Escaping the flatlands: newapproaches for studying the dynamicassembly and activation of GPCRsignaling complexesThomas Huber and Thomas P. Sakmar

Laboratory of Molecular Biology & Biochemistry, The Rockefeller University, 1230 York Avenue, New York, NY 10065, USA

Review

Despite significant recent advances in molecular andstructural studies of G protein-coupled receptors(GPCRs), an understanding of transmembrane signaltransduction with chemical precision requires newapproaches. Simple binary receptor–ligand or receptor–G protein complex models cannot adequately describethe relevant macromolecular signaling machineries.GPCR signalosomes undergo complex dynamic assem-bly–disassembly reactions to create allosteric signalingconduits whose properties cannot necessarily be pre-dicted from individual elements alone. The combinatorialpossibilities inherent in a system with hundreds of po-tential components suggest that high-content miniatur-ized experimental platforms and computationalapproaches will be required. To study allosteric effectsinvolved in signalosome reaction pathways, a bottom-upapproach using multicolor single-molecule detectionfluorescence experiments in biochemically defined sys-tems and complemented by molecular dynamics modelsof macromolecular complexes is proposed. In bridgingthe gap between molecular and systems biology, thissynthetic approach suggests a way forward from theflatlands to multi-dimensional data collection.

Do we need a new conceptual framework to study therelationship between structure and function inpharmacological receptors?The past few years have witnessed remarkable progress instructural studies of heptahelical (7TM) receptors, whichcomprise a gene superfamily with more than 700 membersin humans. The list of known crystal structures of GPCRsand their associated binding partners is steadily growing[1] and recently the first chemokine receptor, CXCR4, wasadded [2]. However, understanding GPCR-mediated sig-naling remains an important and challenging problem. Inaddition to the large number of receptors, the number ofpossible combinations of ternary complexes between recep-tors and cellular proteins is almost astronomically large.For example, there are at least 21 Ga, six Gb and 12 Gg

§ This work was supported by NIH Grant EY12049 and the Crowley FamilyFoundation.

Corresponding authors: Huber, T. (hubert@rockefeller.edu); Sakmar, T.P.(sakmar@rockefeller.edu)

410 0165-6147/$ – see front matter � 2011 Elsevier Ltd. All rights reserved. doi

subunits among heterotrimeric G proteins, seven differentGPCR kinases (GRKs), four arrestins and potentially otherscaffold and adaptor proteins. We contend that a fullunderstanding of how GPCRs work in their native mem-brane environment will require new approaches to probereceptor structural dynamics in bilayers and to detectdiscrete receptor–ligand binding events and the formationof ternary complexes between activated receptors and theircellular protein partners. We propose a new strategy fordetermining the relationships between structural dynam-ics and biological function in macromolecular signalingcomplexes from mammalian cells, focusing on the 7TMGPCR signalosome.

GPCRs are not modular structures. For the most part,they cannot be dissected into fragments, expressed inEscherichia coli and reconstituted in artificial environ-ments. Furthermore, recent advances in cell biology andpharmacology prove that the canonical linear GPCR sig-naling pathway (receptor–G protein–effector) and the no-tion that receptors are merely two-state off–on switches aregross oversimplifications. In fact, GPCRs are best thoughtof as exquisite allosteric machines with multiple activestates that define state-specific ligand binding affinitiesand specificities and signal outputs. Our long-term strate-gy, therefore, is to develop a systematic approach and newtools for studying the GPCR signalosome – the complexbetween receptor, ligand and accessory protein(s) in themembrane. Our tactic is to apply several new and excitingtechnologies to elucidate the relationships between recep-tor structural dynamics, the formation of supramolecularcomplexes and signal output. An interdisciplinary ap-proach to this important problem will yield significantadvances and provide a toolbox of technologies that canbe applied to other receptor systems as well. In bridgingthe gap between molecular and systems biology, this syn-thetic approach suggests a way forward from the flatlands*

to multi-dimensional data collection.

Signal processing by GPCR signalosomesThe operations of a GPCR might be analyzed in terms ofthe abstract concept of a probabilistic finite-state machine.

* The term ‘escaping the flatlands’ was inspired by the work of American informa-tion designer Edward Tufte.

:10.1016/j.tips.2011.03.004 Trends in Pharmacological Sciences, July 2011, Vol. 32, No. 7

RG

RGRKRPArr

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Figure 1. Detection and amplification of signals: dynamic GPCR signalosomes as a macromolecular machine. (a) Cyclic sequence (activation, desensitization and recycling)

of the key states in the GPCR signal transduction process. The corresponding characteristic macromolecular complexes or signalosomes are receptor–G protein (RG),

receptor–GPCR kinase (RGRK), phosphorylated receptor–arrestin (RPArr) and phosphorylated receptor–protein phosphatase (RPPP). Note the quasi-irreversible reaction

resulting in dephosphorylated (R) and phosphorylated receptor (RP). (b) Molecular model of a representative GPCR signalosome, the receptor–G protein complex.

Secondary structure cartoon (left) and space-filling model (right) illustrate the receptor–G protein complex in a phospholipid bilayer.

Review Trends in Pharmacological Sciences July 2011, Vol. 32, No. 7

Figure 1a illustrates the key states, transitions and actionsof this signal-processing unit. We can identify the agonist-dependent signaling switch and the phosphorylation-de-pendent desensitization and recycling switch. Moreover,additional compositional states that could be described as afour-way switch are characterized by the alternative mac-romolecular complexes (signalosomes) of receptor eitherwith G protein, kinase, arrestin or phosphatase. On anoth-er level of detail, each of these key states can be expandedto show how each of the proteins can be switched in areceptor-dependent manner between two or more states(Figure I in Box 1). An increasing level of detail (temporaland spatial) reveal that a given state will exhibit additionalmetastable configurational and/or conformational sub-states. Considering this nested hierarchy on the differentlevels of abstraction necessary to capture the reactivedynamics of the GPCR signal-processing unit, it becomesclear that novel experimental and computational methodsare necessary to crack the code of how genetic informationultimately determines pharmacology.

The computational simulation of such systems requiresa hierarchical approach that models each level from theatomic to the macroscopic scale. Moreover, computationalmethods facilitate the integration of diverse types of ex-perimental information into comprehensive models of ex-perimentally inaccessible structures. For example, noexisting experimental method can be used to determinethe structure of a cell membrane in atomic detail. However,it is possible to obtain microsecond-time-scale, all-atommolecular dynamics (MD) simulation models of the recep-tor–G protein complex in a native-like membrane(Figure 1b). In this way, it might be possible to gain insightinto the structural dynamics of this and related GPCRsignalosomes and to describe the non-equilibrium thermo-dynamics of such functional modules. The long-term goalwill be to reconstruct the atom-level mechanism thatexplains the flow of information (energy) through thissignal-processing unit.

Multiscale modeling of macromolecular processesTo obtain useful computational models of biological sys-tems is a central goal in science. One approach is to build

larger systems bottom-up from smaller subsystems. Eachsubsystem itself is built from even smaller sub-subsys-tems. The nested hierarchy of systems has been describedas a modular approach to understanding biological sys-tems [3]. At the lowest level, there are atoms and bonds.Together these correspond to the familiar molecular graph,a network representation of atoms as nodes and bonds asedges, with characteristic length and time scales of nan-ometers and nanoseconds, respectively. Modeling of thesesystems generally involves quantum chemistry methods.

On the next level, there are molecules, intermolecularinteractions and reactions. Here two types of networkformulations are common. The first type is a network thatshows intermolecular interactions analogous to the chem-ical bonds on the previous level, and this is typically foundin proteomics studies of protein–protein interaction net-works in which the individual proteins are nodes and theinteractions are edges. The second type is a network ofreactions that represents the interconversion of molecules,a formulation that is reminiscent of the metabolic pathwaycharts of biochemistry. The protein interaction networkencodes information (i.e. energy) in terms of the strength ofinteractions. The structures corresponding to the con-nected graphs are molecular complexes and functionalmodules of interacting molecules. By contrast, the meta-bolic pathways illustrate the interconversion of nodescorresponding to molecules (which are molecular graphsfrom the first layer) and the edges corresponding to reac-tions that are typically catalyzed by (enzymatic) proteinfunctions. These two types of network are functionallyinterrelated because proteins undergo reactions (post-translational modifications such as phosphorylation anddephosphorylation), and they are therefore also nodes(reactants or substrates or products) of metabolic net-works. At the same time, the enzymatic function of aprotein is dependent on post-translational modificationsand binding partners (allosteric modulators). The enzy-matic function itself has molecular complexes as structuralcorrelates – the transient complexes of the enzyme withreactant(s), the transition state and product(s). Biomolec-ular simulations approximate the energetic interactionsbetween atoms using classical mechanical force fields that

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Box 1. Allosteric modulation of the receptor–G protein interaction in the G protein cycle

Recent reports of the structure of ligand-free opsin and opsin in

complex with an active-state stabilizing peptide derived from a G

protein provide additional clues about the conformation of the active

receptor [58,59]. For most GPCRs, a fully active state might exist in a

ternary complex of an agonist-bound receptor and a G protein. How

the receptor switches to its active state to induce the release of

bound GDP from the G protein a subunit is not known [60]. In the G

protein heterotrimer, the Gbg dimer acts as a guanine nucleotide

dissociation inhibitor (GDI), whereas the receptor functions as a GEF.

At the same time, Gbg enhances the receptor-dependent nucleotide

exchange, possibly by restricting the orientation of Ga on the

membrane. Experimentally, several discrete steps in the G protein

activation pathway have been defined (Figure I). The receptor–G

protein complex first exhibits reduced affinity for the bound GDP

nucleotide [61], the GDP consequently dissociates [62] and finally

GTP/Mg2+ binds to the empty nucleotide-binding pocket and causes

G protein release [63]. In fact, in rod outer-segment disc membranes,

affinities of the receptor–G complex for GDP and GTP were measured

25 years ago [61]. Crystal structures are available for the isolated

Gat[GTPgS] [64] and the Gbg heterodimer [65]. The interaction of

Ga[GTP] with an effector, such as phospholipase C (PLC), or with a

regulator of G protein signaling (RGS) protein results in increased

GTPase activity. These proteins therefore act as GTPase-activating

proteins (GAPs) that accelerate the decay of active G protein.

Moreover, a transition-state analogue of the GTPase reaction,

Gat[GDP–AlF4–/Ca2+] [66], and the hydrolysis product Gat[GDP/

Mg2+] [67] are known in high-resolution atomic detail. In the GTP-

bound form and in the transition state of GTP hydrolysis with GDP

and monophosphate still bound, Mg2+ is bound with high affinity

[66,68], whereas in the GDP-bound Ga the presence of Mg2+ is

controversial [67,69]. In crystal structures of the GDP-bound hetero-

trimeric G protein, no bound Mg2+ has been observed [70,71].

Consequently, it is likely that the GDP-bound receptor–G protein

complex might lack Mg2+ as well. Mechanistically, this would make

sense, especially because Mg2+ inhibited GDP release in a small G

protein [72]. However, Gai mutagenesis experiments suggested a

sequential release mechanism in which Mg2+ release facilitated

subsequent GDP release in engineered G proteins with high basal

nucleotide exchange rates [73]. It is possible that after GTP uptake,

Ga dissociates first, followed by Gbg. Moreover, it is possible that

the GTP-loaded heterotrimer dissociates from the receptor before

separation of the subunits. Furthermore, the standard model of

dissociation of the heterotrimeric G proteins after receptor activation

was challenged by in vivo FRET experiments suggesting that

heterotrimeric Gi protein apparently undergoes subunit rearrange-

ment instead of dissociation on activation [74].

GDP GTP/Mg2+

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Gβγ

Gα[GDP]Gβγ Gα[GDP/Mg2+•Pi]

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Figure I. Examples of allosteric modulators (A) include pharmacological agents (agonists, partial agonists, inverse agonists, neutral antagonists, biased ligands),

dimerizing receptors, chemical receptor modifications (side-chain protonation or phosphorylation) and physicochemical environmental effects (membrane curvature

stress, lipid composition). Despite significant progress in the structural biology of G proteins, little is known about the precise interaction of a G protein with a GPCR (or

GPCR dimer) or how this interaction leads to GDP release and subsequent GTP uptake by the active complex [57]. Intermediate states of the receptor- and Gbg-

dependent nucleotide exchange process and GTPase cycle of Ga are shown. Note that for each state, multiple conformational substates of the participating proteins are

possible. These conformational substates might be rapidly interconverting or, alternatively, they might correspond to metastable long-lived conformations that exhibit

hysteretic behavior (conformational memory). A pharmacological agonist ligand functions as an allosteric modulator (A) that changes the distribution of conformational

substates. The corresponding perturbation of the receptor free energy landscape will affect binding of the inactive heterotrimer, Ga[GDP]Gbg, and destabilization of its

bound GDP. Structures for components of the lower part of the cycle have been reported.

Review Trends in Pharmacological Sciences July 2011, Vol. 32, No. 7

are parameterized to fit the quantum-chemical potentialenergy surface and condensed-phase solvation propertiesof representative molecular fragments. Coarse-grainedmodels simplify calculations for these networks by collect-ing groups of strongly interacting nodes into a single node;for example, one to five coarse-grained beads might repre-sent an amino acid [4].

In metabolic networks, the nodes are molecules and areconnected by a directed graph of reactions. Connected sub-graphs represent reaction pathways. The molecules andreactions can be segregated in different cellular compart-ments, such as plasma membrane and cytoplasm. In thisway, these networks encode localization (spatial informa-tion) and can be mathematically described by systems ofordinary differential equations (ODEs) with concentrationterms encoding the size of nodes and rate constants deter-mining the reactive flux between nodes. Biological systemsoperate out of thermodynamic equilibrium, so the meta-bolic network is typically found in a quasi-steady state.Perturbations of this steady state will lead to a character-

412

istic temporal response profile for the nodal concentrationsin the network.

From molecular to systems biology of GPCRsHere we suggest how (in principle) the pharmacologicalaction of drugs could be analyzed in this bottom-up ap-proach to systems biology. We propose that a completeunderstanding of the 7TM receptor allosteric machinery ona structural and dynamic level might require rethinking ofthe existing terms of molecular biology and pharmacology.In particular, the analysis of structure–function relation-ships using biomolecular simulations will require newapproaches to quantify function on an appropriate level.Biomolecular simulations are useful for comparing andpredicting the relative stability of closely related struc-tures. Therefore, they provide a platform for studyingmodels of homologous structures derived from experimen-tally determined template structures. It is important toanalyze the reaction pathways in signal transduction net-works to identify relevant targets for detailed analysis. For

Review Trends in Pharmacological Sciences July 2011, Vol. 32, No. 7

example, to compare two related pharmacological antago-nists with different affinities for the receptor, free energycalculations with so-called alchemical transformations ofone ligand into another are required. These calculationsare performed once for the receptor-bound state and oncefor solution. The difference, together with the appropriatethermodynamic cycle, should correspond to the changes indissociation constants and the corresponding difference infree energy. In this case, any existing set of crystal struc-tures of antagonist-bound GPCRs is useful.

It is more complicated to compare two related agonists.The two ligands will differ in their affinity for the receptor,but agonist binding will lead to a shift in the equilibrium ofmetastable conformations of the receptors. Uncertaintyabout the structure of these metastable states is a problembecause available crystal structures typically only give theinactive antagonist-bound ground state of the receptor andbiomolecular simulations are currently not powerfulenough to cover the time scales relevant to sample theseslowly interconverting metastable states. Moreover, thepharmacological characterization of an agonist ligand willidentify two different quantities, potency and efficacy.Efficacy reflects the extent of the pharmacological responseat saturating concentrations relative to another (standard)agonist. Potency reflects the concentration necessary toelicit this response, which is typically determined as theconcentration at half-maximal response (EC50).

To account for these two different qualities, the receptorcould be considered as an enzyme that catalyzes the nu-cleotide exchange reaction of the G protein cycle. Note thatthe catalytic action of the receptor on the G protein cycle isnot a classical enzymatic reaction because there is nochange in the covalent bond structure; it is rather guaninenucleotide exchange factor (GEF) activity. In general, theMichaelis constant (Km) and the maximum velocity (Vmax)characterize the enzymatic function. Allosteric modulationof enzymes results in changes in Km (K-type), Vmax (V-type)or both (mixed type).

At a given concentration of G proteins, changes in Km

and/or Vmax will both affect the rate of nucleotide exchange.In addition, the rate of desensitization (by receptor phos-phorylation and arrestin binding) will limit the extent of Gprotein activation in vivo. Therefore, measurement ofGTPgS uptake (a non-hydrolyzable GTP analogue) in plas-ma membrane preparations eliminates the contribution ofdesensitization due to the absence of ATP in the reaction.

Calculations of reaction rates from biomolecular simu-lations are not trivial. If it is possible to identify a transi-tion state then the rates can be related to its stabilityversus the reactants. As shown in Figure I in Box 1, thenucleotide exchange reaction can be broken down intoseveral microscopically reversible reactions. The apparent-ly irreversible GTP uptake reaction is the result of thelarge excess of GTP over GDP in live cells.

Allosteric modulation and the mechanism of functionalselectivity and conformational memoryThe allosteric effect of an agonist on catalysis of thenucleotide exchange reaction of the G protein cycle couldbe the result of changes in the stability of virtually any ofthe intermediates and transition states shown in Figure I

in Box 1. For example, the ability of an agonist-boundreceptor to recruit G proteins might differ from its abilityto induce nucleotide exchange and hence activation of theG protein. This idea stems from the observation thatcertain mutants of rhodopsin bind but fail to activate itsG protein transducin [5]. This raises the question of wheth-er or not a single active state of the agonist-bound receptoris responsible for binding and activation of the G protein.

Allosteric effects are bidirectional. The affinity of ago-nist ligands in the presence and absence of G proteinsfacilitates measurement of the free energy contributions ofallosteric coupling between the agonist and G-proteinbinding sites. This G protein effect on agonist bindingaffinity is dependent on the concentration of GDP (whichdoes not lead to G protein activation) and GTPgS (whichirreversibly activates G proteins). In addition, we need todevelop new methods [such as multicolor single-moleculedetection (SMD) fluorescence methods] to measure the rateconstants of individual assembly and disassembly steps ofthe G-protein-activation reaction pathway. In this novelexperimental paradigm, it is necessary to identify keystates and corresponding molecular assemblies and tocharacterize the transitions between these states. In thisway, allosteric effects of agonists on transition statesshould be experimentally accessible.

The next open question, which is related to the issue of Gprotein specificity, is the mechanism of functional selectiv-ity of different agonists. There is increasing evidence ofligand-specific signaling states of 7TM receptors [6]. Tworelated agonists on one receptor might exhibit differentefficacy ratios for two downstream signaling pathways. Forexample, one ligand might preferentially activate Gq,whereas the other preferentially stimulates Gi. Theremight be preference within a single class, for exampleGi1 versus Gi2. Moreover, it might be possible that thereceptor bound to one ligand or another prefers particularcombinations of Gb and Gg subunits. Alternatively, func-tional selectivity might also arise as a switch from Gprotein signaling to arrestin signaling. In this case, phos-phorylation of the receptor by GPCR kinases (GRKs) isresponsible for the switch. Because Gbg recruits (localizes)some GRKs to the plasma membrane, two ligands mighthave a different ability to allosterically modulate the ca-talysis of this reaction. Moreover, functional selectivitycould result from differential effects on G protein activa-tion and desensitization. Alternatively, the functional se-lectivity might be explained by ligand preference for theternary complexes with G protein or arrestin (after phos-phorylation). There is also a possibility of a phosphoryla-tion ‘barcode’ encoded by selective recruitment of variouskinases.

It has been shown that ligand binding and dissociationkinetics of orthosteric antagonists plays a role in receptorpharmacology resulting in non-competitive (insurmount-able) antagonism versus competitive (surmountable) an-tagonism [7]. By analogy, different agonist ligands mightaffect the structural dynamics within the receptor in a waysuch that the distribution of states is largely unaffected,but instead the kinetics of exchange between them isaffected. Simply stated, one ligand might ‘mobilize’ thereceptor more than another. The mobilized receptor might

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be relevant for activation of a large number of G proteins,whereas desensitization might be independent of receptorconformational mobilization. In this way, two ligandsmight induce the same percentage of high-affinity bindingsites for the G proteins, but only one ligand will promoterapid equilibration with the low-affinity binding site.These are the types of issue that we intend to address.

G protein precouplingYet another related question is the possible role of Gprotein precoupling to the receptor. In one scenario, areceptor without a ligand might preselect a specific Gprotein that it might be less likely to couple to afteractivation. Precoupling of receptor and G protein is unusu-al, but has been reported in some cases [8,9]. For example,recent findings support a physiologically relevant precou-pling mechanism in the case of preassembled, ligand-inde-pendent GPCR signalosomes of the relaxin receptor [10].Conversely, fluorescence recovery after photobleaching(FRAP) and SMD imaging experiments were used to studycoupling of G proteins to cAMP receptor 1, a chemoattrac-tant receptor, in Dictyostelium. The results support aligand-induced coupling mechanism similar to that inrhodopsin and disfavor precoupling [11].

Moreover, precoupling might be required for initialrecognition of agonists. In this case, binding of the Gprotein would switch the conformation of the receptor topresent a high-affinity binding site for the agonist ligand.The initial observation that purified CCR5 chemokinereceptor cannot bind its natural ligands, MIP-1a, MIP-1b and RANTES [12], at all, or with affinity almost threeorders of magnitude lower in certain reconstituted systemscompared to cell membranes [13] might be explained by anunusually strong allosteric effect of G protein binding [14].Here it will be interesting to observe subsequent rounds ofG protein binding and activation. It is possible that after asingle round the agonist dissociates. In this case, theamplification of the ‘particle’ detector would be one, oneactivated G protein for one agonist-binding event. Suchself-limiting detection might have biological advantagesbecause receptors would be instantaneously desensitizedand recycled. Another alternative is that binding of theagonist would switch the conformation of the receptor,which would then present a binding site for the G protein.

Early and relatively primitive SMD fluorescence experi-ments suggested conformational substates (conformation-al complexity) in the b2 adrenoceptor [15], and thisdynamic behavior was cited as one of the reasons thatGPCR crystallization has been especially challenging forhigh-resolution structural analysis [16]. Such conforma-tional complexity and the existence of multiple functionalmicrodomains, switches and ionic locks have also beendemonstrated by mutagenesis and spectroscopy for rho-dopsin [17–19]. However, although the ‘dynamic personal-ity’ of proteins [20] and the conformational complexity ofGPCRs have gained acceptance, it is still unclear whethera single ‘on’ state is responsible for G protein activation ornot. In this case, all other conformational substates mightbe lumped into an ‘off’ ensemble of states.

In addition, there is the possibility of a conformationalmemory effect. SMD fluorescence studies revealed evidence

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of molecular memory phenomena [21,22]. It will be impor-tant to identify conformational memory effects in GPCRs,which might have a potential role in explaining the func-tional dynamics of GPCRs. For example, does the high-affinity ligand-binding state of the receptor, once formedby the action of a G protein, retain this state (at leasttransiently) after G protein dissociation? Relaxation of li-gand- or G protein-induced conformational states might beslow enough to enable the receptor to retain a pharmacolog-ically relevant active-state conformation even after dissoci-ation of the agonist or G protein subunit. In this way, theallosteric interaction between agonist and G protein wouldnot require simultaneous occupancy of both binding sites.Related to the issue of G protein precoupling is a proposal toexplain apparently allosteric interaction of different recep-tors by a G protein ‘steal’ mechanism as an alternative todirect allosterism in a receptor heterodimer [23]. In thislight, it will be important to characterize the ability ofligands to stabilize the receptor–G protein complex withoutthe necessity of inducing nucleotide exchange.

New experimental approaches: the chemokine receptorsignalosomeWe suggest that SMD fluorescence studies will shed lighton the question of how to detect and define ligand-depen-dent signaling states of the receptor. Our own researchprogram is focused on developing SMD fluorescence meth-ods, namely SMD-total internal reflectance fluorescence(TIRF) microscopy, which we will use to study chemokinereceptors in bilayers. Chemokine receptors are involved indirected cell migration – or chemotaxis – of certain celltypes during development, the immune response, inflam-mation, wound healing, stem cell maintenance and prolif-eration, and other physiological processes. Moreover, theyplay a role in the pathophysiology of tumor metastasis andretroviral infections. There are approximately 20 differentchemokine receptors and 50 different types of chemokineligand. There is significant cross-talk or promiscuity inchemokine receptor signaling: several chemokines canbind one receptor, and one chemokine might bind severalreceptors [24]. The pharmacology of chemokines is not wellunderstood. A ligand bound to a receptor might act as anagonist, a partial agonist, a neutral antagonist or aninverse agonist with respect to its ability to alter theequilibrium of inactive and active conformational state(s)of the receptor. The biology of chemokine receptors, withmultiple cell-specific expression patterns, and how theyfunction in a complex milieu of multiple chemokines atdifferent concentrations that change rapidly over time area complete mystery. CCR5 serves as the primary HIV-1 co-receptor and couples predominantly to Gai2b1g2, GRK2and potentially GRK3, and arrestin-2 in host cells [25,26].Besides studying these interactions that are part of thecanonical signal transduction pathway of GPCRs, it will beinteresting to develop methods to observe the supramolec-ular structures involved in early events in HIV-1 entry.

The interaction of the viral envelope protein (gp120–

gp41) with the primary receptor CD4 on target cells resultsin conformational changes within gp120. This new confor-mation of gp120 facilitates binding to the co-receptor(CCR5 or CXCR4) that triggers virus entry, which involves

Review Trends in Pharmacological Sciences July 2011, Vol. 32, No. 7

insertion of the fusion peptide gp41 in the cellular mem-brane. It has been shown that CD4 and CCR5 (or CXCR4)are each organized into homogeneous microclusters in thecell membrane. These CD4 clusters and chemokine recep-tor clusters frequently close enough to interact with asingle HIV-1 virion [27]. It is thought that these micro-clusters are due to association of CCR5 with lipid rafts,which are important for HIV entry [28]. The lipid raftconcept was highly controversial at first, but recentadvances have demonstrated the presence of nanoscale,dynamic ordered assemblies of proteins and lipids that arerich in cholesterol, saturated hydrocarbon chains andsphingolipids [29–32]. We anticipate that SMD experi-ments with chemokine receptors reconstituted in a chemi-cally defined lipid environment will provide insights intothe physicochemical driving forces involved in the forma-tion of these microclusters in live cells. These experimentswill provide a platform for testing the role of other proteins,such as chaperones [33] and other scaffolding or adaptorproteins, in the formation of receptor oligomers. Moreover,it will be exciting to see whether the known lipid effects onrhodopsin can be generalized to chemokine receptors ornot. For example, curvature and hydrophobic forces driveoligomerization and modulate the activity of rhodopsin inthe membrane [4,34–36].

B

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Figure 2. Functional reconstitution of CCR5 in solid-supported tethered phospholipid

depicted structure by sequential perfusion of the different protein solutions in a simple

(C18) trialkoxy-silane. The binding capacity of the C18-modified glass for biotinylated B

biotinylated BSA is further stabilized by neutravidin (A), a deglycosylated form of the tet

rhodopsin 1D4 mAb that recognizes the C-terminal nonapeptide of rhodopsin (C9 tag) is

biotin binding sites are saturated with biotin–PEG2000–DSPE. The mAb captures hete

solution. A lipid bilayer (light green) is formed by dilution of POPC–CHAPS bicelles. The

using BSA as the carrier.

An understanding of the precise mechanisms of phar-macological allosteric GPCR modulators is another issuethat can be addressed using the same technology proposedfor studying the chemokine receptor signalosome. Addi-tions to the pharmacopoeia of drugs targeting the chemo-kine family of GPCRs are urgently needed [37]. Forexample, despite the lack of clinical efficacy of CCR1antagonists in some trials [38], they have the excitingproperty of being able to suppress liver metastasis in coloncancer [39]. Moreover, a CCR5 agonist drug might beexpected to display adverse effects, but a drug that wouldselectively trigger CCR5 internalization would clearly beuseful [40]. Defining the structural dynamics of chemokinereceptor signaling might facilitate rational approaches todrug discovery. Although the development of newapproaches to GPCR-based drug discovery might be along-term consequence of such work, we focus here ondeveloping and applying a useful toolkit and a conceptualframework for studying the structural dynamics of chemo-kine receptor signalosomes.

Supported membranes for surface-selectivespectroscopy and SMD-TIRF microscopy of CCR5We have developed a strategy for functional reconstitutionof CCR5 in solid-supported tethered phospholipid bilayer

B

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bilayer membranes. We developed the following method to self-assemble the

semi-microfluidics chamber [54]. The glass surface is first coated with octadecyl

SA is substantially higher compared to untreated glass [22]. The adsorbed layer of

rameric biotin-binding protein avidin with a more neutral isoelectric point. The anti-

biotinylated specifically on the Fc stem. It is captured by avidin and the remaining

rologously expressed CCR5 with an engineered C-terminal C9 tag from detergent

fluorescently labeled chemokine (CCL3–MIP-1a-Alexa-647) is added in the last step,

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membranes for single-molecule fluorescence experiments(Figure 2). SMD-TIRF experiments facilitate selective exci-tation of fluorophores in the evanescent wave penetratingapproximately 100 nm into the aqueous layer beyond theglass–water interface. Capture of a molecule of interest inthis spatial region facilitates long-term observation of asingle molecule. In this way, slow dissociation and associa-tion processes can be observed and studies of conformationalmemory effects will be possible. Few general methods existto orient proteins on surfaces, especially at high density [41].Solid-supported bilayers are important models of biomem-branes for classes of biophysical experiments [42]. One of thetechnical challenges is how to incorporate transmembraneproteins into these membranes. Two approaches have beensuccessfully used for GPCRs.

In the first approach, a detergent-solubilized receptor israpidly diluted below the critical micellar concentration inthe presence of preformed phospholipid bilayer mem-branes. This method has been used to incorporate rhodop-sin [43], the d-opioid receptor [44], and the b2-adrenoceptorinto black lipid membranes for surface plasmon resonance(SPR) spectroscopy experiments, and the d-opioid receptorinto polyacrylamide-supported lipid bilayers on a fusedsilica cover slip for SMD-TIRF experiments [45]. Thedrawback of this method is that the orientation of themembrane protein is difficult to control [46]. Moreover,protein aggregation competes with the process of incorpo-ration and only a very small fraction of the protein even-tually becomes incorporated into the membrane [43].

The second strategy to incorporate transmembraneproteins into membranes overcomes these shortcomings.It is based on capture of receptors in a defined orientationto the surface, followed by reconstitution of the supportedlipid bilayer by micellar dilution. This method hasbeen used to incorporate biotinylated rhodopsin (with

Box 2. Suitable and emerging technologies for single-molecule s

� Fluorescence correlation spectroscopy (FCS) has been applied to

ligand-binding studies with fluorophore-labeled ligands in cells [75]

or membrane preparations [76].

� Fluorescence intensity distribution analysis (FIDA) is a SMD method

sensitive to brightness. It has been applied as ultra high-throughput

screening (uHTS) [77] to monitor binding of fluorophore-labeled

ligands to receptors in plasma membrane preparations [78].

� Single-particle tracking (SPT) methods have been used to study the

mobility of GPCR fusion proteins with fluorescent proteins [79,80],

enzyme tags (HaloTag or ACP tag) for specific conjugation with

fluorophores [81,82], or epitope tags for visualization with gold-tagged

Fab antibody fragments [79]. SPT has been used to infer receptor

binding of fluorescent protein fusion constructs of heterotrimeric G

proteins [83,84]. It has also been used to monitor the interaction of a

Ga peptide with photoactivated rhodopsin [85]. SPT of fluorescently

labeled antagonist ligands bound to receptors has demonstrated the

presence of short-lived receptor dimers in living cells [80].

� Single-molecule detection (SMD) has been used to visualize

quantum dot-conjugated peptide antagonists bound to receptors

embedded in solid-supported membranes [86].

� High-density lipoprotein (HDL) particles known as nanodiscs [87]

and nanoscale apolipoprotein-bound bilayers (NABBs) [88] have

been used to reconstitute receptors in a native-like phospholipid

matrix. SMD-TIRF microscopy has been used to visualize fluor-

ophore-conjugated receptors reconstituted in nanodiscs [89,90].

� Single-particle electron microscopy (sp-EM) was used to quantify

monomeric and dimeric receptors labeled with nanogold-malei-

416

carbohydrate-specific biotinylation of the receptor on theextracellular side facing the surface) captured by immobi-lized streptavidin for SPR spectroscopy [47], as well as thechemokine receptors CCR5 [12] and CXCR4 [48] for bio-chemical studies, in which both receptors were modifiedwith a C-terminal C9 tag and captured using randomlyoriented 1D4 mAb covalently immobilized on paramagneticpolystyrene beads. Moreover, N-terminal FLAG-tagged,fluorescently labeled b2-adrenoceptor in detergent has beencaptured by biotinylated M1 anti-FLAG mAb immobilizedto streptavidin on biotinylated BSA-covered glass for TIRFexperiments [49]. TIRF experiments have also beenreported for plasma membrane fragments containingNK1 receptor biotinylated in vivo at its C terminus, whichwas subsequently captured by streptavidin immobilized onquartz slides partially covered with biotinylated BSA [50].

Based on a combination of methods from these earlierstudies, we designed a novel strategy suitable for SMD-TIRF experiments on CCR5. This new strategy shouldfulfill the following criteria: (i) glass or fused silica sub-strates; (ii) immunoaffinity-based capture of epitope-tagged receptors from detergent solution in a definedorientation; and (iii) formation of a bilayer membraneindependently of the density of captured transmembraneproteins. Although an earlier study used lipid head-groupbiotinylated phospholipids bound to streptavidin as amembrane anchor [12], in our case it was necessary tointroduce an additional spacer between the biotin-bindingsites of the neutravidin layer and the bilayer membrane tobridge the thickness of the IgG molecule also anchored tothe neutravidin layer. A sufficiently long spacer was pro-vided by biotinyl-PEG2000-DSPE, which can be stretchedto �10 nm [51]. The equilibrium separation depends on thelateral packing density and should be in the range 4–7 nm[52], which is sufficient for globular proteins in the 100-kDa

tudies of GPCRs and higher order complexes

mide site-specifically at a single reactive cysteine and reconstituted

in NABBs under cryo EM conditions [88]. Alternatively, mass

tagging of the receptor with a mAb Fab fragment bound to a C-

terminal epitope can be used to determine the orientation of

receptor dimers by sp-EM in negatively stained samples [88].

� Modular assembly of detergent-solubilized ternary complexes on

beads and rapid mix flow cytometry was used to measure the

dissociation kinetics of these complexes via several alternative

capturing and labeling schemes [91]. Although these experiments

are limited to measurements of larger ensembles, they demon-

strate the feasibility of reconstitution of functional ternary com-

plexes from purified components.

� Atomic force microscopy (AFM) has been used to visualize the

supramolecular (lateral) organization of receptors in membranes

from retinal photoreceptor cells [92].

� Single-molecule force spectroscopy is an AFM technique that has

been applied to study the unfolding of rhodopsin [93].

� Site-specific unnatural amino acid (UAA) mutagenesis can introduce

novel chemical functionalities in correctly folded, post-translationally

modified proteins expressed in mammalian cell cultures. Receptors

modified with keto and azide groups [94,95] facilitate bioorthogonal

labeling reactions to introduce fluorophores suitable for SMD.

� Homogeneous time-resolved fluorescence resonance energy trans-

fer with a conformationally sensitive antibody to CCR5 can be used

to quantify femtomole amounts of receptors [96]. This auxiliary

technology is relevant for the monitoring of a folded receptor

during purification.

Review Trends in Pharmacological Sciences July 2011, Vol. 32, No. 7

range. Moreover, we observed that the formation of sup-ported membranes on dilution of a CHAPS–POPC bicellesystem leads to the formation of vesicles instead of a flatmembrane in some cases. Formation of the desired flatmembrane was critically dependent on the surface densityof the biotinyl-PEG2000-DSPE anchor lipids, and hencethe neutravidin surface density.

The number of SMD fluorescence techniques available islarge and steadily increasing, but for the study of GPCRsignalosomes a smaller number of methods seem to beespecially suitable (Box 2). They are based on (i) the inten-sity and residence time of fluorescence spots, (ii) dual-colorcolocalization (>10 nm), and (iii) Forster resonance energytransfer (FRET; 3–10 nm). The unique feature of SMD-TIRFmethods is that detailed kinetic information can be obtainedfrom observations of microscopic reversibility in a system inmacroscopic equilibrium or under steady-state conditions.In this way, time-dependent pathways of reactions that areimpossible to synchronize at the ensemble level can be

40 μm

40 μ

m

3.0 μm

5.2

μm

(a)

(c) (d)

(b

118 min

Figure 3. Representative SMD-TIRF images of single chemokine molecules bound to CCR

subtraction of static background from hot pixels of the CCD sensor and after application

Gaussian-like spot in 1/v2 noise [55]. The image shows two classes of single-fluorophore

(b) Time series of the indicated region of interest in (a) using an exposure time of 10 s t

labeled chemokines (CCL3–MIP-1a-Alexa-647) bound to CCR5 embedded in a bilayer me

to (a) before image processing. (d) Surface plot showing spot intensity as peaks. Tall sig

of the Alexa-647 signal) are due to hydrophobic fluorescent impurities in a buffer to imp

can be efficiently removed (data not shown) by hydrophobic affinity chromatography of

hundreds of images with a sufficient signal-to-noise ratio to identify individual recepto

followed [53] and this property can be used to determinethe kinetics of transitions between assembly states. Obvi-ously, conventional TIRF experiments can be performed in acomplementary fashion.

We obtained SMD images of single fluorescently labeledchemokines (MIP-1a-Alexa-647) bound to recombinantexpressed CCR5 embedded in a bilayer membrane teth-ered to the surface of a chip (Figure 3). The fluorescencespots represent single fluorescent chemokines that havebound to CCR5. The binding event is visible because itoccurs at a distance that is within the evanescent field ofthe TIRF illumination. The membrane–receptor assemblyis stable for hours and can be interrogated repeatedly usingthe continuous flow-cell strategy described above. Forexample, MIP-1a-Alexa-647 can be washed out of the celland a different concentration of MIP-1a-Alexa-647 or adifferent labeled chemokine can be added in turn. Compe-tition experiments with small molecules or with chemokinemixtures can be carried out as well.

14 14A

14 KODAK 100TMX

13 13A

13 KODAK 100TMX

15 15A

15 KODAK 100TMX

17 17A

17 KODAK 100TMX

16 16A

16 KODAK 100TMX

18 18A

18 KODAK 100TMX

11 11A

11 KODAK 100TMX

10 10A

10 KODAK 100TMX

12 12A

12 KODAK 100TMX)

112 min 113 min 114 min 115 min 116 min 117 min

118 min 119 min 120 min 121 min 122 min 123 min

124 min 125 min 126 min 127 min 128 min 129 min

TRENDS in Pharmacological Sciences

5 in tethered membranes. (a) Image obtained using an SMD-TIRF microscope after

of 2D convolution with a spot-enhancing filter that was the optimal detector for a

spots. One side of the quadratic image corresponds to 40 mm in the sample plane.

aken at 1-min intervals. The bright central spot corresponds to single fluorescently

mbrane (Figure 3) that is visible from 115 to 126 min. (c) Raw image corresponding

nals are from single ligand–receptor complexes. Small signals (�15% of the height

rove photostability and blinking of Alexa-647 [56]. We found that these impurities

the enzyme used (glucose oxidase or catalase). This scheme can be used to acquire

r-bound chemokine molecules before irreversible photobleaching.

417

Review Trends in Pharmacological Sciences July 2011, Vol. 32, No. 7

Escaping the flatlands one molecule at a time:concluding remarksTo elucidate the structural dynamics of the GPCR signal-processing unit it will be necessary to ‘color-code’ differentproteins with fluorescent probes. In biochemically definedsystems, multi-color SMD-TIRF techniques will enable us todetermine the molecular composition of individual proteincomplexes (assembly states) and the equilibrium distribu-tion of different assembly states. A time-ordered descriptionof the assembly–disassembly processes for these complexes,which correspond to transitions between key states or func-tional intermediates, can be obtained. In this way, we willelucidate the potential roles of hysteresis (conformationalmemory), of sequential and/or cooperative processes, and ofallosteric effects. A series of homologous components will beanalyzed for the hypothetical role of these effects in thephenomenon of biased agonism (functional selectivity), ifpossible. It should be noted that this type of information iscomplementary both to structural work on static complexesand to molecular pharmacology and cell biology.

AcknowledgmentsWe thank Dr. A.V. Botelho for help with the development of the tetheredbilayer. This research was supported by an allocation of advancedcomputing resources provided by the National Science Foundation (NSFPACI grants MCB060033 and MCB110043). The computations wereperformed on Kraken and Athena at the National Institute forComputational Sciences (http://www.nics.Tennessee.edu). This work wassupported by NIH grant EY12049 and the Crowley Family Foundation.

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