
selective for G protein activation or applies to other downstream
which yielded dramatic enhancement of G protein activation by
serotonin, gave rise to almost no effect on this alternate pathway
The Cα atoms, in blue, mapped onto the β2-adrenergic structure (2RH1) of all
positions in the top 20th percentile rank following ET analysis of the trans-
membrane domains of 402 bioamine receptor sequences. (B) Cα atoms, in
cyan, of top 20th percentile positions after ETanalysis of all 2512 class A GPCR
sequences. (C) Bioamine-specific determinants suggested by subtracting set B
(the Class A trace) from set A (the bioamine trace). The residues that cluster in
C define a bioamine-specific core that was further extended to include more
bioamine-specific neighbors (D) or more residues important in all class A
receptors (E) at ranks up to the 40th percentile (see Fig. S1 and Table S1
for details). This set represents 48 candidates for functionally important posi-
tions in bioamine receptors (F), of which 15 have different residues in D2R
and 5-HT2AR (G).
Identification of candidates for specificity-determining residues. (A)
0 10 20 30 40 50 60 70 80
-8.0 -7.5 -7.0 -6.5 -6.0 -5.5 -5.0
Log [Dopamine], M
Ca2þtransients elicited in response to 10 μM dopamine, as measured by fluor-
escence intensity (relative fluorescence units, RFU) changes in a microplate
reader. HEK 293-derived cells stably expressing Gα16were transiently trans-
fected with plasmids expressing D2R WT or indicated mutants, loaded with
dye, and treated with dopamine at t ¼ 10 s. (B) Dopaminemaximal responses
normalized by receptor surface expression. D2R WT response was defined
as 100% (Dashed Line). Eight mutations (Red) reduced receptor responsive-
ness to dopamine. Data represent mean ? S:E:M. (*, P < 0.05; **, P < 0.001).
(C) Dopamine-dose-response curves for D2RWT (▴), I48T (•), N124H (▾) and
S193G (♦). Curves are four parameter fits as described in SI Text. (D) Positions
that reduced dopamine response (α C) mapped onto the β2-adrenergic
Mutation of ET positions in D2R alters dopamine response. (A) Typical
www.pnas.org/cgi/doi/10.1073/pnas.0914877107Rodriguez et al.
(Fig. 3 G–J). Thus its “filtering” function is specific for those
conformational changes required for G protein coupling but
not those required for phosphorylation and arrestin binding. In
contrast, the L379F mutation rendered D2R refractory to inter-
nalization by either dopamine or serotonin. Although this muta-
concentrations of these used in the internalization assays were
high enough to be saturating. Thus this residue allosterically
controls conformational switches required for both G protein
activation and internalization.
Our working hypothesis is that the 15 ETresidues targeted in
this study work together to confer responsiveness to dopamine
while minimizing responsiveness to serotonin. Unfortunately, a
version of D2R with residue swaps at all positions appears to
be improperly folded, as judged by a complete lack of response
to either dopamine or serotonin. It seems likely that additional
residues, perhaps further still from the ligand-binding site, may
need to be swapped to allow proper folding in the context of
all 15 residue swaps. However, we did find that combining ligand
swaps can lead to additive or possibly synergistic effects (Fig. 4).
The S193G mutation confers diminished dopamine affinity and
enhanced serotonin affinity, without much effect on maximal
responses, whereas the N124H and I48T mutations diminish
dopamine responsiveness and enhance serotonin responses with-
out much effect on affinities. Combining S193G with either
N124H or I48T yields a receptor that is more like a serotonin
receptor and less like a dopamine receptor in both its affinities
and responsiveness. Moreover, combining N124H and I48T
swaps yields higher serotonin responsiveness than either swap
by itself. The most dramatic effect was observed when V91S
was combined with I48T to yield a receptor whose serotonin
responsiveness exceeds the response of WT D2R to saturating
The most striking conclusions from these results are that
(i) evolutionary importance is a strong predictor of determinants
of ligand specificity; (ii) ligand-specific responsiveness, or efficacy
the structural level; and (iii) specificity of responsiveness is
determined by residues that almost certainly do not contact the
ligand, in contrast to binding affinity, which is largely determined
by ligand-contacting residues. The first conclusion derives from
the observations that all highly ranked ETresidues tested signifi-
cantly affected ligand binding or responsiveness, whereas poorly
can be drawn partly from the observation that there were only
three residue swaps, F110W, C118S, and S193G, that resulted
in both significantly lower dopamine affinity and significantly
higher serotonin affinity, and these are the only three found at
positions whose corresponding residues are less than 4 Å from
the ligand in structures of rhodopsin (12), β2-adrenergic receptor,
and β1-adrenergic receptor (9, 10). These residues have been
previously proposed to be at the surface of the orthosteric binding
enhancement of serotonin responsiveness, I48T, M117F, N124H,
Log [Dopamine], M
Log [Serotonin], M
0 10203040 50607080
Log [Serotonin], M
05 10152025 30
051015 20 2530
dependence of responses of I48Tand D2RWT to serotonin. (C) Maximal 5-HTresponses normalized by surface expression (mean ? SEM) with WT D2R response
defined as 100% (Dashed Line). Four mutations (Red) yielded significant enhancement (p < 0.01). (D) Mutations with enhanced 5-HT responses (Red) and
inactivating position L379 (Blue) are mapped onto the β2-adrenergic structure. One mutation, S193G, lowered dopamine affinity (E) and enhanced serotonin
affinity (F). Specifically bound [3H] binding was measured in the presence of the indicated concentrations of competing ligands (mean ? SEM). g–j. Receptor
internalization was determined by loss of surface expression using immunofluorescence in HEK WT (G and H) or cells stably expressing Gα16(I and J), that were
cotransfected with receptor and β-arrestin-EGFP cDNAs. Cells were treated with either 10μM dopamine (G and I) or 10 μM serotonin (H and J).
Enhanced serotonin responses in D2R with ET residue swaps. (A) Typical Ca2þtransients, recorded as in Fig. 2, in response to 10 μM 5-HT. (B) Dose
Rodriguez et al. PNAS
April 27, 2010
M117F, all are at positions at least 10 Å from the ligands in the
β-adrenergic receptor structures. T205M paradoxically displays
enhanced dopamine binding but reduced dopamine responsive-
ness. Thus a set of proximal residues largely determine binding
affinities, whereas more distant residues constitute a specificity-
into G protein-activating conformational changes at the cytoplas-
mic face. Of great interest is the observation that the filtering
function may or may not be specific for G protein activation.
Agonist binding also induces activation of an alternate signaling
pathway via GPCR kinases (GRKs), β-arrestin binding, and inter-
nalization (23). The observation that one residue, L379, is essen-
tial for the conformational changes directing both pathways,
whereas another, I48, isselective for Gprotein activation suggests
the intriguing possibility that manipulating specific ETresidues by
used to bias ligand activation toward specific effectors and down-
stream pathways, i.e., to enhance functional selectivity or “biased
agonism”(25, 26) for experimental or therapeutic purposes.
These conclusions have important implications for our under-
standing of how allosteric coupling of agonist binding to distant G
protein activation has evolved to discriminate between related
ligands and for improving rational approaches to drug design.
Considerable prior evidence has pointed to the importance of
structural features distinct from the binding site that are impor-
tant for allosteric coupling of agonist binding and G protein
activation. These include the DRY motif near the cytoplasmic
end of TM3 (27–29) and a glutamate residue (E368 in D2R)
in TM6 that forms a salt bridge (“ionic lock”) to the arginine
in DRY, as well as tryptophan and proline residues involved
in a “rotamer toggle” in TM6 (30, 31), and the NPXXY motif
in TM7. Unlike the residues identified in this study, however,
these conformational switches are largely invariant, suggesting
they mediate universal mechanisms within Class A GPCR that
are unlikely to contribute to ligand specificity. By contrast, the
present results highlight a previously undescribed set of more
variable residues that communicate ligand binding to these
generic switch motifs in a ligand-specific way. TM3 residues
C118 and M117 are in direct contact with the tryptophan of
the rotamer toggle switch, and TM2 residue V83L may commu-
nicate with this switch through intervening water molecules that
occupy a cavity in the structure (Fig. S4). Likewise TM6 residues
L379 and V381, TM7 residue N418, and TM1 residue I48 are
positioned so as to influence the NPXXY motif residues through
intervening waters. Several of the 15 residues are located on TM3
or TM6, helices that undergo relative motion upon activation
(32, 33). These results not only reveal the existence of residues
with the unique function of conferring ligand specificity through
conformational filtering but also demonstrate that they can be
identified computationally and mutated rationally to reprogram
efficacy in an allosteric pathway to respond to alternate bound
ligands, much as the tumblers of a lock may be adjusted to
different keys. The spatial separation of the residues identified
here emphasizes the cooperative nature of the allosteric switch-
ing induced by ligand-binding in GPCR, with a requirement
for concerted movements by multiple structural elements within
the transmembrane domain.
From a therapeutic perspective, our results also suggest a
paradigm shift in rational, structure-based drug design. Currently
ligand functional groups and contact residues in the binding
pocket. The results presented here imply that only limited
on such interactions, but that drugs directed to sites outside the
evolution to maximize response specificity might yield dramatic
improvements in specificity and/or efficacy either alone or in
combination with conventional binding-pocket-directed drugs.
Allosteric modulators of this type have already been identified
for metabotropic glutamate receptors (34) and in a cannabinoid
receptor (35). The sites defined by the residues identified in this
study represent potential targets for rational drug design.
In addition to the ligand-specificity determinants identified
here in D2R, ET has previously successfully identified residues
80 7060 5040
080 7060 504030 20 10
Log [Serotonin], M
Log [Dopamine], M
data for dopamine (A and B) or 5-HT (C and D) for D2R WT, I48T, S193G,
and the indicated double mutants are shown. Activation data are represen-
tative traces for 10 μM dopamine (A) or 5-HT (C). Specific binding (B and D)
was determined and curves calculated as in Fig. 3.
Enhanced effects of combined mutations. Activation and binding
www.pnas.org/cgi/doi/10.1073/pnas.0914877107Rodriguez et al.
critical for function in rhodopsin and related Class A GPCR (16)
as well as residues that discriminate between G protein
signaling and arrestin signaling in the β2-adrenergic receptor
(24). Combining the evolutionary trace with crystal structures
or homology models of target receptors will be an important part
of this approach to drug discovery.
The essential features of the approach are as follows. ETranks
the importance of every residue based on whether its sequence
variations correlate mostly with major or with minor evolutionary
divergences (15). This is the computational equivalent of labora-
tory experiments that measure residues importance by how much
their mutations perturb the functional response of an assay. In
practice, starting with a protein family, its aligned sequences,
and the associated divergence tree, ET identifies and ranks best
alignment positions that vary between major branches but that
have low variation entropy within each one of these branches.
Conversely, it will rank poorly positions that vary even between
closely related species (36). Important properties of top-ranked
ETresidues are that they cluster spatially within the structure of
a representative family member (37), that these clusters identify
functional sites (38), and that they efficiently guide experiments
to functional determinants (24, 39–42). Although individual case
studies cannot guarantee generality, structural motifs of just a
few top-ranked ET residues also prove sufficient to predict
protein function on a structural proteomic scale, which is consis-
tent with accurate and large-scale identification of key functional
Although there are several useful approaches for identifying
functionally important sites in GPCR, the efficiency of the
approach described here for finding specificity determinants rests
on the likelihood that virtually every amino acid substitution at
every position has been tested in the course of evolution so that
the evolutionary record of variation and of divergence provides
orders of magnitude more information than any strictly experi-
mental approach such as random or targeted mutagenesis or
accessibility to chemical modification (46). In particular, these
approaches are unlikely to predict residues critical for ligand-se-
information primarily about the orthosteric binding site.
Beyond its practical implications, the recoding of efficacy by
individual mutations casts a unique light on GPCR evolutionary
mechanisms. Our observations that single residue variations
trigger diverse, sometimes opposite, efficacy changes in distinct
ligands implies that, during evolution, single point variations
can perturb simultaneously ligand affinities, efficacies, andpoten-
tially bias toward downstream signaling pathways, as suggested by
the successful use of ET-guided mutations to reprogram effector
bias (24). Over evolutionary time, variations would probe a large
array of functional changes that reprogram the type, distribution,
andstrengths ofcouplingsbetween extracellular upstreamligands
and intracellular downstream responses, thus providing, from a
network perspective, an evolutionary switchboard mechanism to
constantly reconfigure the inputs and outputs at GPCR nodes.
Material and Methods
Evolutionary Trace Analysis. Evolutionary trace analyses were performed with
the real-value ET (38) in bioamine and class A GPCRs using 402 and 2512
sequences, respectively. These sequences were gathered from GPCRDB and
aligned separately using ClustalW. As before, alignments were performed
on 195 gapless seven transmembrane helix residues, because the loops are
highly divergent (16). The residues ranked in the top 20th percentile of
importance in the bioamine specific and Class A traces were mapped onto
the β2-adrenergic receptor (PDB 2RH1, Fig. S1) and clustered significantly:
with z scores of 12.7 and 12.5, respectively (47). The difference between them
revealed a significant cluster (z score ¼ 5.4) of 10 amino acids traced in
bioamine receptors and not in Class A overall (Fig. S1C). Eight of these
bioamine-specific positions clustered within 4.5?Å of each other and thus
formed a structurally determined core of residues (z score 7.1, Fig. S1C) that
should be especially important to bioamine receptor specific functions.
An additional nine residues that are important at the 20th percentile for
class A GPCRs as a whole, are within 4.5?Å of this initial set (Fig. S1F).
Sequence comparison between D2R and 5-HT2AR reveals that all but one
of these 17 positions are identical. Extending the criteria to include both Class
A and bioamine-specific ET residues to the 40th percentile and within
4.5?Å any of the above 17 positions expanded the target residues to 48
(Fig. S1 J and N). Of these, 15 vary between D2 and 5-HT2A receptors and
were used for functional-swapping experiments (Fig. S1O). The sequences
and alignments inputs, as well as the trace rank file outputs used for these
analyses, may be found and reproduced on our GPCR difference-ET server at
http://mammoth.bcm.tmc.edu/gpcr/diff_GPCRpaper.html. (The visual tool
available in beta version.)
Mutagenesis and Cell Transfection. The cDNA clone for human dopamine
D2Rlongreceptor was obtained from the Missouri S&T cDNA Resource Center
(www.cdna.org). D2R mutants were generated using the QuikChange muta-
genesis kit (Stratagene, La Jolla, CA) and confirmed by DNA sequencing (Lone
Star Labs, Houston). All mutants were generated in the human D2Rlong
tagged in the N-terminal with the HA epitope.
HEK cells (American Type Culture Collection, Manassas, VA) were stably
transfected with the Gα16cDNA (a gift from M. Simon, Caltech) using lipofec-
tamine 2000 (Invitrogen, Carlsbad, CA) as described by the manufacturer.
Cells were maintained in Dulbecco’s modified Eagle’s medium with 10%
L-glutamine, and G418 (250 μg∕l). Cells were grown in a 37°C humidified
environment with 5% CO2. For receptor activation assays, HEK-Gα16cells
were reverse transfected in poly-D-lysine-coated 96-well plates and assays
performed 48 hrs post transfection.
Calcium Release Assays. At the time of assay, cells were washed once with
Krebs/Ringer/Hepes (KRH) buffer (120 mM NaCl, 4.7 mM KCl, 2.2 mM
CaCl2, 10 mM Hepes, 1.2 mM KH2PO4, 1.2 mM MgSO4, pH 7.4) supplemented
with 1.8 g∕L glucose. Cells were incubated with 2.5 μM Fluo-4 AM (Invitro-
gen) for 1 hr at room temperature with pluronic acid F-127 (final conc. 0.02%
v∕v), and maintained in 1 mM probenecid to inhibit dye efflux. Ca2þ-en-
hanced fluorescence was detected using a Synergy HT plate reader (Biotek,
Winooski, VT). Fluorescence was measured for 10 s to establish baseline, and
then at t ¼ 10 seconds, drugs (diluted in KRH) were injected into the well and
fluorescence measured every half second for 1 min. On the same plate,
receptor surface expression was detected using immunofluorescence. Briefly,
cells were fixed with 4% paraformaldehyde for 1hr at RT. Cells were incu-
bated with Phosphate Saline buffer (PBS) supplemented with 5% donkey
serum (Jackson ImmunoResearch, West Grove, PA) followed by incubations
with a mouse anti-HA epitope (Santa Cruz Biotechnologies, Santa Cruz, CA)
and Alexa Fluor 488-conjugated donkey antimouse antibody (Invitrogen).
Receptor activation data were normalized by the receptor surface expression
and traces plotted using GraphPad Prism. Baseline was subtracted to all
traces. In some experiments immunolabeling was also carried out in the pre-
sence of detergent (0.1% Triton X in TBST with 5% Donkey serum) to check
for any major differences in the ratios of surface receptor to total receptor.
Internalization Assays. HEK WTor HEK-Gα16cells were transfected, fixed, and
protein expression (total and surface) determined as described above. Cells
were cotransfected either with receptor-expressing plasmids alone, or with
equal amount of receptor and β-arrestin-EGFP cDNAs. Forty eight h after
transfection, either HEK WT or HEK-Gα16were treated at 37 °C with 10 μM
dopamine or 5-HTat different time points. Immunodetection was performed
by incubating the cells with mouse anti-HA antibody followed by incubations
with an Alexa Fluor 594-conjugated donkey antimouse antibody. Endpoint
fluorescence values were detected using a Synergy HT plate reader. Cells
transfected with pcDNA 3.1ðþÞ instead of receptor cDNA were used to
subtract nonspecific fluorescence.
[3H] Spiperone Binding. Membranes were prepared from transiently trans-
fected HEK-Gα16 cells. 48 h after transfection, cells were scrapped and centri-
fugedat1000 × gfor5minat4 °C,andthepelletswereresuspendedin1mlof
with protease inhibitors. The homogenates were centrifuged at 13;500 × g
for 10 min at 4 °C, and the membrane pellets (from a confluent 100-mm dish)
were resuspended by homogenization in 1 ml of binding buffer (10 mM Tris,
150 mM NaCl, pH 7.4). Aliquots of membrane suspension were incubated in
binding buffer either with different concentrations of the antagonist [3H]
spiperone (in saturation binding experiments) or with increasing concentra-
tions of agonists or antagonists in the presence of 0.6 nM [3H] spiperone
for 90 min at RT prior to filtration through Whatman GF/C filters using a
Rodriguez et al.PNAS
April 27, 2010
96-well Inotech filtration apparatus and counted using a Beckman LS1701
ing less nonspecific binding in the presence of 1 μM sulpiride (Sigma Aldrich,
St. Louis). Saturation and competition binding data were analyzed by
nonlinear regression analysis using GraphPad Prism 3.0 (GraphPad Software,
San Diego), and the equation, B ¼ BmaxL∕ðL þ KdÞ, where B is bound spiper-
the data from the competition studies to a one-site competition model. Ki
values were determined using the equation Ki¼ IC50∕ð1 þ L∕KDÞ, where L
is the concentration of radioligand, and KDis the spiperone concentration
for half-maximal binding of [3H] spiperone in the absence of competitor.
ACKNOWLEDGMENTS. We thank Monica Galaz Montoya for performing some
assays and Rhonald Lua for help with the difference-ETserver. This work was
supported by grants from the National Institutes of Health (GM066099 and
GM079656 to O.L.) and by the Welch Foundation (Q0035 to T.G.W.) and NIH
training fellowships (T90 DK070109 and T15 LM007093 to G.J.R.).
1. Huber T, Menon S, Sakmar TP (2008) Structural basis for ligand binding and specificity
in adrenergic receptors: Implications for GPCR-targeted drug discovery. Biochemistry
2. GetherU (2000) Uncoveringmolecular mechanismsinvolvedin activationof G protein-
coupled receptors. Endocr Rev 21:90–113.
3. Rothman RB, Baumann MH (2006) Therapeutic potential of monoamine transporter
substrates. Curr Top Med Chem 6:1845–1859.
4. Gonzalez-Maeso J, Sealfon SC (2009) Agonist-trafficking and hallucinogens. Curr Med
5. Javitch JA (1998) Mapping the binding-site crevice of the D2 receptor. Adv Pharmacol
6. Simpson MM, et al. (1999) Dopamine D4/D2 receptor selectivity is determined by a
divergent aromatic microdomain contained within the second, third, and seventh
membrane-spanning segments. Mol Pharmacol 56:1116–1126.
7. Kalani MY, et al. (2004) The predicted 3D structure of the human D2 dopamine
receptor and the binding site and binding affinities for agonists and antagonists. Proc
Natl Acad Sci USA 101:3815–3820.
8. Lan H, Durand CJ, Teeter MM, Neve KA (2006) Structural determinants of pharmaco-
logical specificity between D(1) and D(2) dopamine receptors. Mol Pharmacol
9. Cherezov V, et al. (2007) High-resolution crystal structure of an engineered human
beta2-adrenergic G protein-coupled receptor. Science 318:1258–1265.
10. Warne T, et al. (2008) Structure of a beta1-adrenergic G-protein-coupled receptor.
11. Jaakola VP, et al. (2008) The 2.6 angstrom crystal structure of a human A2A adenosine
receptor bound to an antagonist. Science 322:1211–1217.
12. Palczewski K, et al. (2000) Crystal structure of rhodopsin: A G protein-coupled recep-
tor. Science 289:739–745.
13. Overington JP, Al-Lazikani B, Hopkins AL (2006) How many drug targets are there?.
Nat Rev Drug Discov 5:993–996.
14. Leach K, Sexton PM, Christopoulos A (2007) Allosteric GPCR modulators: Taking
advantage of permissive receptor pharmacology. Trends Pharmacol Sci 28:382–389.
15. Lichtarge O, Bourne HR, Cohen FE (1996) An evolutionary trace method defines
binding surfaces common to protein families. J Mol Biol 257:342–358.
16. Madabushi S, et al. (2004) Evolutionary trace of G protein-coupled receptors reveals
clusters of residues that determine global and class-specific functions. J Biol Chem
17. RaviscioniM, HeQ, SalicruEM,Smith CL, LichtargeO(2006) Evolutionaryidentification
of a subtype specific functional site in the ligand binding domain of steroid receptors.
18. Ballesteros J, Weinstein H (1995) Integrated methods for modeling G-protein coupled
receptors. Methods Neurosci 25:366–428.
19. Al-Fulaij MA, Ren Y, Beinborn M, Kopin AS (2007) Identification of amino acid
determinantsofdopamine2receptor syntheticagonistfunction.JPharmacolExp Ther
20. Kenakin T (2002) Efficacy at G-protein-coupled receptors. Nat Rev Drug Discov
21. Wiens BL, Nelson CS, Neve KA (1998) Contribution of serine residues to constitutive
and agonist-induced signaling via the D2S dopamine receptor: Evidence for multiple,
agonist-specific active conformations. Mol Pharmacol 54:435–444.
22. Javitch JA, Li X, Kaback J, Karlin A (1994) A cysteine residue in the third membrane-
spanning segment of the human D2 dopamine receptor is exposed in the binding-site
crevice. Proc Natl Acad Sci USA 91:10355–10359.
23. DeWire SM, Ahn S, Lefkowitz RJ, Shenoy SK (2007) Beta-arrestins and cell signaling.
Annu Rev Physiol 69:483–510.
24. Shenoy SK, et al. (2006) beta-arrestin-dependent, G protein-independent ERK1/2
activation by the beta2 adrenergic receptor. J Biol Chem 281:1261–1273.
25. Urban JD, et al. (2007) Functional selectivity and classical concepts of quantitative
pharmacology. J Pharmacol Exp Ther 320:1–13.
26. Violin JD, Lefkowitz RJ (2007) Beta-arrestin-biased ligands at seven-transmembrane
receptors. Trends Pharmacol Sci 28:416–422.
27. Kim JH, Cho EY, Min C, Park JH, Kim KM (2008) Characterization of functional roles of
DRY motif in the 2nd intracellular loop of dopamine D2 and D3 receptors. Arch Pharm
28. Rovati GE, Capra V, Neubig RR (2007) The highly conserved DRY motif of class A G
protein-coupled receptors: Beyond the ground state. Mol Pharmacol 71:959–964.
29. Bhattacharya S, Hall SE, Li H, Vaidehi N (2008) Ligand-stabilized conformational states
of human beta(2) adrenergic receptor: Insight into G-protein-coupled receptor
activation. Biophys J 94:2027–2042.
30. Shi L, et al. (2002) Beta2 adrenergic receptor activation. Modulation of the proline
kink in transmembrane 6 by a rotamer toggle switch. J Biol Chem 277:40989–40996.
31. Swaminath G, et al. (2005) Probing the beta2 adrenoceptor binding site with catechol
reveals differences in binding and activation by agonists and partial agonists. J Biol
32. Farrens DL, Altenbach C, Yang K, Hubbell WL, Khorana HG (1996) Requirement of
rigid-body motion of transmembrane helices for light activation of rhodopsin. Science
33. Sheikh SP, Zvyaga TA, Lichtarge O, Sakmar TP, Bourne HR (1996) Rhodopsin activation
blocked by metal-ion-binding sites linking transmembrane helices C and F. Nature
34. Kew JN (2004) Positive and negative allosteric modulation of metabotropic glutamate
receptors: Emerging therapeutic potential. Pharmacol Ther 104:233–244.
35. Price MR, et al. (2005) Allosteric modulation of the cannabinoid CB1 receptor.
Mol Pharmacol 68:1484–1495.
36. Mihalek I, Res I, Lichtarge O (2004) A family of evolution-entropy hybrid methods for
ranking protein residues by importance. J Mol Biol 336:1265–1282.
37. Madabushi S, et al. (2002) Structural clusters of evolutionary trace residues are
statistically significant and common in proteins. J Mol Biol 316:139–154.
38. Yao H, et al. (2003) An accurate, sensitive, and scalable method to identify functional
sites in protein structures. J Mol Biol 326:255–261.
39. Sowa ME, et al. (2001) Prediction and confirmation of a site critical for effector
regulation of RGS domain activity. Nat Struct Biol 8:234–237.
40. Ribes-Zamora A, Mihalek I, Lichtarge O, Bertuch AA (2007) Distinct faces of the Ku
heterodimer mediate DNA repair and telomeric functions. Nat Struct Mol Biol
41. Kobayashi H, Ogawa K, Yao R, Lichtarge O, Bouvier M (2009) Functional rescue
of beta-adrenoceptor dimerization and trafficking by pharmacological chaperones.
42. Baameur F, et al. (2010) Role for the regulator of G-protein signaling homology
domain of G protein-coupled receptor kinases 5 and 6 in beta 2-adrenergic receptor
and rhodopsin phosphorylation. Mol Pharmacol 77:405–415.
43. Ward RM, et al. (2009) Evolutionary Trace Annotation Server: automated enzyme
function prediction in protein structures using 3D templates. Bioinformatics
44. Ward RM, et al. (2008) De-orphaning the structural proteome through reciprocal
comparison of evolutionarily important structural features. PLoS ONE 3:e2136.
45. Erdin S, Ward RM, Venner E, Lichtarge O (2010) Evolutionary trace annotation of
protein function in the structural proteome. J Mol Biol 396:1451–1473.
46. Javitch JA, et al. (2000) The fourth transmembrane segment of the dopamine D2
receptor: Accessibility in the binding-site crevice and position in the transmembrane
bundle. Biochemistry 39:12190–12199.
47. Mihalek I, Res I, Yao H, Lichtarge O (2003) Combining inference from evolution and
geometric probability in protein structure evaluation. J Mol Biol 331:263–279.
www.pnas.org/cgi/doi/10.1073/pnas.0914877107Rodriguez et al.
BIOPHYSICS AND COMPUTATIONAL BIOLOGY
Correction for “Evolution-guided discovery and recoding of
allosteric pathway specificity determinants in psychoactive bio-
amine receptors,” by Gustavo J. Rodriguez, Rong Yao, Olivier
Lichtarge, and Theodore G. Wensel, which appeared in issue
17, April 27, 2010, of Proc Natl Acad Sci USA (107:7787–7792;
first published April 12, 2010; 10.1073/pnas.0914877107).
The authors note that the e-mail address for Olivier Lichtarge
should have appeared as email@example.com.
| May 18, 2010
| vol. 107
| no. 20www.pnas.org/cgi/doi/10.1073/pnas.1005260107