G protein-coupled receptors (GPCRs) have long been studied as monomeric units, but accumulating evidence demonstrates that these receptors can also form homo- and hetero-oligomers with far-reaching functional implications. The properties emerging from these oligomers can be distinct from those of the monomeric protomers in ligand binding (El-Asmar et al., 2005; Casadó-Anguera et al., 2016; Guitart et al., 2014; Yoshioka et al., 2001), G protein coupling (Cristóvão-Ferreira et al., 2013; Cordomí et al., 2015; González-Maeso et al., 2007; Lee et al., 2004; Rashid et al., 2007), downstream signaling (Liu et al., 2016; Hilairet et al., 2003; Rozenfeld and Devi, 2007; Borroto-Escuela et al., 2010), and receptor internalization/desensitization (Ecke et al., 2008; Stanasila et al., 2003; Faklaris et al., 2015). With the vast number of genes identified in the human genome (Takeda et al., 2002), GPCRs are able to form a daunting number of combinations with unprecedented functional consequences. The existence of this intricate network of interactions among GPCRs presents major challenges and opportunities for the development of novel therapeutic approaches (Dorsam and Gutkind, 2007; Farran, 2017; Schonenbach et al., 2015; Ferré et al., 2014; Bräuner-Osborne et al., 2007; George et al., 2002). Hence, it is crucial to identify the driving factors of GPCR oligomerization, such that this process can be more deliberately controlled to facilitate structure-function studies of GPCRs.

GPCR oligomers with multiple interfaces (Song et al., 2020; Ghosh et al., 2014; Periole et al., 2012; Fanelli and Felline, 2011; Liu et al., 2012) can give rise to myriad ways by which these complexes can be formed and their functions modulated. In the crystal structure of the turkey β₁-adrenergic receptor (β₁AR), the receptor appears to dimerize via two different interfaces, one formed via TM4/TM5 (transmembrane domains 4/5) and the other via TM1/TM2/H8 (helix 8) contacts (Huang et al., 2013). Similarly, in the crystal structure of the antagonist-bound μ-opioid receptor (μ-OR), the protomers also dimerize via two interfaces; however, only one of them is predicted to induce a steric hindrance that prevents activation of both protomers (Manglik et al., 2012), hinting at interface-specific functional consequences. A recent computational study predicted that the adenosine A_2A receptor (A_2AR) forms homodimers via three different interfaces and that the resulting dimeric architectures can modulate receptor function in different or even opposite ways (Fanelli and Felline, 2011). All the above-mentioned interfaces are symmetric, meaning that the two protomers are in face-to-face orientations, hence forming strictly dimers. Asymmetric interfaces, reported in M₃ muscarinic receptor (Thorsen et al., 2014), rhodopsin (Fotiadis et al., 2006; Fotiadis et al., 2003; Liang et al., 2003), and opsin (Liang et al., 2003), are in contrast formed with the protomers positioning face-to-back, possibly enabling the association of higher-order oligomers.

Not only do GPCRs adopt multiple oligomeric interfaces, but various studies also suggest that these interfaces may dynamically rearrange to activate receptor function (Xue et al., 2015). According to a recent computational study, A_2AR oligomers can adopt eight different interfaces that interconvert when the receptor is activated or when there are changes in the local membrane environment (Song et al., 2020). Similarly, a recent study that combined experimental and computational data proposed that neurotensin receptor 1 (NTS₁R) dimer is formed by ‘rolling’ interfaces that coexist and interconvert when the receptor is activated (Dijkman et al., 2018). Clearly, meaningful functional studies of GPCRs require exploring their dynamic, heterogeneous oligomeric interfaces.

The variable nature of GPCR oligomeric interfaces suggests that protomers of GPCR oligomers may be connected by tunable interactions. In this study, we explore the role of an intrinsically disordered region (IDR) of a model GPCR that could engage in diverse non-covalent interactions, such as electrostatic interactions, hydrogen bonds, or hydrophobic interactions. These non-covalent interactions are readily tunable by external factors, such as pH, salts, and solutes, and further can be entropically enhanced by depletion interactions (Asakura and Oosawa, 1958; Yodh et al., 2001; Marenduzzo et al., 2006), leading to structure formation and assembly (Milles et al., 2018; Wicky et al., 2017; Szasz et al., 2011; Goldenberg and Argyle, 2014; Qin and Zhou, 2013; Cino et al., 2012; Soranno et al., 2014; Zosel et al., 2020). In a system where large protein molecules and small solute particles typically coexist in solution, assembly of the protein molecules causes their excluded volumes to overlap and the solvent volume accessible to the non-protein solutes to increase, raising the entropy of the system. The type and concentration of solutes or ions can also remove water from the hydration shell around the proteins, further enhancing entropy-driven protein-protein association in what is known as the hydrophobic effect (Tanford, 1980; Tanford, 1978; Pratt and Chandler, 1977; van der Vegt et al., 2017). This phenomenon is applied in the precipitation of proteins upon addition of so-called salting-out ions according to the Hofmeister series (Hofmeister, 1888; Hyde et al., 2017; Yang, 2009). The ability of IDRs to readily engage in these non-covalent interactions motivates our focus on the potential role of IDRs in driving GPCR oligomerization.

The cytosolic carboxy (C-)terminus of GPCRs is usually an IDR (Tovo-Rodrigues et al., 2014; Jaakola et al., 2005). Varying in length among different GPCRs, the C-terminus is commonly removed in structural studies of GPCRs to enhance receptor stability and conformational homogeneity. A striking example is A_2AR, a model GPCR with a particularly long, 122-residue, C-terminus that is truncated in all published structural biology studies (Song et al., 2020; Fanelli and Felline, 2011; García-Nafría et al., 2018; Sun et al., 2017; Lebon et al., 2011; Xu et al., 2011; Doré et al., 2011; Jaakola et al., 2008; Carpenter et al., 2016; Hino et al., 2012). However, evidence is accumulating that such truncations—shown to affect GPCR downstream signaling (Koretz et al., 2021; Navarro et al., 2018a; Jain and McGraw, 2020)—may abolish receptor oligomerization (Schonenbach et al., 2016; Svetlana and Devi, 1997). A study using immunofluorescence has demonstrated that C-terminally truncated A_2AR does not show protein aggregation or clustering on the cell surface, a process readily observed in the wild-type form (Burgueño et al., 2003). Our recent study employing a tandem three-step chromatography approach uncovered the impact of a single-residue substitution of a C-terminal cysteine, C394S, in reducing the receptor homo-oligomerization in vitro (Schonenbach et al., 2016). In the context of heteromerization, mass spectrometry and pull-down experiments have demonstrated that A_2AR-D₂R dimerization occurs via direct electrostatic interactions between the C-terminus of A_2AR and the third intracellular loop of D₂R (Ciruela et al., 2004). These results all suggest that the C-terminus may participate in A_2AR oligomer formation. However, no studies to date have directly and systematically investigated the role of the C-terminus, or any IDRs, in GPCR oligomerization.

This study focuses on the homo-oligomerization of the human adenosine A_2AR, a model GPCR, and seeks to address (i) whether the C-terminus engages in A_2AR oligomerization, and if so, (ii) whether the C-terminus forms multiple oligomeric interfaces. We use size-exclusion chromatography (SEC) to assess the oligomerization levels of A_2AR variants with strategic C-terminal modifications: mutations of a cysteine residue C394 and a cluster of charged residues ³⁵⁵ERR³⁵⁷, as well as systematic truncations at eight different sites along its length. We complemented our experimental study with an independent molecular dynamics (MD) simulation study of A_2AR dimers of five C-terminally truncated A_2AR variants designed to mirror the experimental constructs. We furthermore examined the oligomerization level of select C-terminally modified A_2AR variants under conditions of varying ionic strength ranging from 0.15 to 0.95 M. To verify whether the A_2AR oligomer populations are thermodynamic products, we performed a series of SEC analyses on SEC-separated monomer and dimer/oligomer populations to observe their repopulation into monomer and dimer/oligomer populations. Finally, to test whether the C-termini directly and independently promote A_2AR oligomerization, we recombinantly expressed the entire A_2AR C-terminal segment sans the transmembrane portion of the receptor and investigated its solubility and assembly properties with increasing ion concentration and temperature. This is the first study designed to uncover the role of the intrinsically disordered C-terminus on the oligomerization of a GPCR.

This study systematically investigates the role of the C-terminus on A_2AR oligomerization and the nature of the involved interactions through strategic mutations and truncations at the C-terminus as well as modulation of the ionic strength of solvent. All experiments were done at 4°C unless stated otherwise. The experimental assessment of A_2AR oligomerization relies on SEC analysis.

SEC quantifies A_2AR oligomerization

We performed SEC analysis on a mixture of ligand-active A_2AR purified from a custom synthesized antagonist affinity column (Figure 1—figure supplement 1A). Distinct oligomeric species were separated and eluted in the following order: high-molecular-weight (HMW) oligomer, dimer, and monomer (Figure 1 and Figure 1—figure supplement 1B). This peak assignment has been verified with SEC-MALS (multi-angle light scattering) experiments, as detailed in a previous publication (Schonenbach et al., 2016). The population of each oligomeric species was quantified as the integral of each Gaussian from a multiple-Gaussian curve fit of the SEC signal. The reported standard errors were calculated from the variance of the fit that do not correspond to experimental errors (see Supplementary file 1 and Figure 1—figure supplement 2 for SEC data corresponding to all A_2AR variants in this study). As this study sought to identify the factors that promote A_2AR oligomerization, the populations with oligomeric interfaces (i.e., dimer and HMW oligomer) were compared with those without such interfaces (i.e., monomer). Hence, the populations of the HMW oligomer and dimer were expressed relative to the monomer population in arbitrary units as monomer-equivalent concentration ratios, henceforth referred to as population levels (Figure 1).

Figure 1 with 2 supplements see all

Download asset Open asset

C-terminal amino acid residue C394 contributes to A_2AR oligomerization

To investigate whether the C-terminus of A_2AR is involved in receptor oligomerization, we first examined the role of residue C394 as a previous study demonstrated that the mutation C394S dramatically reduced A_2AR oligomer levels (Schonenbach et al., 2016). The C394S mutation was replicated in our experiments, alongside other amino acid substitutions for the cysteine, namely alanine, leucine, methionine, or valine, generating five A_2AR-C394X variants. The HMW oligomer and dimer levels of A_2AR wild-type (WT) were compared with those of the A_2AR-C394X variants. We found that the dimer level of A_2AR-WT was significantly higher than that of the A_2AR-C394X variants (WT: 1.14; C394X: 0.24–0.57; Figure 2A). A similar result, though less pronounced, was observed when the HMW oligomer and dimer levels were considered together (WT: 1.34; C394X: 0.59–1.21; Figure 2A). This suggests that residue C394 plays a role in A_2AR oligomerization, and even more prominently in A_2AR dimerization.

Figure 2

Download asset Open asset

Figure 2—source data 1

Raw western blot of size-exclusion chromatography-separated dimeric populations of A_2AR-WT with and without 5 mM TCEP.

https://cdn.elifesciences.org/articles/66662/elife-66662-fig2-data1-v2.tif.zip

Download elife-66662-fig2-data1-v2.tif.zip

Figure 2—source data 2

Raw western blot of size-exclusion chromatography-separated dimeric populations of A_2AR-WT with and without 5 mM TCEP.

MagicMark protein ladder (LC5602) is used as the molecular weight standard.

https://cdn.elifesciences.org/articles/66662/elife-66662-fig2-data2-v2.tif.zip

Download elife-66662-fig2-data2-v2.tif.zip

Figure 2—source data 3

Raw western blot of size-exclusion chromatography-separated dimeric populations of A_2AR-Q372ΔC with and without 5 mM TCEP.

https://cdn.elifesciences.org/articles/66662/elife-66662-fig2-data3-v2.tif.zip

Download elife-66662-fig2-data3-v2.tif.zip

Figure 2—source data 4

Raw western blot of size-exclusion chromatography-separated dimeric populations of A_2AR-Q372ΔC with and without 5 mM TCEP.

MagicMark protein ladder (LC5602) is used as the molecular weight standard.

https://cdn.elifesciences.org/articles/66662/elife-66662-fig2-data4-v2.tif.zip

Download elife-66662-fig2-data4-v2.tif.zip

Figure 2—source data 5

Raw size-exclusion chromatography data of A_2AR-WT and C394X variants.

https://cdn.elifesciences.org/articles/66662/elife-66662-fig2-data5-v2.xlsx

Download elife-66662-fig2-data5-v2.xlsx

To test whether residue C394 stabilizes A_2AR dimerization by forming disulfide linkages, we incubated the SEC-separated dimers of A_2AR-WT and A_2AR-Q372ΔC with 5 mM of the reducing agent TCEP, followed by SDS-PAGE and western blotting. The population of each species was determined as the area under the densitometric trace. The dimer level was then expressed as monomer-equivalent concentration ratios in a manner similar to that of the SEC experiment described above. Upon incubation with TCEP, the dimer level of the A_2AR-WT sample decreased from 1.14 to 0.51 (Figure 2B). This indicates that disulfide bond formation via residue C394 is one possible mechanism for A_2AR dimerization. Interestingly, the dimer level of the A_2AR-Q372ΔC sample also decreased from 0.68 to 0.22 (Figure 2B). This suggests that there may exist other inter-A_2AR disulfide bonds that do not involve residue C394. Still, in both cases, a clearly visible population of A_2AR dimer persists, even after reduction of disulfide bonds via TCEP (Figure 2B), suggesting that there must be additional interfacial sites that help drive A_2AR dimer/oligomerization.

C-terminus truncation systematically reduces A_2AR oligomerization

To determine which interfacial sites in the C-terminus other than the disulfide-bonded cysteines drive A_2AR dimer/oligomerization, we carried out systematic truncations at eight sites along the C-terminus (A316, V334, G344, G349, P354, N359, Q372, and P395), generating eight A_2AR-ΔC variants (Figure 3A). The A_2AR-A316ΔC variant corresponds to the removal of the entire disordered C-terminal region and is used in all published structural studies of A_2AR (Martynowycz et al., 2020; Song et al., 2020; García-Nafría et al., 2018; Sun et al., 2017; Carpenter et al., 2016; Hino et al., 2012; Xu et al., 2011; Lebon et al., 2011; Doré et al., 2011; Jaakola et al., 2008; Fanelli and Felline, 2011). Using the SEC analysis described earlier (Figure 1), we evaluated the HMW oligomer and dimer levels of the A_2AR-ΔC variants relative to that of the A_2AR full-length-wild-type (FL-WT) control. Both the dimer and the total oligomer levels of A_2AR decreased progressively with the shortening of the C-terminus, with almost no oligomerization detected upon complete truncation of the C-terminus at site A316 (Figure 3B). This result shows that the C-terminus drives A_2AR oligomerization, with multiple potential interaction sites positioned along much of its length.

Figure 3

Download asset Open asset

Figure 3—source data 1

Raw size-exclusion chromatography data of A_2AR-WT and C-terminally truncated ΔC variants.

https://cdn.elifesciences.org/articles/66662/elife-66662-fig3-data1-v2.xlsx

Download elife-66662-fig3-data1-v2.xlsx

Interestingly, there occurred a dramatic decrease in the dimer level between the N359 and P354 truncation sites, from a value of 0.81 to 0.19, respectively (Figure 3B). A similar result, though less pronounced, was observed on the total oligomer level, with a decrease from 1.09 to 0.62 for the N359 and P354 truncation sites, respectively (Figure 3B). Clearly, the C-terminal segment encompassing residues 354–359 (highlighted in black in Figure 3A) is a key constituent of the A_2AR oligomeric interface.

Since segment 354–359 contains three consecutive charged residues (³⁵⁵ERR³⁵⁷; Figure 3A), which could be involved in electrostatic interactions, we hypothesized that this ³⁵⁵ERR³⁵⁷ cluster could strengthen inter-protomer A_2AR-A_2AR association. To test this hypothesis, residues ³⁵⁵ERR³⁵⁷ were substituted by ³⁵⁵AAA³⁵⁷ on A_2AR-FL-WT and A_2AR-N359ΔC to generate A_2AR-ERR:AAA variants (Figure 3C). We then compared the HMW oligomer and dimer levels of the resulting variants with controls (same A_2AR variants but without the ERR:AAA mutations). We found that the ERR:AAA mutations had varied effects on the dimer level: decreasing for A_2AR-FL-WT (ctrl: 0.49; ERR:AAA: 0.29) but increasing for A_2AR-N359ΔC (ctrl: 0.33; ERR:AAA: 0.48) (Figure 3C). In contrast, the ERR:AAA mutations reduced the HMW oligomer level of both A_2AR-FL-WT (ctrl: 0.88; ERR:AAA: 0.66) and A_2AR-N359ΔC (ctrl: 0.68; ERR:AAA: 0.38) (Figure 3C). Consistently, the ERR:AAA mutation lowered the total oligomer level of both A_2AR-FL-WT (ctrl: 1.37; ERR:AAA: 0.94) and A_2AR-N359ΔC (ctrl: 1.01; ERR:AAA: 0.85) (Figure 3C). These results suggest that the charged residues ³⁵⁵ERR³⁵⁷ participate in A_2AR oligomerization, with a greater effect in the context of a longer C-terminus and for forming higher-order oligomers. The question then arises as to what types of interactions are formed along the C-terminus that help stabilize A_2AR oligomerization.

C-terminus truncation disrupts complex network of non-bonded interactions necessary for A_2AR dimerization

Given that the structure of A_2AR dimers or oligomers is unknown, we next used MD simulations to seek molecular-level insights into the role of the C-terminus in driving A_2AR dimerization and to gain an understanding of what types of interactions and sites may be involved in this process. First, to explore A_2AR dimeric interface, we performed coarse-grained (CG) MD simulations using the Martini force field (see Materials and methods for details). The Martini force field can access the length and time scales relevant to membrane protein oligomerization, albeit at the expense of atomic-level details. We carried out a series of CGMD simulations on five A_2AR-ΔC variants designed to mirror the experiments by systematic truncation at five sites along the C-terminus (A316, V334, P354, N359, and C394). Our results revealed that A_2AR dimers were formed with multiple interfaces, all involving the C-terminus only (Figure 4A). The transmembrane heptahelical bundles were not a part of the dimeric interfaces as they all showed distances greater than the minimum distance criterion of 7 Å for interacting helices. The vast majority of A_2AR dimers were symmetric, with the C-termini of the protomers directly interacting with each other. A smaller fraction of the dimers had asymmetric orientations, with the C-terminus of one protomer interacting with other parts of the other protomer, such as ICL2 (the second intracellular loop) and ICL3 (Figure 4A).

Figure 4

Download asset Open asset

Figure 4—source data 1

Detailed data regarding the multiple interfaces of A_2AR and the network of non-bonded interactions that stabilize these interfaces.

(A) Dimer configurations from cluster analysis in GROMACS of the 394-residue variant. (B) Average number of residues that form electrostatic contacts as a function of sequence length of A_2AR. (C) Average number of residues that form hydrogen bonds as a function of sequence length of A_2AR.

https://cdn.elifesciences.org/articles/66662/elife-66662-fig4-data1-v2.xlsx

Download elife-66662-fig4-data1-v2.xlsx

Our observation of multiple A_2AR oligomeric interfaces, which is consistent with previous studies (Fanelli and Felline, 2011; Song et al., 2020), suggests that tunable, non-covalent intermolecular interactions may be involved in receptor dimerization. We first dissected two key non-covalent interaction types: electrostatic and hydrogen bonding interactions. Electrostatic interactions were calculated from CGMD simulations, while hydrogen bonds were quantified from atomistic MD simulation as the CG model merges all hydrogens into a CG bead and hence cannot report on hydrogen bonds. This analysis was performed on the symmetric dimers as they constituted the more dominant population. With the least truncated A_2AR variant containing the longest C-terminus, A_2AR-C394ΔC, we observed an average of 15.9 electrostatic contacts (Figure 4B) and 26.7 hydrogen bonds (Figure 4C) between the C-termini of the protomers. This result shows that both electrostatic interactions and hydrogen bonds can play important roles in A_2AR dimer formation.

Upon further C-terminus truncation, the average number of both electrostatic contacts and hydrogen bonds involving C-terminal residues progressively declined, respectively reaching 5.4 and 6.0 for A_2AR-A316ΔC (in which the disordered region of the C-terminus is removed) (Figure 4B, C). This result is consistent with the experimental result, which demonstrated a progressive decrease of A_2AR oligomerization with the shortening of the C-terminus (Figure 3B). Interestingly, upon systematic truncation of the C-terminal segment 335–394, we observed in segment 291–334 a steady decrease in the average number of electrostatic contacts, from 10.4 to 7.4 (Figure 4B). This trend was even more pronounced with hydrogen bonding contacts involving segment 291–334 decreasing drastically from 21.0 to 7.0 as segment 335–394 was gradually removed (Figure 4C). This observation that truncation of a C-terminal segment reduces inter-A_2AR contacts elsewhere along the C-terminus indicates that an allosteric mechanism of dimerization exists, in which an extended C-terminus of A_2AR stabilizes inter-A_2AR interactions near the heptahelical bundles of the dimeric complex. These results demonstrate that A_2AR dimers can be formed via multiple interfaces and stabilized by an allosteric network of electrostatic interactions and hydrogen bonds along much of its C-terminus.

Ionic strength modulates oligomerization of C-terminally truncated A_2AR variants

So far, we have demonstrated that the C-terminus clearly plays a role in forming A_2AR oligomeric interfaces. However, it remains unclear what the driving factors of A_2AR oligomerization are and whether the oligomeric populations are thermodynamic products. The variable nature of A_2AR oligomeric interfaces suggests that the main driving forces must be non-covalent interactions, such as electrostatic interactions and hydrogen bonds. Modulating the solvent ionic strength is an effective method to identify the types of non-covalent interaction(s) at play. Specifically, with increasing ionic strength, electrostatic interactions are weakened (based on Debye–Hückel theory, most electrostatic bonds at a distance greater than 5 Å are screened out at an ionic strength of 0.34 M at 4°C) and depletion interactions are enhanced with salting-out salts, while hydrogen bonds remain relatively impervious. For this reason, we subjected various A_2AR variants (FL-WT, FL-ERR:AAA, N359ΔC, and V334ΔC) to ionic strength ranging from 0.15 to 0.95 M by adding NaCl (buffer composition shown in Materials and methods). The HMW oligomer and dimer levels of the four A_2AR variants were determined and plotted as a function of ionic strengths.

The low ionic strength of 0.15 M should not affect hydrogen bonds or electrostatic interactions if present. We found that the dimer and total oligomer levels of all four variants were near zero (Figure 5). This is a striking experimental observation: despite being shown to play a role in stabilizing A_2AR dimers according to our MD simulations (Figure 4B, C), we can conclude that electrostatic and hydrogen-bonding interactions are not the dominant driving force for A_2AR association. The question remains whether depletion interactions could facilitate A_2AR oligomerization.

Figure 5 with 1 supplement see all

Download asset Open asset

Figure 5—source data 1

Raw size-exclusion chromatography data of various A_2AR variants under different ionic strengths of 0.15, 0.45, and 0.95 M.

https://cdn.elifesciences.org/articles/66662/elife-66662-fig5-data1-v2.xlsx

Download elife-66662-fig5-data1-v2.xlsx

At higher ionic strengths of 0.45 M and 0.95 M, the dimer and total oligomer levels of A_2AR-V334ΔC still remained near zero (Figure 5). In contrast, we observed a progressive and significant increase in the dimer and total oligomer levels of A_2AR-FL-WT with increasing ionic strength (Figure 5). This result indicates that A_2AR oligomerization is driven by depletion interactions enhanced with increasing ionic strength and that these interactions must involve the C-terminal segment after residue V334.

Upon closer examination, we recognize that at the very high ionic strength of 0.95 M the increase in the dimer and total oligomer levels was robust for A_2AR-FL-WT, but less pronounced for A_2AR-FL-ERR:AAA (Figure 5). Furthermore, this high ionic strength even had an opposite effect on A_2AR-N359ΔC, with both its dimer and total oligomer levels abolished (Figure 5). These results indicate that the charged cluster ³⁵⁵ERR³⁵⁷ and the C-terminal segment after residue N359 promote the depletion interactions to drive A_2AR oligomerization. Taken together, we can conclude that A_2AR oligomerization is more robust when the C-terminus is fully present and the ionic strength higher, suggesting that depletion interactions via the C-terminus are strong driving factors of A_2AR oligomerization.

The discussion of depletion interactions as driving factors assumes that A_2AR dimer/oligomer populations are thermodynamic products at equilibrium with the A_2AR monomer population. However, some of the A_2AR dimer/oligomer populations may be kinetically stabilized. To address this question, we tested the stability and reversibility of A_2AR oligomers by performing a second round of SEC on the monomer and dimer/oligomer populations of the A_2AR-WT and Q372ΔC variants. We found that the SEC-separated monomers repopulate into dimer/oligomer, with the total oligomer level after redistribution comparable with that of the initial samples for both A_2AR-WT (initial: 2.87; redistributed: 1.60) and Q372ΔC (initial: 1.49; redistributed: 1.40) (Figure 5—figure supplement 1A). This observation indicates that A_2AR oligomer is a thermodynamic product with a lower free energy compared with that of the monomer (Figure 5—figure supplement 1B). This agrees with the results we have shown in Supplementary file 1 that the oligomer levels of A_2AR-WT are consistent among replicates (1.34–2.05) and that A_2AR oligomerization can be modulated with ionic strengths via depletion interactions (Figure 5).

In contrast, the SEC-separated dimer/oligomer populations do not repopulate to form monomers (Figure 5—figure supplement 1A). This observation is consistent with a published study of ours on A_2AR dimers (Schonenbach et al., 2016), indicating that once the oligomers are formed, some are kinetically trapped and thus cannot redistribute into monomers. We believe that disulfide linkages are likely candidates to kinetically stabilize A_2AR oligomers, as demonstrated by their redistribution into monomers only in the presence of a reducing agent (Figure 2B).

Taken together, we suggest that A_2AR oligomerization is a thermodynamic process (Figure 5—figure supplement 1B), with the free energy of the dimer/oligomers lowered by depletion forces that hence increase their population relative to that of the monomers (there always exists a distribution between the two). Once formed, the redistributed dimer/oligomer populations may be kinetically stabilized by disulfide linkages. The question then arises whether inter-A_2AR interactions are primarily a result of the C-termini directly interacting with one another. This question motivated us to carry out a study focused on investigating the behavior of A_2AR C-terminus sans the transmembrane domains.

The isolated A_2AR C-terminus is prone to aggregation

To test whether A_2AR oligomerization is driven by direct depletion interactions among the C-termini of the protomers, we assayed the solubility and assembly properties of the stand-alone A_2AR C-terminus—an intrinsically disordered peptide—sans the upstream transmembrane regions. Since depletion interactions can be manifested via the hydrophobic effect (van der Vegt et al., 2017), we examined whether this effect can also drive the assembly of the A_2AR C-terminal peptides.

It is an active debate whether the hydrophobic effect can be promoted or suppressed by ions with salting-out or salting-in tendency, respectively (Thomas and Elcock, 2007; Graziano, 2010; Zangi et al., 2007; Grover and Ryall, 2005). We increased the solvent ionic strength using either sodium (salting-out) or guanidinium (salting-in) ions and assessed the aggregation propensity of the C-terminal peptides using UV-Vis absorption at 450 nm, which indicates the turbidity of the solution. We first observed the behavior of the C-terminus with increasing salting-out NaCl concentrations. At NaCl concentrations below 1 M, the peptide was dominantly soluble, despite showing slight aggregation at NaCl concentrations between 250 and 500 mM (Figure 6A). At NaCl concentrations above 1 M, A_2AR C-terminal peptides strongly associated into insoluble aggregates (Figure 6A). Consistent with the observations made with the intact receptor (Figure 5), the A_2AR C-terminus showed the tendency to progressively associate and eventually precipitate with increasing ionic strengths, suggesting that depletion interactions drive the association and precipitation of the peptides. We next observed the behavior of the C-terminus with increasing concentrations of guanidine hydrochloride (GdnHCl), which contains salting-in cations that do not induce precipitation and instead facilitate the solubilization of proteins (Heyda et al., 2017; Baldwin, 1996). Our results demonstrated that the A_2AR C-terminus incubated in 4 M GdnHCl showed no aggregation propensity (Figure 6A), validating our expectation that salting-in salts do not enhance depletion interactions. These observations demonstrate that the C-terminal peptide in and of itself, outside the context of the lipid membrane and TM domain, can directly interact with other C-terminal peptides to form self-aggregates in the presence of ions, and presumably solutes, that have salting-out effects.

Figure 6 with 1 supplement see all

Download asset Open asset

Figure 6—source data 1

Detailed data showing the propensity of A_2AR C-terminus to aggregate.

(A) Absorbance at 450 nm of the A_2AR C-terminus in solution, with NaCl and GdnHCl concentrations varied to achieve ionic strengths 0–4 M. (B) SYPRO orange fluorescence of solutions containing the A_2AR C-terminus as the temperature was varied from 20°C to 70°C (gray). The change in fluorescence, measured in relative fluorescence unit (RFU), was calculated by taking the first derivative of the fluorescence values.

https://cdn.elifesciences.org/articles/66662/elife-66662-fig6-data1-v2.xlsx

Download elife-66662-fig6-data1-v2.xlsx

Attractive hydrophobic interactions among the hydrophobic residues are further enhanced when the water that solvate the protein surface have more favorable interactions with other water molecules, ions, or solutes than with the protein surface, here the truncated C-terminus (Larsen et al., 1998; Tsai and Nussinov, 1997; Tsai et al., 1997). We explored the possible contribution of hydrophobic interactions to the aggregation of the C-terminal peptides using both experimental and computational approaches. Using differential scanning fluorimetry (DSF), we gradually increased the temperature to melt the C-terminal peptides, exposing any previously buried hydrophobic residues (Figure 6—figure supplement 1A, B), which then bound to the SYPRO orange fluorophore, resulting in an increase in fluorescence signal. Our results showed that as the temperature increased, a steady rise in fluorescence was observed (Figure 6B), indicating that multiple hydrophobic residues were gradually exposed to the SYPRO dye. However, at approximately 65°C, the melt peak signal was abruptly quenched (Figure 6B), indicating that the hydrophobic residues were no longer exposed to the dye. This observation suggests that, at 65°C, enough hydrophobic residues in the C-terminal peptides become exposed such that they collapse on one another (thus expelling the bound dye molecules), resulting in aggregation. This experimental result is further supported by our CGMD computational analysis of C-terminal non-polar contacts found in A_2AR symmetrical dimers (Figure 6—figure supplement 1C). Specifically, we observed an average of 60 non-polar contacts for A_2AR-C394ΔC. This number progressively declined upon further C-terminus truncation, reaching 15 for A_2AR-A316ΔC. Clearly, the hydrophobic effect can cause A_2AR C-terminal peptides to directly associate. These results demonstrate that A_2AR oligomer formation can be driven by depletion interactions among the C-termini of the protomers by non-polar contacts.

The key finding of this study is that the C-terminus of A_2AR, removed in all previously published structural studies, is directly responsible for receptor oligomerization. Using a combination of experimental and computational approaches, we demonstrate that the C-terminus stabilizes A_2AR oligomers via a combination of disulfide linkages, hydrogen bonds, electrostatic interactions, and hydrophobic interactions. This diverse combination of interactions is greatly enhanced by depletion interactions, forming a network of malleable bonds that drives A_2AR oligomerization and gives rise to multiple oligomeric interfaces.

Intermolecular disulfide linkages play a role in A_2AR oligomerization, potentially by kinetically trapping the receptor oligomers. Among the seven cysteines that do not form intramolecular disulfide bonds (De Filippo et al., 2016; Naranjo et al., 2015; O'Malley et al., 2010), residue C394 is largely involved in stabilizing A_2AR oligomers (Figure 2A). Indeed, this cysteine is highly conserved and a C-terminal cysteine is almost always present in A_2AR homologs (Pándy-Szekeres et al., 2018), suggesting that it may serve an important role in vivo. There may also exist inter-A_2AR disulfide linkages that do not involve residue C394 at all as the SEC-separated dimer/oligomer populations of A_2AR-Q372ΔC, which lack residue C394, were still resistant to TCEP reduction (Figure 2B) and appear to be kinetically trapped (Figure 5—figure supplement 1). Such disulfide linkages may involve other cysteines in the hydrophobic core of A_2AR, namely C28^1.54, C82^3.30, C128^4.49, C185^5.46, C245^6.47, or C254^6.56. Many examples exist where disulfide linkages help drive GPCR oligomerization, including the CaR-mGluR₁ heterodimer (Gama et al., 2001), homodimers of mGluR₅ (Romano et al., 1996), M₃R (Zeng and Wess, 1999), V₂R (Zhu and Wess, 1998), 5-HT₄R (Berthouze et al., 2007) and 5-HT_1DR (Lee et al., 2000), and even higher-order oligomers of D₂R (Guo et al., 2008). Although unconventional cytoplasmic disulfide bonds have been reported (Saaranen and Ruddock, 2013; Locker and Griffiths, 1999), no study has shown how such linkages would be formed in vivo as the cytoplasm lacks the conditions and machinery required for disulfide bond formation (Gaut and Hendershot, 1993; Hwang et al., 1992; Helenius et al., 1992; Creighton et al., 1980).

The electrostatic interactions that stabilize A_2AR oligomer formation come from multiple sites along the C-terminus. From a representative snapshot of a A_2AR-C394ΔC dimer from our MD simulations (Figure 7A), we could visualize not only the intermolecular interactions calculated from the CGMD simulations (Figure 4B), but also intramolecular salt bridges. In particular, the ³⁵⁵ERR³⁵⁷ cluster of charged residues lies distal from the dimeric interface but still forms several salt bridges (Figure 7A, inset). This observation is supported by our experimental results showing that substituting this charged cluster with alanines reduces the total A_2AR oligomer levels (Figure 3C). However, it is unclear how such salt bridges involving this ³⁵⁵ERR³⁵⁷ cluster are enhanced by depletion interactions (Figure 5) as electrostatic interactions are usually screened out at high ionic strengths. In our MD simulations, we also observed networks of salt bridges along the dimeric interface, for example, between K315 of one monomer and D382 and E384 of the other monomer (Figure 7A, inset). The innate flexibility of the C-terminus could facilitate the formation of such salt bridges, which then help stabilize A_2AR dimers.

Figure 7 with 1 supplement see all

Download asset Open asset

Figure 7—source data 1

MD simulations data used to visualize A_2AR dimeric interface and observe the conformational changes of the TM7.

(A) List of all C-terminal residue pairs of A_2AR-C394ΔC dimers engaging in electrostatic interactions. (B) Helical tilt angles for TM7 helix in A_2AR as a function of protein length.

https://cdn.elifesciences.org/articles/66662/elife-66662-fig7-data1-v2.xlsx

Download elife-66662-fig7-data1-v2.xlsx

Our finding that A_2AR forms homo-oligomers via multiple interfaces (Figure 4A) agrees with the increasing number of studies reporting multiple and interconverting oligomeric interfaces in A_2AR and other GPCRs (Song et al., 2020; Ghosh et al., 2014; Periole et al., 2012; Fanelli and Felline, 2011; Liu et al., 2012; Huang et al., 2013; Manglik et al., 2012; Thorsen et al., 2014; Fotiadis et al., 2006; Fotiadis et al., 2003; Liang et al., 2003; Xue et al., 2015; Dijkman et al., 2018). When translated to in vivo situations, GPCR oligomers can also transiently associate and dissociate (Kasai et al., 2018; Tabor et al., 2016; Möller et al., 2020; Vilardaga et al., 2008). Such conformational changes require that the oligomeric interfaces be formed by interactions that can easily be modulated. This is consistent with our study, which demonstrates that depletion interactions via the intrinsically disordered, malleable C-terminus drive A_2AR oligomerization. Because depletion interactions can be readily tuned by environmental factors, such as ionic strength, molecular crowding, and temperature, the formation of GPCR oligomeric complexes could be dynamically modulated in response to environmental cues to regulate receptor function.

Not only did we find multiple A_2AR oligomeric interfaces, we also found that these interfaces can be either symmetric or asymmetric. This finding is supported by a growing body of evidence that there exists both symmetric and asymmetric oligomeric interfaces for A_2AR (Song et al., 2020) and many other GPCRs. Studies using various biochemical and biophysical techniques have shown that heterotetrameric GPCR complexes can be formed by dimers of dimers, including μOR-δOR (Golebiewska et al., 2011), CXC₄R-CC₂R (Armando et al., 2014), CB₁R/D₂R (Bagher et al., 2017), as well as those involving A_2AR, such as A₁R-A_2AR (Navarro et al., 2018a; Navarro et al., 2016) and A_2AR-D₂R (Navarro et al., 2018b). The quaternary structures identified in these studies required specific orientations of each protomer, with the most viable model involving a stagger of homodimers with symmetric interfaces (DelaCuesta-Barrutia et al., 2020). On the other hand, since symmetric interfaces limit the degree of receptor association to dimers, the HMW oligomer of A_2AR observed in this (Song et al., 2020) and other studies (Schonenbach et al., 2016; Vidi et al., 2008) can only be formed via asymmetric interfaces. It is indeed tempting to suggest that the formation of the HMW oligomer of A_2AR may even arise from combinations of different interfaces. In any case, the wide variation of GPCR oligomerization requires the existence of both symmetric and asymmetric oligomeric interfaces.

The ultimate question to answer is how oligomerization alters A_2AR function. In the case of A_2AR, displacement of the transmembrane domains has been demonstrated to be the hallmark of receptor activation (Eddy et al., 2018; Sušac et al., 2018; Prosser et al., 2017; Ye et al., 2016), but no studies have linked receptor oligomerization with the arrangement of the TM bundles in A_2AR. Our MD simulations revealed that C-terminus truncation resulted in structural changes in the heptahelical bundles of A_2AR dimers. Specifically, as more of the C-terminus was preserved, we observed a progressive increase in the helical tilt of TM7 (Figure 7B). This change in helical tilt occurred for the entire heptahelical bundle, with an increase in tilt for TM1, TM2, TM3, TM5, and TM7, and a decrease in tilt for TM4 and TM6 (Figure 7—figure supplement 1). The longer C-terminus in the full-length A_2AR permits greater rearrangements in the transmembrane regions, leading to the observed change in helical tilt. Furthermore, in the cellular context, it has been demonstrated that truncation of the C-terminus significantly reduced receptor association with Gα_s and cAMP production in cellular assays (Koretz et al., 2021). These results hint at potential conformational changes of A_2AR upon oligomerization, necessitating future investigation on functional consequences.

Like all biophysical studies of membrane proteins in non-native environments, a drawback in our study is the question whether the above results, conducted in detergent micelles, can be translated to bilayer or cellular context. It has been demonstrated that the propensity of membrane proteins to associate and oligomerize is greater in lipid bilayers compared to that in detergent micelles (Popot and Engelman, 1990). Furthermore, in the cellular context, A_2AR has been shown to assemble into homo-oligomers in transfected HEK293 cells (Canals et al., 2003) and in Cath.A differentiated neuronal cells (Vidi et al., 2008), while C-terminally truncated A_2AR shows no protein aggregation or clustering on the cell surface, in contrast with its WT form (Burgueño et al., 2003). Therefore, we speculate that A_2AR oligomerization will be present in the lipid bilayer and cellular environment. Regardless, given that most biophysical structure-function studies of GPCRs are conducted in detergent micelles and other artificial membrane mimetics, it is critical to understand the role of the C-terminus in the oligomerization of A_2AR reconstituted in detergent micelles.

C-terminal truncations prior to crystallization and structural studies may be the main reason for the scarcity of GPCR structures featuring oligomers. In that context, this study offers valuable insights and approaches into how the oligomerization of A_2AR and potentially of other GPCRs can be tuned by modifying the intrinsically disordered C-terminus and varying salt types and concentrations. The presence of A_2AR oligomeric populations with partial C-terminal truncations means that one can now study its oligomerization with less perturbation from the C-terminus. We also present evidence that the multiple C-terminal interactions that drive A_2AR oligomerization can be easily modulated by ionic strength and specific salts (Figures 5 and 6). Given that ~75% and ~15% of all class A GPCRs possess a C-terminus of >50 and >100 amino acid residues (Mirzadegan et al., 2003), respectively, it will be worthwhile to explore the prospect of tuning GPCR oligomerization not only by shortening the C-terminus but also with simpler approaches such as modulating ionic strength and the surrounding salt environment.

All data generated or analysed during this study are included in the manuscript and supporting files.

1. 1. Abraham MJ
   2. Murtola T
   3. Schulz R
   4. Páll S
   5. Smith JC
   6. Hess B
   7. Lindahl E

   (2015) GROMACS: high performance molecular simulations through multi-level parallelism from laptops to supercomputers

   SoftwareX 1-2:19–25.

   https://doi.org/10.1016/j.softx.2015.06.001

   • Google Scholar
2. 1. Armando S
   2. Quoyer J
   3. Lukashova V
   4. Maiga A
   5. Percherancier Y
   6. Heveker N
   7. Pin JP
   8. Prézeau L
   9. Bouvier M

   (2014) The chemokine CXC4 and CC2 receptors form Homo- and heterooligomers that can engage their signaling G-protein effectors and βarrestin

   The FASEB Journal 28:4509–4523.

   https://doi.org/10.1096/fj.13-242446

   • PubMed
   • Google Scholar
3. 1. Asakura S
   2. Oosawa F

   (1958) Interaction between particles suspended in solutions of macromolecules

   Journal of Polymer Science 33:183–192.

   https://doi.org/10.1002/pol.1958.1203312618

   • Google Scholar
4. 1. Bagher AM
   2. Laprairie RB
   3. Toguri JT
   4. Kelly MEM
   5. Denovan-Wright EM

   (2017) Bidirectional allosteric interactions between cannabinoid receptor 1 (CB₁) and dopamine receptor 2 long (D_2L) heterotetramers

   European Journal of Pharmacology 813:66–83.

   https://doi.org/10.1016/j.ejphar.2017.07.034

   • PubMed
   • Google Scholar
5. 1. Baldwin RL

   (1996) How Hofmeister ion interactions affect protein stability

   Biophysical Journal 71:2056–2063.

   https://doi.org/10.1016/S0006-3495(96)79404-3

   • PubMed
   • Google Scholar
6. 1. Berthouze M
   2. Rivail L
   3. Lucas A
   4. Ayoub MA
   5. Russo O
   6. Sicsic S
   7. Fischmeister R
   8. Berque-Bestel I
   9. Jockers R
   10. Lezoualc'h F

   (2007) Two transmembrane cys residues are involved in 5-HT4 receptor dimerization

   Biochemical and Biophysical Research Communications 356:642–647.

   https://doi.org/10.1016/j.bbrc.2007.03.030

   • PubMed
   • Google Scholar
7. 1. Best RB
   2. Zhu X
   3. Shim J
   4. Lopes PE
   5. Mittal J
   6. Feig M
   7. Mackerell AD

   (2012) Optimization of the additive CHARMM all-atom protein force field targeting improved sampling of the backbone φ, ψ and side-chain χ(1) and χ(2) dihedral angles

   Journal of Chemical Theory and Computation 8:3257–3273.

   https://doi.org/10.1021/ct300400x

   • PubMed
   • Google Scholar
8. 1. Borroto-Escuela DO
   2. Narvaez M
   3. Marcellino D
   4. Parrado C
   5. Narvaez JA
   6. Tarakanov AO
   7. Agnati LF
   8. Díaz-Cabiale Z
   9. Fuxe K

   (2010) Galanin receptor-1 modulates 5-hydroxtryptamine-1A signaling via heterodimerization

   Biochemical and Biophysical Research Communications 393:767–772.

   https://doi.org/10.1016/j.bbrc.2010.02.078

   • PubMed
   • Google Scholar
9. 1. Bräuner-Osborne H
   2. Wellendorph P
   3. Jensen AA

   (2007) Structure, pharmacology and therapeutic prospects of family C G-protein coupled receptors

   Current Drug Targets 8:169–184.

   https://doi.org/10.2174/138945007779315614

   • PubMed
   • Google Scholar
10. 1. Bryksin AV
    2. Matsumura I

    (2010) Overlap extension PCR cloning: a simple and reliable way to create recombinant plasmids

    BioTechniques 48:463–465.

    https://doi.org/10.2144/000113418

    • PubMed
    • Google Scholar
11. 1. Burgueño J
    2. Blake DJ
    3. Benson MA
    4. Tinsley CL
    5. Esapa CT
    6. Canela EI
    7. Penela P
    8. Mallol J
    9. Mayor F
    10. Lluis C
    11. Franco R
    12. Ciruela F

    (2003) The adenosine A2A receptor interacts with the actin-binding protein alpha-actinin

    Journal of Biological Chemistry 278:37545–37552.

    https://doi.org/10.1074/jbc.M302809200

    • PubMed
    • Google Scholar
12. 1. Bussi G
    2. Donadio D
    3. Parrinello M

    (2007) Canonical sampling through velocity rescaling

    The Journal of Chemical Physics 126:014101.

    https://doi.org/10.1063/1.2408420

    • PubMed
    • Google Scholar
13. 1. Canals M
    2. Burgueño J
    3. Marcellino D
    4. Cabello N
    5. Canela EI
    6. Mallol J
    7. Agnati L
    8. Ferré S
    9. Bouvier M
    10. Fuxe K
    11. Ciruela F
    12. Lluis C
    13. Franco R

    (2003) Homodimerization of adenosine A2A receptors: qualitative and quantitative assessment by fluorescence and bioluminescence energy transfer

    Journal of Neurochemistry 88:726–734.

    https://doi.org/10.1046/j.1471-4159.2003.02200.x

    • Google Scholar
14. 1. Carpenter B
    2. Nehmé R
    3. Warne T
    4. Leslie AG
    5. Tate CG

    (2016) Structure of the adenosine A(2A) receptor bound to an engineered G protein

    Nature 536:104–107.

    https://doi.org/10.1038/nature18966

    • PubMed
    • Google Scholar
15. 1. Casadó-Anguera V
    2. Bonaventura J
    3. Moreno E
    4. Navarro G
    5. Cortés A
    6. Ferré S
    7. Casadó V

    (2016) Evidence for the heterotetrameric structure of the Adenosine A2A-dopamine D2 receptor complex

    Biochemical Society Transactions 44:595–600.

    https://doi.org/10.1042/BST20150276

    • PubMed
    • Google Scholar
16. 1. Cino EA
    2. Karttunen M
    3. Choy WY

    (2012) Effects of molecular crowding on the dynamics of intrinsically disordered proteins

    PLOS ONE 7:e49876.

    https://doi.org/10.1371/journal.pone.0049876

    • PubMed
    • Google Scholar
17. 1. Ciruela F
    2. Burgueño J
    3. Casadó V
    4. Canals M
    5. Marcellino D
    6. Goldberg SR
    7. Bader M
    8. Fuxe K
    9. Agnati LF
    10. Lluis C
    11. Franco R
    12. Ferré S
    13. Woods AS

    (2004) Combining mass spectrometry and pull-down techniques for the study of receptor heteromerization. Direct epitope-epitope electrostatic interactions between adenosine A2A and dopamine D2 receptors

    Analytical Chemistry 76:5354–5363.

    https://doi.org/10.1021/ac049295f

    • PubMed
    • Google Scholar
18. 1. Clements JM
    2. Catlin GH
    3. Price MJ
    4. Edwards RM

    (1991) Secretion of human epidermal growth factor from Saccharomyces cerevisiae using synthetic leader sequences

    Gene 106:267–271.

    https://doi.org/10.1016/0378-1119(91)90209-T

    • PubMed
    • Google Scholar
19. 1. Cordomí A
    2. Navarro G
    3. Aymerich MS
    4. Franco R

    (2015) Structures for G-Protein-Coupled receptor tetramers in complex with G proteins

    Trends in Biochemical Sciences 40:548–551.

    https://doi.org/10.1016/j.tibs.2015.07.007

    • PubMed
    • Google Scholar
20. 1. Creighton TE
    2. Hillson DA
    3. Freedman RB

    (1980) Catalysis by protein-disulphide isomerase of the unfolding and refolding of proteins with disulphide bonds

    Journal of Molecular Biology 142:43–62.

    https://doi.org/10.1016/0022-2836(80)90205-3

    • PubMed
    • Google Scholar
21. 1. Cristóvão-Ferreira S
    2. Navarro G
    3. Brugarolas M
    4. Pérez-Capote K
    5. Vaz SH
    6. Fattorini G
    7. Conti F
    8. Lluis C
    9. Ribeiro JA
    10. McCormick PJ
    11. Casadó V
    12. Franco R
    13. Sebastião AM

    (2013) A1R-A2AR heteromers coupled to gs and G i/0 proteins modulate GABA transport into astrocytes

    Purinergic Signalling 9:433–449.

    https://doi.org/10.1007/s11302-013-9364-5

    • PubMed
    • Google Scholar
22. 1. Daura X
    2. Gademann K
    3. Jaun B
    4. Seebach D
    5. van Gunsteren WF
    6. Mark AE

    (1999) Peptide folding: when simulation meets experiment

    Angewandte Chemie International Edition 38:236–240.

    https://doi.org/10.1002/(SICI)1521-3773(19990115)38:1/2<236::AID-ANIE236>3.0.CO;2-M

    • Google Scholar
23. 1. De Filippo E
    2. Namasivayam V
    3. Zappe L
    4. El-Tayeb A
    5. Schiedel AC
    6. Müller CE

    (2016) Role of extracellular cysteine residues in the adenosine A2A receptor

    Purinergic Signalling 12:313–329.

    https://doi.org/10.1007/s11302-016-9506-7

    • PubMed
    • Google Scholar
24. 1. de Jong DH
    2. Singh G
    3. Bennett WF
    4. Arnarez C
    5. Wassenaar TA
    6. Schäfer LV
    7. Periole X
    8. Tieleman DP
    9. Marrink SJ

    (2013) “Improved Parameters for the Martini Coarse-Grained Protein Force Field.”

    Journal of Chemical Theory and Computation 9:687–697.

    https://doi.org/10.1021/ct300646g

    • PubMed
    • Google Scholar
25. 1. DelaCuesta-Barrutia J
    2. Peñagarikano O
    3. Erdozain AM

    (2020) G Protein-Coupled receptor heteromers as putative pharmacotherapeutic targets in autism

    Frontiers in Cellular Neuroscience 14:588662.

    https://doi.org/10.3389/fncel.2020.588662

    • PubMed
    • Google Scholar
26. 1. Dijkman PM
    2. Castell OK
    3. Goddard AD
    4. Munoz-Garcia JC
    5. de Graaf C
    6. Wallace MI
    7. Watts A

    (2018) Dynamic tuneable G protein-coupled receptor monomer-dimer populations

    Nature Communications 9:03727-6.

    https://doi.org/10.1038/s41467-018-03727-6

    • Google Scholar
27. 1. Doré AS
    2. Robertson N
    3. Errey JC
    4. Ng I
    5. Hollenstein K
    6. Tehan B
    7. Hurrell E
    8. Bennett K
    9. Congreve M
    10. Magnani F
    11. Tate CG
    12. Weir M
    13. Marshall FH

    (2011) Structure of the adenosine A(2A) receptor in complex with ZM241385 and the xanthines XAC and caffeine

    Structure 19:1283–1293.

    https://doi.org/10.1016/j.str.2011.06.014

    • PubMed
    • Google Scholar
28. 1. Dorsam RT
    2. Gutkind JS

    (2007) G-protein-coupled receptors and cancer

    Nature Reviews Cancer 7:79–94.

    https://doi.org/10.1038/nrc2069

    • PubMed
    • Google Scholar
29. 1. Ecke D
    2. Hanck T
    3. Tulapurkar ME
    4. Schäfer R
    5. Kassack M
    6. Stricker R
    7. Reiser G

    (2008) Hetero-oligomerization of the P2Y11 receptor with the P2Y1 receptor controls the internalization and ligand selectivity of the P2Y11 receptor

    Biochemical Journal 409:107–116.

    https://doi.org/10.1042/BJ20070671

    • PubMed
    • Google Scholar
30. 1. Eddy MT
    2. Lee M-Y
    3. Gao Z-G
    4. White KL
    5. Didenko T
    6. Horst R
    7. Audet M
    8. Stanczak P
    9. McClary KM
    10. Han GW
    11. Jacobson KA
    12. Stevens RC
    13. Wüthrich K

    (2018) Allosteric coupling of drug binding and intracellular signaling in the A2A adenosine receptor

    Cell 172:68–80.

    https://doi.org/10.1016/j.cell.2017.12.004

    • Google Scholar
31. 1. El-Asmar L
    2. Springael JY
    3. Ballet S
    4. Andrieu EU
    5. Vassart G
    6. Parmentier M

    (2005) Evidence for negative binding cooperativity within CCR5-CCR2b heterodimers

    Molecular Pharmacology 67:460–469.

    https://doi.org/10.1124/mol.104.003624

    • PubMed
    • Google Scholar
32. 1. Eswar N
    2. Webb B
    3. Marti‐Renom MA
    4. Madhusudhan MS
    5. Eramian D
    6. Shen M‐Y
    7. Pieper U
    8. Sali A

    (2006) Comparative protein structure modeling using modeller

    Current Protocols in Bioinformatics 15:5.6.1–5.6.5.

    https://doi.org/10.1002/0471250953.bi0506s15

    • Google Scholar
33. 1. Faklaris O
    2. Cottet M
    3. Falco A
    4. Villier B
    5. Laget M
    6. Zwier JM
    7. Trinquet E
    8. Mouillac B
    9. Pin JP
    10. Durroux T

    (2015) Multicolor time-resolved förster resonance energy transfer microscopy reveals the impact of GPCR oligomerization on internalization processes

    The FASEB Journal 29:2235–2246.

    https://doi.org/10.1096/fj.14-260059

    • PubMed
    • Google Scholar
34. 1. Fanelli F
    2. Felline A

    (2011) Dimerization and ligand binding affect the structure network of A2A adenosine receptor

    Biochimica Et Biophysica Acta (BBA) - Biomembranes 1808:1256–1266.

    https://doi.org/10.1016/j.bbamem.2010.08.006

    • Google Scholar
35. 1. Farran B

    (2017) An update on the physiological and therapeutic relevance of GPCR oligomers

    Pharmacological Research 117:303–327.

    https://doi.org/10.1016/j.phrs.2017.01.008

    • PubMed
    • Google Scholar
36. 1. Ferré S
    2. Casadó V
    3. Devi LA
    4. Filizola M
    5. Jockers R
    6. Lohse MJ
    7. Milligan G
    8. Pin JP
    9. Guitart X

    (2014) G protein-coupled receptor oligomerization revisited: functional and pharmacological perspectives

    Pharmacological Reviews 66:413–434.

    https://doi.org/10.1124/pr.113.008052

    • PubMed
    • Google Scholar
37. 1. Fotiadis D
    2. Liang Y
    3. Filipek S
    4. Saperstein DA
    5. Engel A
    6. Palczewski K

    (2003) Atomic-force microscopy: rhodopsin dimers in native disc membranes

    Nature 421:127–128.

    https://doi.org/10.1038/421127a

    • PubMed
    • Google Scholar
38. 1. Fotiadis D
    2. Jastrzebska B
    3. Philippsen A
    4. Müller DJ
    5. Palczewski K
    6. Engel A

    (2006) Structure of the rhodopsin dimer: a working model for G-protein-coupled receptors

    Current Opinion in Structural Biology 16:252–259.

    https://doi.org/10.1016/j.sbi.2006.03.013

    • PubMed
    • Google Scholar
39. 1. Gama L
    2. Wilt SG
    3. Breitwieser GE

    (2001) Heterodimerization of calcium sensing receptors with metabotropic glutamate receptors in neurons

    Journal of Biological Chemistry 276:39053–39059.

    https://doi.org/10.1074/jbc.M105662200

    • Google Scholar
40. 1. García-Nafría J
    2. Lee Y
    3. Bai X
    4. Carpenter B
    5. Tate CG

    (2018) Cryo-EM structure of the adenosine A_2Areceptor coupled to an engineered heterotrimeric G protein

    eLife 7:e35946.

    https://doi.org/10.7554/eLife.35946

    • PubMed
    • Google Scholar
41. 1. Gaut JR
    2. Hendershot LM

    (1993) The modification and assembly of proteins in the endoplasmic reticulum

    Current Opinion in Cell Biology 5:589–595.

    https://doi.org/10.1016/0955-0674(93)90127-C

    • PubMed
    • Google Scholar
42. 1. George SR
    2. O'Dowd BF
    3. Lee SP

    (2002) G-protein-coupled receptor oligomerization and its potential for drug discovery

    Nature Reviews Drug Discovery 1:808–820.

    https://doi.org/10.1038/nrd913

    • PubMed
    • Google Scholar
43. 1. Ghosh A
    2. Sonavane U
    3. Joshi R

    (2014) Multiscale modelling to understand the self-assembly mechanism of human β2-adrenergic receptor in lipid bilayer

    Computational Biology and Chemistry 48:29–39.

    https://doi.org/10.1016/j.compbiolchem.2013.11.002

    • PubMed
    • Google Scholar
44. Book

    1. Gietz RD

    (2014) “Yeast Transformation by the LiAc/SS Carrier DNA/PEG Method

    In: Xiao W, editors. Yeast ProtocolsMethods in Molecular Biology. New York: Springer. pp. 33–44.

    https://doi.org/10.1385/0896033198

    • Google Scholar
45. 1. Goldenberg DP
    2. Argyle B

    (2014) Minimal effects of macromolecular crowding on an intrinsically disordered protein: a small-angle neutron scattering study

    Biophysical Journal 106:905–914.

    https://doi.org/10.1016/j.bpj.2013.12.003

    • PubMed
    • Google Scholar
46. 1. Golebiewska U
    2. Johnston JM
    3. Devi L
    4. Filizola M
    5. Scarlata S

    (2011) Differential response to morphine of the oligomeric state of μ-opioid in the presence of δ-opioid receptors

    Biochemistry 50:2829–2837.

    https://doi.org/10.1021/bi101701x

    • PubMed
    • Google Scholar
47. 1. González-Maeso J
    2. Weisstaub NV
    3. Zhou M
    4. Chan P
    5. Ivic L
    6. Ang R
    7. Lira A
    8. Bradley-Moore M
    9. Ge Y
    10. Zhou Q
    11. Sealfon SC
    12. Gingrich JA

    (2007) Hallucinogens recruit specific cortical 5-HT(2A) receptor-mediated signaling pathways to affect behavior

    Neuron 53:439–452.

    https://doi.org/10.1016/j.neuron.2007.01.008

    • PubMed
    • Google Scholar
48. 1. Graziano G

    (2010) Hydrophobic interaction of two large plates: an analysis of salting-in/salting-out effects

    Chemical Physics Letters 491:54–58.

    https://doi.org/10.1016/j.cplett.2010.03.092

    • Google Scholar
49. 1. Grover PK
    2. Ryall RL

    (2005) Critical appraisal of salting-out and its implications for chemical and biological sciences

    Chemical Reviews 105:1–10.

    https://doi.org/10.1021/cr030454p

    • PubMed
    • Google Scholar
50. 1. Guitart X
    2. Navarro G
    3. Moreno E
    4. Yano H
    5. Cai NS
    6. Sánchez-Soto M
    7. Kumar-Barodia S
    8. Naidu YT
    9. Mallol J
    10. Cortés A
    11. Lluís C
    12. Canela EI
    13. Casadó V
    14. McCormick PJ
    15. Ferré S

    (2014) Functional selectivity of allosteric interactions within G protein-coupled receptor oligomers: the dopamine D1-D3 receptor heterotetramer

    Molecular Pharmacology 86:417–429.

    https://doi.org/10.1124/mol.114.093096

    • PubMed
    • Google Scholar
51. 1. Guo W
    2. Urizar E
    3. Kralikova M
    4. Mobarec JC
    5. Shi L
    6. Filizola M
    7. Javitch JA

    (2008) Dopamine D2 receptors form higher order oligomers at physiological expression levels

    The EMBO Journal 27:2293–2304.

    https://doi.org/10.1038/emboj.2008.153

    • PubMed
    • Google Scholar
52. 1. Helenius A
    2. Marquardt T
    3. Braakman I

    (1992) The endoplasmic reticulum as a protein-folding compartment

    Trends in Cell Biology 2:227–231.

    https://doi.org/10.1016/0962-8924(92)90309-B

    • PubMed
    • Google Scholar
53. 1. Hess B
    2. Bekker H
    3. Berendsen HJC
    4. Fraaije JGEM

    (1997) LINCS: a linear constraint solver for molecular simulations

    Journal of Computational Chemistry 18:1463–1472.

    https://doi.org/10.1002/(SICI)1096-987X(199709)18:12<1463::AID-JCC4>3.0.CO;2-H

    • Google Scholar
54. 1. Heyda J
    2. Okur HI
    3. Hladílková J
    4. Rembert KB
    5. Hunn W
    6. Yang T
    7. Dzubiella J
    8. Jungwirth P
    9. Cremer PS

    (2017) Guanidinium can both cause and prevent the hydrophobic collapse of biomacromolecules

    Journal of the American Chemical Society 139:863–870.

    https://doi.org/10.1021/jacs.6b11082

    • PubMed
    • Google Scholar
55. 1. Hilairet S
    2. Bouaboula M
    3. Carrière D
    4. Fur GL
    5. Casellas P

    (2003) Hypersensitization of the orexin 1 receptor by the CB1 receptor: evidence for cross-talk blocked by the specific CB1 antagonist, SR141716

    Journal of Biological Chemistry 278:23731–23737.

    https://doi.org/10.1074/jbc.M212369200

    • Google Scholar
56. 1. Hino T
    2. Arakawa T
    3. Iwanari H
    4. Yurugi-Kobayashi T
    5. Ikeda-Suno C
    6. Nakada-Nakura Y
    7. Kusano-Arai O
    8. Weyand S
    9. Shimamura T
    10. Nomura N
    11. Cameron AD
    12. Kobayashi T
    13. Hamakubo T
    14. Iwata S
    15. Murata T

    (2012) G-protein-coupled receptor inactivation by an allosteric inverse-agonist antibody

    Nature 482:237–240.

    https://doi.org/10.1038/nature10750

    • PubMed
    • Google Scholar
57. 1. Hofmeister F

    (1888) Zur Lehre yon der wirkung der salze

    Archiv Für Experimentelle Pathologie Und Pharmakologie 24:247–260.

    https://doi.org/10.1007/BF01918191

    • Google Scholar
58. 1. Huang J
    2. Chen S
    3. Zhang JJ
    4. Huang XY

    (2013) Crystal structure of oligomeric β1-adrenergic G protein-coupled receptors in ligand-free basal state

    Nature Structural & Molecular Biology 20:419–425.

    https://doi.org/10.1038/nsmb.2504

    • PubMed
    • Google Scholar
59. 1. Humphrey W
    2. Dalke A
    3. Schulten K

    (1996) VMD: visual molecular dynamics

    Journal of Molecular Graphics 14:33–38.

    https://doi.org/10.1016/0263-7855(96)00018-5

    • PubMed
    • Google Scholar
60. 1. Hwang C
    2. Sinskey AJ
    3. Lodish HF

    (1992) Oxidized redox state of glutathione in the endoplasmic reticulum

    Science 257:1496–1502.

    https://doi.org/10.1126/science.1523409

    • PubMed
    • Google Scholar
61. 1. Hyde AM
    2. Zultanski SL
    3. Waldman JH
    4. Zhong Y-L
    5. Shevlin M
    6. Peng F

    (2017) General principles and strategies for Salting-Out informed by the Hofmeister series

    Organic Process Research & Development 21:1355–1370.

    https://doi.org/10.1021/acs.oprd.7b00197

    • Google Scholar
62. 1. Jaakola V-P
    2. Prilusky J
    3. Sussman JL
    4. Goldman A

    (2005) G protein-coupled receptors show unusual patterns of intrinsic unfolding

    Protein Engineering, Design and Selection 18:103–110.

    https://doi.org/10.1093/protein/gzi004

    • Google Scholar
63. 1. Jaakola VP
    2. Griffith MT
    3. Hanson MA
    4. Cherezov V
    5. Chien EY
    6. Lane JR
    7. Ijzerman AP
    8. Stevens RC

    (2008) The 2.6 angstrom crystal structure of a human A2A adenosine receptor bound to an antagonist

    Science 322:1211–1217.

    https://doi.org/10.1126/science.1164772

    • PubMed
    • Google Scholar
64. 1. Jain A
    2. McGraw C

    (2020) The Adenosine A1 and A2A receptor C-Termini are necessary for activation but not the specificity of downstream signaling

    Authorea 24:55605148.

    https://doi.org/10.22541/au.158532015.55605148

    • Google Scholar
65. 1. Jorgensen WL
    2. Chandrasekhar J
    3. Madura JD
    4. Impey RW
    5. Klein ML

    (1983) Comparison of simple potential functions for simulating liquid water

    The Journal of Chemical Physics 79:926–935.

    https://doi.org/10.1063/1.445869

    • Google Scholar
66. 1. Kasai RS
    2. Ito SV
    3. Awane RM
    4. Fujiwara TK
    5. Kusumi A

    (2018) The Class-A GPCR dopamine D2 receptor forms transient dimers stabilized by agonists: detection by Single-Molecule tracking

    Cell Biochemistry and Biophysics 76:29–37.

    https://doi.org/10.1007/s12013-017-0829-y

    • PubMed
    • Google Scholar
67. 1. Koretz KS
    2. McGraw CE
    3. Stradley S
    4. Elbaradei A
    5. Malmstadt N
    6. Robinson AS

    (2021) Characterization of binding kinetic_s of A_2AR to Gα_sprotein by surface plasmon resonance

    Biophysical Journal 120:1641–1649.

    https://doi.org/10.1016/j.bpj.2021.02.032

    • PubMed
    • Google Scholar
68. 1. Kyte J
    2. Doolittle RF

    (1982) A simple method for displaying the hydropathic character of a protein

    Journal of Molecular Biology 157:105–132.

    https://doi.org/10.1016/0022-2836(82)90515-0

    • PubMed
    • Google Scholar
69. 1. Larsen TA
    2. Olson AJ
    3. Goodsell DS

    (1998) Morphology of protein-protein interfaces

    Structure 6:421–427.

    https://doi.org/10.1016/S0969-2126(98)00044-6

    • PubMed
    • Google Scholar
70. 1. Lebon G
    2. Warne T
    3. Edwards PC
    4. Bennett K
    5. Langmead CJ
    6. Leslie AG
    7. Tate CG

    (2011) Agonist-bound adenosine A2A receptor structures reveal common features of GPCR activation

    Nature 474:521–525.

    https://doi.org/10.1038/nature10136

    • PubMed
    • Google Scholar
71. 1. Lee SP
    2. Xie Z
    3. Varghese G
    4. Nguyen T
    5. O'Dowd BF
    6. George SR

    (2000) Oligomerization of dopamine and serotonin receptors

    Neuropsychopharmacology 23:S32–S40.

    https://doi.org/10.1016/S0893-133X(00)00155-X

    • PubMed
    • Google Scholar
72. 1. Lee SP
    2. So CH
    3. Rashid AJ
    4. Varghese G
    5. Cheng R
    6. Lança AJ
    7. O'Dowd BF
    8. George SR

    (2004) Dopamine D1 and D2 receptor Co-activation generates a novel phospholipase C-mediated calcium signal

    Journal of Biological Chemistry 279:35671–35678.

    https://doi.org/10.1074/jbc.M401923200

    • Google Scholar
73. 1. Liang Y
    2. Fotiadis D
    3. Filipek S
    4. Saperstein DA
    5. Palczewski K
    6. Engel A

    (2003) Organization of the G Protein-coupled receptors rhodopsin and opsin in native membranes

    Journal of Biological Chemistry 278:21655–21662.

    https://doi.org/10.1074/jbc.M302536200

    • Google Scholar
74. 1. Liu W
    2. Chun E
    3. Thompson AA
    4. Chubukov P
    5. Xu F
    6. Katritch V
    7. Han GW
    8. Roth CB
    9. Heitman LH
    10. IJzerman AP
    11. Cherezov V
    12. Stevens RC

    (2012) Structural basis for allosteric regulation of GPCRs by sodium ions

    Science 337:232–236.

    https://doi.org/10.1126/science.1219218

    • PubMed
    • Google Scholar
75. 1. Liu H
    2. Tian Y
    3. Ji B
    4. Lu H
    5. Xin Q
    6. Jiang Y
    7. Ding L
    8. Zhang J
    9. Chen J
    10. Bai B

    (2016) Heterodimerization of the kappa opioid receptor and neurotensin receptor 1 contributes to a novel β-arrestin-2–biased pathway

    Biochimica Et Biophysica Acta (BBA) - Molecular Cell Research 1863:2719–2738.

    https://doi.org/10.1016/j.bbamcr.2016.07.009

    • Google Scholar
76. 1. Locker JK
    2. Griffiths G

    (1999) An unconventional role for cytoplasmic disulfide bonds in vaccinia virus proteins

    Journal of Cell Biology 144:267–279.

    https://doi.org/10.1083/jcb.144.2.267

    • Google Scholar
77. 1. Manglik A
    2. Kruse AC
    3. Kobilka TS
    4. Thian FS
    5. Mathiesen JM
    6. Sunahara RK
    7. Pardo L
    8. Weis WI
    9. Kobilka BK
    10. Granier S

    (2012) Crystal structure of the µ-opioid receptor bound to a morphinan antagonist

    Nature 485:321–326.

    https://doi.org/10.1038/nature10954

    • PubMed
    • Google Scholar
78. 1. Marenduzzo D
    2. Finan K
    3. Cook PR

    (2006) The depletion attraction: an underappreciated force driving cellular organization

    Journal of Cell Biology 175:681–686.

    https://doi.org/10.1083/jcb.200609066

    • PubMed
    • Google Scholar
79. 1. Martonák R
    2. Laio A
    3. Parrinello M

    (2003) Predicting crystal structures: the Parrinello-Rahman method revisited

    Physical Review Letters 90:075503.

    https://doi.org/10.1103/PhysRevLett.90.075503

    • PubMed
    • Google Scholar
80. Preprint

    1. Martynowycz MW
    2. Shiriaeva A
    3. Ge X
    4. Hattne J
    5. Nannenga BL
    6. Cherezov V
    7. Gonen T

    (2020) MicroED structure of the human adenosine receptor determined from a single nanocrystal in LCP

    bioRxiv.

    https://doi.org/10.1101/2020.09.27.316109

    • Google Scholar
81. 1. Milles S
    2. Salvi N
    3. Blackledge M
    4. Jensen MR

    (2018) Characterization of intrinsically disordered proteins and their dynamic complexes: from in vitro to cell-like environments

    Progress in Nuclear Magnetic Resonance Spectroscopy 109:79–100.

    https://doi.org/10.1016/j.pnmrs.2018.07.001

    • PubMed
    • Google Scholar
82. 1. Mirzadegan T
    2. Benkö G
    3. Filipek S
    4. Palczewski K

    (2003) Sequence analyses of G-protein-coupled receptors: similarities to rhodopsin

    Biochemistry 42:2759–2767.

    https://doi.org/10.1021/bi027224+

    • PubMed
    • Google Scholar
83. 1. Möller J
    2. Isbilir A
    3. Sungkaworn T
    4. Osberg B
    5. Karathanasis C
    6. Sunkara V
    7. Grushevskyi EO
    8. Bock A
    9. Annibale P
    10. Heilemann M
    11. Schütte C
    12. Lohse MJ

    (2020) Single-molecule analysis reveals agonist-specific dimer formation of µ-opioid receptors

    Nature Chemical Biology 16:946–954.

    https://doi.org/10.1038/s41589-020-0566-1

    • PubMed
    • Google Scholar
84. 1. Monticelli L
    2. Kandasamy SK
    3. Periole X
    4. Larson RG
    5. Tieleman DP
    6. Marrink SJ

    (2008) The MARTINI Coarse-Grained force field: extension to proteins

    Journal of Chemical Theory and Computation 4:819–834.

    https://doi.org/10.1021/ct700324x

    • PubMed
    • Google Scholar
85. 1. Naranjo AN
    2. Chevalier A
    3. Cousins GD
    4. Ayettey E
    5. McCusker EC
    6. Wenk C
    7. Robinson AS

    (2015) Conserved disulfide bond is not essential for the adenosine A2A receptor: extracellular cysteines influence receptor distribution within the cell and ligand-binding recognition

    Biochimica Et Biophysica Acta (BBA) - Biomembranes 1848:603–614.

    https://doi.org/10.1016/j.bbamem.2014.11.010

    • Google Scholar
86. 1. Navarro G
    2. Cordomí A
    3. Zelman-Femiak M
    4. Brugarolas M
    5. Moreno E
    6. Aguinaga D
    7. Perez-Benito L
    8. Cortés A
    9. Casadó V
    10. Mallol J
    11. Canela EI
    12. Lluís C
    13. Pardo L
    14. García-Sáez AJ
    15. McCormick PJ
    16. Franco R

    (2016) Quaternary structure of a G-protein-coupled receptor heterotetramer in complex with gi and gs

    BMC Biology 14:0247-4.

    https://doi.org/10.1186/s12915-016-0247-4

    • Google Scholar
87. 1. Navarro G
    2. Cordomí A
    3. Brugarolas M
    4. Moreno E
    5. Aguinaga D
    6. Pérez-Benito L
    7. Ferre S
    8. Cortés A
    9. Casadó V
    10. Mallol J
    11. Canela EI
    12. Lluís C
    13. Pardo L
    14. McCormick PJ
    15. Franco R

    (2018a) Cross-communication between G_i and G_s in a G-protein-coupled receptor heterotetramer guided by a receptor C-terminal domain

    BMC Biology 16:0491-x.

    https://doi.org/10.1186/s12915-018-0491-x

    • Google Scholar
88. 1. Navarro G
    2. Cordomí A
    3. Casadó-Anguera V
    4. Moreno E
    5. Cai N-S
    6. Cortés A
    7. Canela EI
    8. Dessauer CW
    9. Casadó V
    10. Pardo L
    11. Lluís C
    12. Ferré S

    (2018b) Evidence for functional pre-coupled complexes of receptor heteromers and adenylyl cyclase

    Nature Communications 9:03522-3.

    https://doi.org/10.1038/s41467-018-03522-3

    • Google Scholar
89. 1. Niebauer RT
    2. Robinson AS

    (2006) Exceptional total and functional yields of the human adenosine (A2a) receptor expressed in the yeast Saccharomyces cerevisiae

    Protein Expression and Purification 46:204–211.

    https://doi.org/10.1016/j.pep.2005.09.020

    • PubMed
    • Google Scholar
90. 1. Nørholm MH

    (2010) A mutant pfu DNA polymerase designed for advanced uracil-excision DNA engineering

    BMC Biotechnology 10:21.

    https://doi.org/10.1186/1472-6750-10-21

    • PubMed
    • Google Scholar
91. 1. Nour-Eldin HH
    2. Hansen BG
    3. Nørholm MH
    4. Jensen JK
    5. Halkier BA

    (2006) Advancing uracil-excision based cloning towards an ideal technique for cloning PCR fragments

    Nucleic Acids Research 34:e122.

    https://doi.org/10.1093/nar/gkl635

    • PubMed
    • Google Scholar
92. 1. O'Malley MA
    2. Lazarova T
    3. Britton ZT
    4. Robinson AS

    (2007) High-level expression in Saccharomyces cerevisiae enables isolation and spectroscopic characterization of functional human adenosine A2a receptor

    Journal of Structural Biology 159:166–178.

    https://doi.org/10.1016/j.jsb.2007.05.001

    • PubMed
    • Google Scholar
93. 1. O'Malley MA
    2. Mancini JD
    3. Young CL
    4. McCusker EC
    5. Raden D
    6. Robinson AS

    (2009) Progress toward heterologous expression of active G-protein-coupled receptors in Saccharomyces cerevisiae: linking cellular stress response with translocation and trafficking

    Protein Science 18:2356–2370.

    https://doi.org/10.1002/pro.246

    • PubMed
    • Google Scholar
94. 1. O'Malley MA
    2. Naranjo AN
    3. Lazarova T
    4. Robinson AS

    (2010) Analysis of Adenosine A₂a receptor stability: effects of ligands and disulfide bonds

    Biochemistry 49:9181–9189.

    https://doi.org/10.1021/bi101155r

    • PubMed
    • Google Scholar
95. 1. Pándy-Szekeres G
    2. Munk C
    3. Tsonkov TM
    4. Mordalski S
    5. Harpsøe K
    6. Hauser AS
    7. Bojarski AJ
    8. Gloriam DE

    (2018) GPCRdb in 2018: adding GPCR structure models and ligands

    Nucleic Acids Research 46:D440–D446.

    https://doi.org/10.1093/nar/gkx1109

    • PubMed
    • Google Scholar
96. 1. Parekh R
    2. Forrester K
    3. Wittrup D

    (1995) Multicopy overexpression of bovine pancreatic trypsin inhibitor saturates the protein folding and secretory capacity of Saccharomyces cerevisiae

    Protein Expression and Purification 6:537–545.

    https://doi.org/10.1006/prep.1995.1071

    • PubMed
    • Google Scholar
97. 1. Parekh RN
    2. Shaw MR
    3. Wittrup KD

    (1996) An integrating vector for tunable, high copy, stable integration into the dispersed ty Delta sites of Saccharomyces cerevisiae

    Biotechnology Progress 12:16–21.

    https://doi.org/10.1021/bp9500627

    • PubMed
    • Google Scholar
98. 1. Periole X
    2. Cavalli M
    3. Marrink SJ
    4. Ceruso MA

    (2009) Combining an elastic network with a Coarse-Grained molecular force field: structure, dynamics, and intermolecular recognition

    Journal of Chemical Theory and Computation 5:2531–2543.

    https://doi.org/10.1021/ct9002114

    • PubMed
    • Google Scholar
99. 1. Periole X
    2. Knepp AM
    3. Sakmar TP
    4. Marrink SJ
    5. Huber T

    (2012) Structural determinants of the supramolecular organization of G protein-coupled receptors in bilayers

    Journal of the American Chemical Society 134:10959–10965.

    https://doi.org/10.1021/ja303286e

    • PubMed
    • Google Scholar
100. 1. Popot JL
     2. Engelman DM

     (1990) Membrane protein folding and oligomerization: the two-stage model

     Biochemistry 29:4031–4037.

     https://doi.org/10.1021/bi00469a001

     • PubMed
     • Google Scholar
101. 1. Pratt LR
     2. Chandler D

     (1977) Theory of the hydrophobic effect 

     The Journal of Chemical Physics 67:3683–3704.

     https://doi.org/10.1063/1.435308

     • Google Scholar
102. 1. Prosser RS
     2. Ye L
     3. Pandey A
     4. Orazietti A

     (2017) Activation processes in ligand-activated G protein-coupled receptors: A case study of the adenosine A _2A receptor

     BioEssays 39:1700072.

     https://doi.org/10.1002/bies.201700072

     • Google Scholar
103. 1. Qin S
     2. Zhou H-X

     (2013) Effects of macromolecular crowding on the conformational ensembles of disordered proteins

     The Journal of Physical Chemistry Letters 4:3429–3434.

     https://doi.org/10.1021/jz401817x

     • Google Scholar
104. 1. Rashid AJ
     2. So CH
     3. Kong MM
     4. Furtak T
     5. El-Ghundi M
     6. Cheng R
     7. O'Dowd BF
     8. George SR

     (2007) D1-D2 dopamine receptor heterooligomers with unique pharmacology are coupled to rapid activation of gq/11 in the striatum

     PNAS 104:654–659.

     https://doi.org/10.1073/pnas.0604049104

     • PubMed
     • Google Scholar
105. 1. Romano C
     2. Yang W-L
     3. O'Malley KL

     (1996) Metabotropic glutamate receptor 5 is a Disulfide-linked dimer

     Journal of Biological Chemistry 271:28612–28616.

     https://doi.org/10.1074/jbc.271.45.28612

     • Google Scholar
106. Conference

     1. Romo TD
     2. Grossfield A

     (2009) LOOS: an extensible platform for the structural analysis of simulations

     2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

     https://doi.org/10.1109/IEMBS.2009.5335065

     • Google Scholar
107. 1. Rozenfeld R
     2. Devi LA

     (2007) Receptor heterodimerization leads to a switch in signaling: beta-arrestin2-mediated ERK activation by mu-delta opioid receptor heterodimers

     The FASEB Journal 21:2455–2465.

     https://doi.org/10.1096/fj.06-7793com

     • PubMed
     • Google Scholar
108. 1. Saaranen MJ
     2. Ruddock LW

     (2013) Disulfide bond formation in the cytoplasm

     Antioxidants & Redox Signaling 19:46–53.

     https://doi.org/10.1089/ars.2012.4868

     • PubMed
     • Google Scholar
109. 1. Schonenbach NS
     2. Hussain S
     3. O’Malley MA

     (2015) Structure and function of G Protein-Coupled receptor oligomers: implications for drug discovery: studying GPCR oligomer function

     Wiley Interdisciplinary Reviews. Nanomedicine and Nanobiotechnology 7:408–427.

     https://doi.org/10.1002/wnan.1319

     • Google Scholar
110. 1. Schonenbach NS
     2. Rieth MD
     3. Han S
     4. O'Malley MA

     (2016) Adenosine A2a receptors form distinct oligomers in protein detergent complexes

     FEBS Letters 590:3295–3306.

     https://doi.org/10.1002/1873-3468.12367

     • PubMed
     • Google Scholar
111. Software

     1. Schrödinger, LLC

     (2020) The PyMOL Molecular Graphics System, version 2.0

     PyMOL.

     https://www.schrodinger.com/products/pymol
112. Preprint

     1. Song W
     2. Duncan AL
     3. Sansom MSP

     (2020) GPCR oligomerisation modulation by conformational state and lipid interactions revealed by MD simulations and markov models

     bioRxiv.

     https://doi.org/10.1101/2020.06.24.168260

     • Google Scholar
113. 1. Soranno A
     2. Koenig I
     3. Borgia MB
     4. Hofmann H
     5. Zosel F
     6. Nettels D
     7. Schuler B

     (2014) Single-molecule spectroscopy reveals polymer effects of disordered proteins in crowded environments

     PNAS 111:4874–4879.

     https://doi.org/10.1073/pnas.1322611111

     • PubMed
     • Google Scholar
114. 1. Stanasila L
     2. Perez J-B
     3. Vogel H
     4. Cotecchia S

     (2003) Oligomerization of the α _1a - and α _1b -adrenergic receptor subtypes: potential implications in receptor internalization

     Journal of Biological Chemistry 278:40239–40251.

     https://doi.org/10.1074/jbc.M306085200

     • Google Scholar
115. 1. Sun B
     2. Bachhawat P
     3. Chu ML
     4. Wood M
     5. Ceska T
     6. Sands ZA
     7. Mercier J
     8. Lebon F
     9. Kobilka TS
     10. Kobilka BK

     (2017) Crystal structure of the adenosine A_2A receptor bound to an antagonist reveals a potential allosteric pocket

     PNAS 114:2066–2071.

     https://doi.org/10.1073/pnas.1621423114

     • PubMed
     • Google Scholar
116. 1. Sušac L
     2. Eddy MT
     3. Didenko T
     4. Stevens RC
     5. Wüthrich K

     (2018) A _2A adenosine receptor functional states characterized by ¹⁹ F-NMR

     PNAS 2018:13649.

     https://doi.org/10.1073/pnas.1813649115

     • Google Scholar
117. 1. Svetlana C
     2. Devi LA

     (1997) Dimerization of the δ opioid receptor: implication for a role in receptor internalization

     Journal of Biological Chemistry 272:26959–26964.

     https://doi.org/10.1074/jbc.272.43.26959

     • Google Scholar
118. 1. Szasz CS
     2. Alexa A
     3. Toth K
     4. Rakacs M
     5. Langowski J
     6. Tompa P

     (2011) Protein disorder prevails under crowded conditions

     Biochemistry 50:5834–5844.

     https://doi.org/10.1021/bi200365j

     • PubMed
     • Google Scholar
119. 1. Tabor A
     2. Weisenburger S
     3. Banerjee A
     4. Purkayastha N
     5. Kaindl JM
     6. Hübner H
     7. Wei L
     8. Grömer TW
     9. Kornhuber J
     10. Tschammer N
     11. Birdsall NJM
     12. Mashanov GI
     13. Sandoghdar V
     14. Gmeiner P

     (2016) Visualization and ligand-induced modulation of dopamine receptor dimerization at the single molecule level

     Scientific Reports 6:srep33233.

     https://doi.org/10.1038/srep33233

     • Google Scholar
120. 1. Takeda S
     2. Kadowaki S
     3. Haga T
     4. Takaesu H
     5. Mitaku S

     (2002) Identi¢cation of G Protein-Coupled Receptor Genes from the Human Genome Sequence

     FEBS Letters 520:97–110.

     https://doi.org/10.1016/s0014-5793(02)02775-8

     • PubMed
     • Google Scholar
121. 1. Tanford C

     (1978) The hydrophobic effect and the organization of living matter

     Science 200:1012–1018.

     https://doi.org/10.1126/science.653353

     • PubMed
     • Google Scholar
122. Book

     1. Tanford C

     (1980) The Hydrophobic Effect: Formation of Micelles and Biological Membranes (Second Edition)

     J Wiley.

     https://doi.org/10.1021/ed058pA246.1

     • Google Scholar
123. 1. Thomas AS
     2. Elcock AH

     (2007) Molecular dynamics simulations of hydrophobic associations in aqueous salt solutions indicate a connection between water hydrogen bonding and the hofmeister effect

     Journal of the American Chemical Society 129:14887–14898.

     https://doi.org/10.1021/ja073097z

     • PubMed
     • Google Scholar
124. 1. Thorsen TS
     2. Matt R
     3. Weis WI
     4. Kobilka BK

     (2014) Modified T4 lysozyme fusion proteins facilitate G Protein-Coupled receptor crystallogenesis

     Structure 22:1657–1664.

     https://doi.org/10.1016/j.str.2014.08.022

     • PubMed
     • Google Scholar
125. 1. Tovo-Rodrigues L
     2. Roux A
     3. Hutz MH
     4. Rohde LA
     5. Woods AS

     (2014) Functional characterization of G-protein-coupled receptors: a bioinformatics approach

     Neuroscience 277:764–779.

     https://doi.org/10.1016/j.neuroscience.2014.06.049

     • PubMed
     • Google Scholar
126. 1. Tsai C-J
     2. Lin SL
     3. Wolfson HJ
     4. Nussinov R

     (1997) Studies of Protein-Protein interfaces: a statistical analysis of the hydrophobic effect: protein-protein interfaces: the hydrophobic effect

     Protein Science 6:53–64.

     https://doi.org/10.1002/pro.5560060106

     • Google Scholar
127. 1. Tsai CJ
     2. Nussinov R

     (1997) Hydrophobic folding units at protein-protein interfaces: implications to protein folding and to protein-protein association

     Protein Science 6:1426–1437.

     https://doi.org/10.1002/pro.5560060707

     • PubMed
     • Google Scholar
128. 1. van der Vegt NFA
     2. Nayar D
     3. Vegt NFA

     (2017) The Hydrophobic Effect and the Role of Cosolvents

     The Journal of Physical Chemistry B 121:9986–9998.

     https://doi.org/10.1021/acs.jpcb.7b06453

     • PubMed
     • Google Scholar
129. 1. Vidi PA
     2. Chen J
     3. Irudayaraj JM
     4. Watts VJ

     (2008) Adenosine A(2A) receptors assemble into higher-order oligomers at the plasma membrane

     FEBS Letters 582:3985–3990.

     https://doi.org/10.1016/j.febslet.2008.09.062

     • PubMed
     • Google Scholar
130. 1. Vilardaga JP
     2. Nikolaev VO
     3. Lorenz K
     4. Ferrandon S
     5. Zhuang Z
     6. Lohse MJ

     (2008) Conformational cross-talk between alpha2A-adrenergic and mu-opioid receptors controls cell signaling

     Nature Chemical Biology 4:126–131.

     https://doi.org/10.1038/nchembio.64

     • PubMed
     • Google Scholar
131. 1. Wassenaar TA
     2. Pluhackova K
     3. Böckmann RA
     4. Marrink SJ
     5. Tieleman DP

     (2014) Going backward: a flexible geometric approach to reverse transformation from coarse grained to atomistic models

     Journal of Chemical Theory and Computation 10:676–690.

     https://doi.org/10.1021/ct400617g

     • PubMed
     • Google Scholar
132. 1. Weiß HM
     2. Grisshammer R

     (2002) Purification and characterization of the human adenosine A(2a) receptor functionally expressed in Escherichia coli

     European Journal of Biochemistry 269:82–92.

     https://doi.org/10.1046/j.0014-2956.2002.02618.x

     • PubMed
     • Google Scholar
133. 1. Wicky BIM
     2. Shammas SL
     3. Clarke J

     (2017) Affinity of IDPs to their targets is modulated by ion-specific changes in kinetics and residual structure

     PNAS 114:9882–9887.

     https://doi.org/10.1073/pnas.1705105114

     • PubMed
     • Google Scholar
134. 1. Xu F
     2. Wu H
     3. Katritch V
     4. Han GW
     5. Jacobson KA
     6. Gao ZG
     7. Cherezov V
     8. Stevens RC

     (2011) Structure of an agonist-bound human A2A adenosine receptor

     Science 332:322–327.

     https://doi.org/10.1126/science.1202793

     • PubMed
     • Google Scholar
135. 1. Xue L
     2. Rovira X
     3. Scholler P
     4. Zhao H
     5. Liu J
     6. Pin JP
     7. Rondard P

     (2015) Major ligand-induced rearrangement of the heptahelical domain interface in a GPCR dimer

     Nature Chemical Biology 11:134–140.

     https://doi.org/10.1038/nchembio.1711

     • PubMed
     • Google Scholar
136. 1. Yang Z

     (2009) Hofmeister effects: an explanation for the impact of ionic liquids on biocatalysis

     Journal of Biotechnology 144:12–22.

     https://doi.org/10.1016/j.jbiotec.2009.04.011

     • PubMed
     • Google Scholar
137. 1. Ye L
     2. Van Eps N
     3. Zimmer M
     4. Ernst OP
     5. Prosser RS

     (2016) Activation of the A2A adenosine G-protein-coupled receptor by conformational selection

     Nature 533:265–268.

     https://doi.org/10.1038/nature17668

     • PubMed
     • Google Scholar
138. 1. Yodh AG
     2. Lin K
     3. Crocker JC
     4. Dinsmore AD
     5. Verma R
     6. Kaplan PD

     (2001) Entropically driven self–assembly and interaction in suspension

     Philosophical Transactions of the Royal Society of London 359:921–937.

     https://doi.org/10.1098/rsta.2000.0810

     • Google Scholar
139. 1. Yoshioka K
     2. Saitoh O
     3. Nakata H

     (2001) Heteromeric association creates a P2Y-like adenosine receptor

     PNAS 98:7617–7622.

     https://doi.org/10.1073/pnas.121587098

     • PubMed
     • Google Scholar
140. 1. Zangi R
     2. Hagen M
     3. Berne BJ

     (2007) Effect of ions on the hydrophobic interaction between two plates

     Journal of the American Chemical Society 129:4678–4686.

     https://doi.org/10.1021/ja068305m

     • PubMed
     • Google Scholar
141. 1. Zeng F-Y
     2. Wess J

     (1999) Identification and molecular characterization of m3 muscarinic receptor dimers

     Journal of Biological Chemistry 274:19487–19497.

     https://doi.org/10.1074/jbc.274.27.19487

     • Google Scholar
142. 1. Zhu X
     2. Wess J

     (1998) Truncated V2 vasopressin receptors as negative regulators of wild-type V2 receptor function

     Biochemistry 37:15773–15784.

     https://doi.org/10.1021/bi981162z

     • PubMed
     • Google Scholar
143. 1. Zosel F
     2. Soranno A
     3. Buholzer KJ
     4. Nettels D
     5. Schuler B

     (2020) Depletion interactions modulate the binding between disordered proteins in crowded environments

     PNAS 117:13480–13489.

     https://doi.org/10.1073/pnas.1921617117

     • PubMed
     • Google Scholar

Author details

1. Khanh Dinh Quoc Nguyen

   Department of Chemistry and Biochemistry, University of California, Santa Barbara, Santa Barbara, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-9367-499X

2. Michael Vigers

   Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Validation, Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

3. Eric Sefah

   C. Eugene Bennett Department of Chemistry, West Virginia University, Morgantown, United States

   Contribution

   Conceptualization, Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

4. Susanna Seppälä

   Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, United States

   Contribution

   Conceptualization, Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

5. Jennifer Paige Hoover

   Department of Chemistry and Biochemistry, University of California, Santa Barbara, Santa Barbara, United States

   Contribution

   Data curation, Investigation

   Competing interests

   No competing interests declared

6. Nicole Star Schonenbach

   Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

7. Blake Mertz

   C. Eugene Bennett Department of Chemistry, West Virginia University, Morgantown, United States

   Contribution

   Conceptualization, Software, Supervision, Funding acquisition, Validation, Writing - review and editing

   Competing interests

   No competing interests declared

8. Michelle Ann O'Malley

   Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, United States

   Contribution

   Conceptualization, Supervision, Funding acquisition, Writing - review and editing

   For correspondence

   momalley@engineering.ucsb.edu

   Competing interests

   No competing interests declared

9. Songi Han

   1. Department of Chemistry and Biochemistry, University of California, Santa Barbara, Santa Barbara, United States
   2. Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, United States

   Contribution

   Conceptualization, Supervision, Funding acquisition, Writing - original draft, Writing - review and editing

   For correspondence

   songi@chem.ucsb.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-6489-6246

• 1,890

  views

• 317

  downloads

• 8

  citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.