Communication processes within and between the cells of the brain, organized in complex cellular networks (CCNs) (Agnati and Fuxe, 2000) allow the brain integrative actions, hence the adaptive responses of metazoan organisms. In principle, intercellular and intracellular communication processes consist of signals and recognition/decoding apparatuses of these signals (for a theoretical discussion of general aspects of this issue see, e.g. Agnati et al., 2014a).
From the end of the 19th century, the biochemical and functional implications of intercellular recognition-decoding processes have been specifically investigated, and on this basis, it has been possible not only to gather a better understanding of the physiological mechanisms that allow homeostatic responses of multicellular organisms but also a new extremely productive approach to pharmacology was made possible.
In the 1980s, by means of in vitro and in vivo experiments, our group gave indirect biochemical and functional evidence that G protein-coupled receptors (GPCRs) could allosterically interact at the plasma membrane level forming multimeric assemblies of receptors (receptor mosaics [RMs]; Agnati et al., 1980, 1982; Fuxe et al., 1983a). Thus, allosteric interactions between GPCRs at the plasma membrane level (i.e. receptor-receptor interactions [RRIs]) were proposed as a new integrative mechanism for chemical signals impinging on cell plasma membranes (for the state of the art at the middle of the 1980s, see Fuxe and Agnati, 1987a). Later on, several groups provided direct evidence for the existence of several GPCR-RMs (Fuxe et al., 1998; Bockaert and Pin, 1999; Xie et al., 1999; Franco et al., 2000; Overton and Blumer, 2000; Zeng and Wess, 2000; Angers et al., 2001; Dean et al., 2001; Devi, 2001; Portoghese, 2001; Christopoulos and Kenakin, 2002; Kenakin, 2002).
This evidence pointed to the variety of meanings that a given chemical signal can have depending on the apparatus carrying out the recognition/decoding process. The multivalence of a chemical signal has already been present in pharmacology since the middle of the last century. Actually, the concept of iso-receptors (or receptor subtypes) was originally introduced by Ahlqvist to explain the opposite effects of catecholamine observed in some target cells. He characterized these receptors capable of different recognition/decoding processes of the same signal, calling them alpha- and beta- adrenoreceptors (Ahlquist, 1948, 1980). Later on, Sir James Black (Anonymous, 1982; see Quirke, 2006) pointed out the relevance of iso-receptors for the clinical practice. In the same period as well in the subsequent years, our group has proposed that iso-receptors could have additional implications in the light of the RM concept (Agnati et al., 1980, 1982, 2003, 2010a; Fuxe et al., 1982; Fuxe and Agnati, 1985, 1987a,b).
In this context, in fact, the functional spectrum of iso-receptors becomes wider, further emphasizing the view that neurotransmitters can act as a trigger, but the induced cell responses depend mainly on both the iso-receptors that have been activated and the special RM in which they play a role.
The basic phenomenon involved in RRI is allostery and cooperativity of membrane receptors as pointed out by Changeux in 1964 by the farsighted proposal of extending the concept of cooperativity to ‘membrane phenomena involved in the recognition of communication signals and their transmission’ (Changeux, 2013a).
Accordingly, the present paper will provide basic information concerning the relevance of allostery and cooperativity for RRI, hence for the functional assembly of RMs and their possible role as components of the horizontal molecular networks (HMNs) (Agnati et al., 2005a) located in plasma membrane microdomains, especially lipid rafts (LRs) (Agnati et al., 2007a; Negro et al., 2008; Genedani et al., 2010). Next, the possible theoretical meaning of iso-receptor RMs will be discussed since iso-receptors and allostery and cooperativity allow distinguishing at least two classes of RM that may be capable of different biochemical integrative mechanisms (Agnati et al., 2005b). Finally, a broadening of the functional meaning of the iso-receptor RM is proposed based on an analogy with artificial information systems (see ‘General discussion’ section). Thus, it will be suggested that iso-receptor RM could act as a sort of ‘demultiplexer’, a logic circuit able to select an output (among a set of available possibilities) based on the features of the incoming signal and of the functional organization of the recognition apparatus.
A particular focus will be maintained on dopamine receptor (DA-R) subtypes and the iso-receptor complexes they form with other DA-R subtypes (see Agnati et al., 2005b; Hasbi et al., 2011; Guitart et al., 2014).
GPCRs and the communication processes
The importance of GPCRs as far as intercellular communication is concerned is underlined by the demonstration that they are the largest family of transmembrane receptors (Pierce et al., 2002) encoded by about 800 genes in the human genome. They are involved in the majority of signal transduction processes playing a basic role in communication processes. As far as their functional aspects are concerned, according to the classical model, specific signals (ligands) switch the receptor to an active conformational state that permits its coupling and activation of heterotrimeric guanosine triphosphate-binding proteins (Gαβγ proteins). Activation of the Gαβγ proteins, in turn, trigger multiple intracellular phosphorylation pathways involved in the regulation of gene expression and diverse biological responses, such as proliferation, and differentiation.
Later on, however, the classical model of GPCR signaling was revised (Chilmonczyk et al., 2014), since it was shown that several GPCRs (or, more precisely, seven transmembrane domain receptors) can also trigger G protein-independent signaling pathways. In fact, activated GPCRs also interact with other cytosolic ligands, such as arrestins (β-arrestin-1 and -2), which were discovered by Lefkowitz and his group in 1990 (Lohse et al., 1990). The β-arrestins turn off the GPCR response or adapt the system to a persistent stimulus by coordinating spatially and temporally the uncoupling of G protein from receptors and by mediating agonist-promoted receptor internalization (Lefkowitz and Shenoym, 2005). Actually, numerous GPCR-interacting proteins (GIPs) have been identified, modulating GPCR recognition/decoding processes and in some instances allowing for the formation of novel signal transduction complexes that modulate cellular function. Furthermore, GIPs regulate GPCR processing in the endoplasmic reticulum, trafficking to the cell surface, compartmentalization to plasma membrane microdomains, endocytosis, and trafficking between intracellular membrane compartments (Maurice et al., 2011; Magalhaes et al., 2012). In particular, a number of GIPs have been shown to exert dramatic effects on both the biosynthetic trafficking and the postendocytic sorting of a particular GPCR (von Zastrow and Kobilka, 1994; Ritter and Hall, 2009). A schematic representation of the molecular networks involved in the recognition/decoding processes carried out by GPCR is given in Figure 1. The relevance of the plasma membrane microdomains, in particular LRs and caveolae, for the formation of GPCR complexes and function should be noted (see, e.g. Becher and McIlhinney, 2005; Patel et al., 2008; Genedani et al., 2010; Czysz et al., 2015).
The present paper deals with a further mechanism of functional plasticity in the recognition/decoding processes of a given chemical signal by GPCR, namely the expression of more receptor forms capable of recognizing and decoding the same signal, i.e. of iso-receptors.
The iso-receptor concept
The definition of iso-receptors was based on the criteria defining isozymes (Hebebrand et al., 1988); however, it can be further detailed by using the following five criteria:
At the othosteric binding site, they recognize the same endogenous ligand but sometimes with different affinities.
They have similar chemical structures; in the case of GPCRs, they are all seven transmembrane domain receptors.
They may trigger different intracellular molecular networks.
It is possible to differentiate iso-receptors by means of exogenous ligands.
They can be differently assembled to form different multimeric receptor complexes.
In general, an iso-receptor consists of one or more protein subunits and/or domains for each of which structurally slightly different forms can exist. By definition, all iso-receptors bind the same endogenous ligand, and in a biological sense, they could have evolved to enable the organism to react differently to such a ligand. In fact, mutations in some subunits can directly affect the binding site, possibly resulting in affinity changes that often are exploited experimentally for identifying receptor subtypes (Agnati et al., 1980; Rudolph and Knoflach, 2011; Changeux, 2013a).
However, the functional features of a receptor can also be modified by mutations in domains not involved in ligand recognition since GPCR can show changes in the response to allosteric effectors, i.e. to ligands binding to sites different from the othosteric binding site (Kenakin and Miller, 2010).
It is noteworthy that almost for each given endogenous ligand acting through a GPCR, a set of iso-receptors for that GPCR can be identified. Thus, the small structural differences occurring between iso-receptors can trigger differences in ligand recognition and/or in G protein/β-arrestin coupling characteristics, leading to quite different signaling properties of the various receptor forms (Fuxe et al., 1998; see also Shenoy and Lefkowitz, 2011; Alexander et al., 2013). DA-R subtypes represent a significant example of this strategy.
The DA-R subtypes
Dopamine signal is recognized/decoded by two subclasses of dopamine iso-receptors, the (D1)-like (D1 and D5) and the D2-like (D2, D3, and D4) receptors, with capacity to activate or inhibit adenylyl cyclase and the cyclic AMP signaling pathway, respectively. Thus, D1-like receptors couple to the Gs/olf proteins to activate adenylyl cyclase-mediated formation of cAMP, whereas the D2-like receptors couple to the Gi/o proteins to inhibit adenylyl cyclase (Sibley and Monsma, 1992; Missale et al., 1998).
It should be noted that while D1 and D5 show about 80% homology in their transmembrane domains, D3 and D4 are 75% and 53% homologous, respectively, with the D2 receptor.
A further structural difference has been demonstrated in the cytoplasmic domain since the COOH-terminal for the D1-class receptors is about seven times longer than that of the D2-class receptors. On the contrary, the NH2-terminal domain has about the same number of amino acids in all DA-Rs (Gingrich and Caron, 1993; Missale et al., 1998).
Polymorphic variants of some DA-Rs also exist. Examples include D2 and D4 receptors. The D2 receptor exists in two isoforms: the long form (D2L) and the short form (D2S). The two isoforms are generated from the same gene by alternative splicing. D2L differs from D2S by the addition of 29 amino acids in the third intracellular loop (ICL) of its protein structure.
The gene encoding the D4 receptor contains a large number of polymorphisms in its coding sequence (LaHoste et al., 1996). The most extensive polymorphism is in exon 3, a region that codes for the third ICL of the protein and consists of a variable number of tandem repeats in which a 48-bp sequence exists as 2- to 11-fold repeats (Wang et al., 2004). The three most common variants contain 2, 4, and 7 repeats (D4.2, D4.4, and D4.7, respectively).
Different functional significances of the isoforms have been identified for both the D2 (Xu et al., 2002) and D4 (Gonzàles et al., 2012) receptor variants.
Certain types of dopamine iso-receptors are preferentially distributed in some brain areas (Missale et al., 1998; Gerfen, 2000; Vallone et al., 2000; Seeman, 2006; Sokoloff et al., 2006; Rankin et al., 2010), underlining the possibility of their peculiar role for some integrative functions of the CCN present in that brain area.
Thus, it could be surmised that besides the functional relevance of a certain chemical signal for the integrative action of the CCN present in that brain area, a crucial functional role has the recognition/decoding processes of that chemical signal via certain types of iso-receptors.
As far as the distribution of the DA iso-receptors in the brain areas is concerned, it has been observed that:
D1 receptors are expressed at a high level of density in the nigrostriatal, mesolimbic, and mesocortical areas and frontal cortex, while at lower levels, in the hippocampus, cerebellum, thalamic areas, and hypothalamic areas.
D5 receptors are expressed, but only at low levels, in the prefrontal cortex, premotor cortex, cingulated cortex, entorhinal cortex, as well as in the substantia nigra, hypothalamus, hippocampus, and dentate gyrus.
D2 receptors are expressed at higher levels in striatum, nucleus accumbens, and olfactory tubercle, while at lower, even significant, levels, in the substantia nigra, ventral tegmental area, hypothalamus, cortical areas, septum, amygdala, and hippocampus.
D3 receptors are widely expressed in the brain with moderate amounts of D3 binding in the basal ganglia, parietal, temporal and occipital cortex, and cerebellar cortex, followed by substantia nigra, hippocampus, and the basolateral, lateral, and basomedial amygdaloid nuclei (Levant, 1997). The highest expressions were observed in the islands of Calleja and nucleus accumbens (Suzuki et al., 1998).
Concerning the distribution of DA-Rs at the synaptic level, it has been demonstrated that the D1 class of DA-Rs is found exclusively post-synaptically on dopamine-receptive cells, while the D2 class of DA-Rs is expressed both post-synaptically on dopamine target cells and presynaptically on dopaminergic neurons (Sokoloff et al., 2006; Rankin et al., 2010; Rondou et al., 2010).
GPCRs as components of molecular networks
Differential expression of GIPs and rapid alterations of GPCR/GIP interaction networks are efficient means to regulate GPCR function in a tissue-specific and spatiotemporal manner to trigger appropriate cellular responses (Daulat et al., 2009).
At least five strictly interconnected molecular networks should be considered in analyzing the recognition/decoding processes carried out by GPCR and their turnover (see Figure 1). Let us give some main aspects of these molecular networks and on their main interconnections (refer to cited literature for a more detailed description Agnati et al., 2005a, 2006a, 2008a, 2010a).
The ligand recognition process by the GPCR takes place according to different steric patterns since the location of the agonist-binding site is highly variable for different receptors. Thus, monoamines and acetylcholine bind within the transmembrane (TM) core. Small peptide hormones bind to the amino terminus, the extracellular loops between TM domains and within the TM core. Large amino terminal domains form the binding site for glutamate, GABA, glycoprotein hormones, ions (the Ca2+-sensing receptor). Finally, in protease-activated receptors, the agonist is generated by proteolytic cleavage of the amino terminus of the receptor (Ji et al., 1998).
Also, concerning the interaction between GPCR and their cognate G proteins, multiple sites have been identified. These include ICL 2 between TM3 and TM4, ICL 3 between TM 5 and TM 6, and loop 4 formed between TM 7 and the lipid modification on the proximal carboxyl terminus (Bockaert et al., 2004; Shpakov, 2011). Agonist binding causes steric changes in the arrangement of the TM domains that are allosterically transmitted to the associated G-protein heterotrimer (Gαβγ) that dissociate into Gα and Gβγ subunits. Both dissociated Gα and Gβγ subunits are capable of modulating a variety of effectors, including adenylyl cyclase, phospholipase C, and ion channels. As pointed out above, a GPCR can also signal through several G protein-independent pathways. In particular, β-arrestins and kinases, by interacting with GPCR, can activate intracellular signaling pathways that may involve receptor desensitization, coupling to multiple G proteins, Gα or Gβγ signaling, as well as activation of G protein-independent molecular networks (Chilmonczyk et al., 2014). It has also been shown that different agonists with a preferential triggering of a peculiar molecular network can activate the same GPCR. This phenomenon has been called ‘agonist functional selectivity’ or ‘agonist biased signaling’ (Chilmonczyk et al., 2014). As far as trafficking is concerned, the process is strictly linked to signaling since receptor activation triggers not only signaling but also receptor endocytosis. It should also be noted that GPCRs are synthesized in the endoplasmatic reticulum and can dimerize/oligomerize already at this biosynthesis stage (Bulenger et al., 2005); hence, oligomerization could represent an additional mechanism for proper folding, with each protomer acting as a chaperone for the other via interaction of their hydrophobic surfaces. In addition, signaling proteins can be incorporated to the complex already at this early stage (Dupre and Hebert, 2006) and could function as sorting signals for specific complexes.
This brief overview of GPCR-associated molecular networks underlines once more the importance of proteins in the biochemical recognition/decoding processes of intercellular and intracellular signaling. It is noteworthy that many proteins can self-associate into assemblies of two or more monomers working as ‘switches’ that regulate metabolic reactions (as enzymes) or capable of triggering appropriate cellular responses to signals (as receptor-transducer complexes). However, until the 1980s, it was not surmised that GPCRs could assemble into multimeric complexes, and our early investigations suggested for the first time the possible existence of GPCR hetero-oligomers with emergent properties (Fuxe et al., 1981, 1983a; Agnati et al., 1982, 1984; Fuxe and Agnati, 1985, 1987a). In the opening address of the WGC Symposium, Fuxe and Agnati proposed a broad view of the phenomenon by surmising that GPCR, together with different types of proteins, could form molecular assemblages at plasma membrane level capable of operating as integrative microdevices: “Very likely, we will find out that some sophisticated elaborations of information are performed at the membrane level, via interactions within and among different classes of macromolecules” (Fuxe and Agnati, 1987b).
Based on these assumptions and on new experimental data, the concept of HMN was introduced as a molecular microdevice capable of sophisticated integration of several types of chemico-physical signals impinging on the cell plasma membrane (Agnati et al., 2003, 2010a,b).
A basic biochemical mechanism behind this function is the plasticity of the steric conformation of proteins and their ‘stickiness’ (Pauling, 1953). In fact, protein monomers can aggregate and the subunits of a multimeric protein undergo changes in both their conformation (tertiary structure) and arrangements of inter-subunit contacts (quaternary structure).
These steric changes take place in response to the binding of other molecules and/or under the influence of chemical-physical conditions (i.e. the energy landscape) of the microenvironment in which they are embedded (see ‘The receptor mosaic concept’ section; Agnati et al., 2007a, 2010b; Borroto-Escuela et al., 2011a,b). The biochemical and biophysical processes that are involved in the assembly of GPCRs have been investigated, but the field has not been yet completely clarified (Lambert and Javitch, 2014).
The RM concept
Evidence for the existence of receptor complexes
In the 1980s, the first indication of the possible existence of GPCR-GPCR interactions at plasma membrane level was obtained from binding studies on cell membranes and on brain sections (Agnati et al., 1980, 1983a; Fuxe et al., 1981, 1983a) as well as from in vivo functional studies (Agnati et al., 1983b, 1985; Fuxe et al., 1983b, 1984, 1986).
Later on, more sophisticated approaches, such as FRET, BRET, and PLA, provided further support to the assumption (see Trifilieff et al., 2011; Borroto-Escuela et al., 2013a,b; Guidolin et al., 2015), and a new AFM approach (Agnati et al., 2010a), associated with computer-assisted image analysis of immunocytochemical (ICC) preparations and biochemical experiments, was provided to support the assumption of A2A-D2 physical and functional interactions at plasma membrane level. Thus, it has been proposed that to support the possible existence of receptor multimeric complexes at the plasma membrane level and of direct RRI, at least six conditions should be fulfilled. Some of these conditions are schematically illustrated in Figure 2 and can be briefly mentioned as follows (Agnati et al., 2010a; Fuxe et al., 2012; Guidolin et al., 2015):
Colocalization of the GPCR in the same microdomain at the plasma membrane level, representing a necessary condition that can be investigated, e.g. by computer-assisted image analysis of ICC preparations (Agnati et al., 2005c);
Physical proximity in a nanometer range of the involved proteins, representing a necessary condition that can be investigated, e.g. by biophysical techniques such as BRET, FRET, PLA, and AFM or by biochemical techniques such as coimmunoprecipitation (Skieterska et al., 2013);
Allosteric modulation of the affinity of the orthosteric binding site of GPCR-B following the binding of a ligand to the orthosteric site of GPCR-A. In particular, modulation of the intracellular molecular networks following the GPCR cross-talk at the plasma membrane level (i.e. the RRI) provides a strong support for RRI and can be investigated by means of ad hoc biochemical experiments (Agnati et al., 1982, 2003, 2007b, 2008a; Fuxe et al., 2005, 2007a);
Corecognition that can be demonstrated by means of bivalent ligands capable of binding at the same time both partners in a pair of interacting receptors (Bhushan et al., 2004; Daniels et al., 2005; Hiller et al., 2013; Yekkirala et al., 2013). This condition can be investigated by means of binding and pharmacological experiments;
Cointernalization of the GPCR. Thus, it can be shown that activation of GPCR-A (e.g. D2-R) leads not only to its internalization (i.e. of D2-R) but also to the internalization of GPCR-B (i.e. of A2A-R). This evidence can be obtained, e.g. by ICC associated with computer-assisted image analysis (Genedani et al., 2005; Agnati et al., 2010a);
Blockade of the heteromer formation (see Azdad et al., 2009; Borroto-Escuela et al., 2010a; Hasbi et al., 2014) or disruption of the formed hetero-receptor complex (Kenakin and Miller, 2010; Pei et al., 2010) by means of ligands interacting with amino acid sequences involved in the RRI interface. This experimental approach would benefit from a bioinformatics evaluation of the possible amino acid sequences forming the interaction interface (see ‘Interaction interfaces and RM arrangement: a bioinformatics analysis of DA iso-receptors’ section).
The existence of receptor multimeric complexes (receptor homomers and receptor heteromers) in cellular models is presently not questioned, and the overall available evidence (obtained through multiple approaches with consistent results) strongly supports the relevance of the phenomenon also in native systems (Borroto-Escuela et al., 2013b; Bouvier and Hébert, 2014; Guidolin et al., 2015). Thus, GPCRs can be assembled into multimeric complexes and, via allosteric interactions (RRIs), integrate signals impinging on cell membrane and trigger cellular responses differing from the ones triggered by the activation of the single GPCR. In this respect, already in the 1980s, the possible functional meaning of RRI at synaptic levels was discussed also in view of the coexistence of monoamines and peptides in the same neuron terminals (Agnati et al., 1983c,d; Fuxe et al., 1983a; Hökfelt et al., 1983, 1986, 1987; Fuxe and Agnati, 1987a). Thus, the presence at postsynaptic level of the cognate receptors assembled in a RM could allow the cross-talk between different transmitters such as monoamines and peptides (Agnati et al., 1980, 2010a; Fuxe et al., 1981, 1983a). Furthermore, it was pointed out that RRIs could occur also in perisynaptic and extrasynaptic RM in view of the possible diffusion of chemical signals in the extracellular space via volume transmission (VT), allowing integration of several intercellular signals at the plasma membrane level of far-located target cells (Agnati and Fuxe, 2000; Agnati et al., 2006a, 2010c).
It is obvious that if GPCRs aggregate the topology of the multimeric assembly, the quaternary organization can play a fundamental role on the integrative recognition/decoding processes carried out by the receptor complex. Hence, we have introduced the term RM as a meaningful pictorial analogy illustrating how different assemblies could be obtained from the same set of tesserae (e.g. GPCR) assembled according to different topologies. Each of these different spatial patterns can lead to a peculiar recognition/decoding process of a certain signal impinging on the cell plasma membrane (Agnati et al., 1982, 2005d, 2009a). In agreement with the mosaic analogy, both the tesserae that assemble into a real mosaic as well as the monomers that assemble into a GPCR-RM have to match their tertiary conformations. However, in the case of GPCR (forming a RM), protein plasticity (e.g. protein flexibility) can favor their matching while protein stickiness (e.g. electrostatic interactions) can favor their assemblage (Azdad et al., 2009; Ferré et al., 2009, 2010; Fuxe et al., 2009a,b, 2012; Navarro et al., 2009, 2010; Borroto-Escuela et al., 2011b; Agnati et al., 2013; Tovo-Rodrigues et al., 2014).
As far as the triggering of the intracellular molecular networks is concerned, it should be noted that the RM concept changed the classical model of signal transduction. In fact, the earlier classical model maintained that the successive steps of the recognition/decoding process were organized in a ‘linear’ manner.
According to this model, the ligand interacts with its cognate receptor and the ligand-receptor complex operates as a functional unit capable of triggering specific signals in the cell (e.g. changes in the second-messenger levels) that cause multiple cellular chemical-physical responses.
Thanks to RRI, a possible divergent activation of different cytoplasmic networks can occur already at the cell plasma level. This functional aspect should be considered also in the frame of the data demonstrating that allosteric modulators can alter the conformation of the receptor, hence not only its recognition/decoding processes but also the recognition/decoding processes of other GPCRs of the RM (Agnati et al., 2006a,b; Kenakin and Miller, 2010). It should be noted that allosteric modulators can reach GPCR from the extracellular, membrane, and intracellular environments (Kenakin, 2010).
Thus, the recognition/decoding processes carried out by a GPCR is conditioned by three environments: the extracellular fluid, the plasma membrane, and the intracellular fluid (see Figure 1 and also Kenakin and Miller, 2010) as well as by the RRI with other GPCRs of the RM.
In particular, the following should be mentioned:
The ligand (neurotransmitter or hormone) impinges on the interface between the extracellular environment and the plasma membrane and binds the orthosteric site of the receptor;
The interactions of the receptor at the plasma membrane/cytoplasm interface with specific cytosolic molecules (e.g. heterotrimeric G proteins, as well as other key cytosolic proteins) (Oldham and Hamm, 2008);
The interactions of the receptor in the plane of the lipid bilayer with other GPCR (Borroto-Escuela et al., 2011a; Guidolin et al., 2015) within the RM or with other membrane-associated proteins and/or lipids (Kenakin and Miller, 2010);
The possible role of ‘hub’ proteins (see Glossary table) in plasma membrane microdomains. This important phenomenon has been recently proposed for adenylate cyclase (see ‘A possible criterion for RM classification based on homotropic vs. heterotropic cooperativity’ section and Cooper and Tabbasum, 2014);
Actions of physicochemical factors characterizing the three environments with which the GPCR is in contact that can affect the energy landscape of the receptor (Deupi and Kobilka, 2010; Venkatakrishnan et al., 2013; see also below).
Concerning the concept of energy landscape, Motlagh and collaborators have pointed out that proteins, hence also GPCRs, sample a spectrum of conformations that form their ‘energy landscape’ (Frauenfelder et al., 1988, 1991; Hilser et al., 1998, 2006; Motlagh et al., 2014). Thus, proteins are dynamically fluctuating macromolecules, constantly taking conformational excursions away from a canonical native structure (Liu et al., 2006; Motlagh et al., 2014). Membrane potential can affect the energy landscape of GPCR since it has been demonstrated that both the activity of GPCR and their affinity toward agonists are regulated also by membrane potential (Mahaut-Smith et al., 2008; Sahlholm et al., 2011; Chaim et al., 2013; Rinne et al., 2013).
To summarize, the following main structural and operational characteristics of RM affect their integrative actions:
Composition of the RM as far as the chemical nature of monomers is concerned (Agnati et al., 2005b), in particular, whether the RM is formed by different GPCRs (upper panel, Figure 3) or by only one type of GPCR or by iso-receptors of the same GPCR (lower panels, Figure 3). These different compositions could lead to hetero-topic cooperativity (upper panel, Figure 3) or homotropic cooperativity (lower panels, Figure 3), respectively;
Biochemical interfaces between GPCRs may form more or less stable protein-protein interactions and also may be differently suited to allow the transmission of allosteric signals. As illustrated in Figure 4 (upper panel), it can be surmised that the RRIs outside the plasma membrane are possibly plastic contacts, that is they can be formed and/or broken down more easily than the RRIs inside the membrane or the ones that occur via the scaffold proteins (Agnati et al., 2003, 2005d; Ciruela et al., 2005; Franco et al., 2007; Fuxe et al., 2007b). Furthermore, as suggested in a previous paper (Agnati et al., 2010a), the receptor-receptor biochemical interfaces could have special amino acid sequences operating as ‘check-points’ capable of controlling the allosteric interactions between the two interacting GPCRs (Figure 4; see also ‘Relevance of allostery for the GPCR-GPCR interactions’ section);
Topology of the single GPCR in the RM that can be linear, and hence, each GPCR is in contact at most with two GPCRs; or not linear, and hence, each GPCR can be in contact with a variable number of partners (see Figure 5). A peculiar topology is the closed arrangement that has been formally analyzed in previous papers as a molecular reverberating circuit, hence for its possible functional implications for learning and memory (Agnati et al., 2007c; Guidolin et al., 2007);
Order of activation of the single monomers of the RM since it can affect in a marked way the integrative action of RM especially if a hub receptor can be surmised in the multimeric complex (Agnati et al., 2008a, 2009b).
It is worthwhile to note that the last two mentioned operational characteristics allow different integrative actions by RM that are chemically identical.
Relevance of allostery for the GPCR-GPCR interactions
Monod (1979) defined allostery as ‘the second secret of life’ since allostery could be considered important second only to the genetic code (Fenton, 2008), and as mentioned above and discussed in previous papers, the basic phenomenon mediating RRI is allosterism (see Agnati et al., 2005b, 2010a; Kenakin et al., 2010).
Allostery, or a ‘different shape’, according to the classical view, involves coupling of conformational changes between two widely separated binding sites in a protein; hence, allostery allows an extraordinary functional plasticity to proteins, resulting as a crucial mechanism for living cells. Allosterism is a term nowadays used with broader meanings with respect the one proposed by Monod and coworkers about 50 years ago (Monod, 1979; for a historical and theoretical discussion, see Changeux, 2013a,b).
According to the recent views (see Kenakin and Miller, 2010; Nussinov, 2013; Nussinov and Tsai, 2013), proteins subject to allosteric communication can be monomers or components of large, hetero-oligomeric complexes and allosteric behavior can be even displayed by single domains within a protein (see also Agnati et al., 2007b, 2008b). Since allostery involves the propagation of signals between distant sites in a protein structure (Changeux and Edelstein, 2005), many experimental studies and theoretical models suggest that there is a network of physically interconnected and/or thermodynamically linked residues forming channels along which signals are communicated between binding sites (Goodey and Benkovic, 2008).
Thus, allostery has been proposed as a universal phenomenon whereby a perturbation by an effector at one site of the molecule leads to a functional change at another through alteration of shape and/or dynamics (Nussinov and Tsai, 2013).
As Motlagh et al. (2014) point out, the phenomenon of allosterism is related to the conformational steric plasticity of proteins. Actually, all possible conformations of a protein and, hence, also of GPCR are sampled (or populated) according to their energies. This means that lower energy conformations are sampled more often than those of higher energy are. Because the binding of any ligand increases how often that state is sampled, allosteric ligands and the medium effectively remodel the energy landscape of allosteric proteins such as GPCR. Thus, an important point critical to typifying an allosteric protein ensemble, hence also a RM, is the assessment of the small fraction of the conformations of the ensemble that are stabilized by a certain ligand and/or by some chemico-physical characteristics of the medium. In fact, such a stabilization will cause a redistribution of the probabilities of every state of the ensemble (Motlagh et al., 2014).
According to such a view, every state of a RM can have potentially different affinities for the orthosteric ligands and bind different allosteric modulators; hence, it may trigger different cytoplasmic molecular networks.
Let us briefly discuss some aspects of the allosteric interactions in a RM and the possible role of cooperativity for RRI (Agnati et al., 2005b, 2010a).
Allostery occurs also within a single GPCR (as shown in the lower right panel of Figure 4; Agnati et al., 2010a); hence, the complexity of the integrative actions carried out by a RM depends on allosteric interactions within and between the GPCRs of the RM. Furthermore, GIPs, by a fine-tuning of receptor steric conformations, likely affect their predisposition to form heteromers as well as their aptitude of showing peculiar allosteric interactions. It should be also pointed out that GPCR assemblage can occur by different biochemical mechanisms that likely have also different functional impacts on the integrative action of the RM (Tovo-Rodrigues et al., 2014).
An overview is given in the upper panel of Figure 4 that should be analyzed in the frame of the articles cited by recent reviews (see Kenakin and Miller, 2010; Borroto-Escuela et al., 2014; Ferré et al., 2014; Guidolin et al., 2015) and of the experimental work of Woods and coworkers on the relevance of electrostatic interactions (Ciruela et al., 2004; Woods et al., 2005) to generate receptor complexes and on the role of certain kinases (as for instance adenylate cyclase) to impart specificity to the interactions (Woods and Jackson, 2013). It is also noteworthy that the noncovalent complexes so formed appear more stable than covalent bonds (Jackson et al., 2005, 2006). Once the receptor assemblage is formed (and this is not a completely solved problem), the relevant aspect is how the allosteric interactions among GPCRs in the multimeric complex occurs.
A peculiar aspect of allosteric interactions is the cooperativity phenomenon that can be observed in macromolecule assemblages when the number of binding sites or their affinity for a ligand is a nonlinear function of the ligand concentration. Thus, the phenomenon of cooperativity is displayed by molecular systems involving elements, which act nonindependently of each other since the binding of one ligand molecule to one site either increases (positive cooperativity) or decreases (negative cooperativity) the affinity of the other site(s) for a ligand. Such effects can be either homotropic, i.e. one ligand species affects the binding of the same ligand species, or heterotropic, i.e. one ligand species affects the binding of a different ligand species.
In the present article, emphasis will be given to the former since homotropic cooperative phenomenon is likely in operation in RM formed by both homoreceptors and iso-receptors.
Thus, as proposed in a previous paper, cooperativity can be a criterion to classify different types of RM that can display different integrative capabilities (Agnati et al., 2005b).
Iso-receptors as ‘tesserae’ of RM
A possible criterion for RM classification based on homotropic vs. heterotropic cooperativity
Since allostery is a basic phenomenon in RRI, cooperativity plays an important role in the RM integrative actions. On this basis, it has been proposed that the two types of cooperativity, namely homotropic and heterotropic cooperativity, could allow distinguishing two types of functionally different RM (see Agnati et al., 2005b):
RM-type 1 (RM1): The receptors of the multimeric complex recognize/decode the same chemical signal (Nt). Thus, it is suggested to distinguish the homo-RMs (i.e. formed by one type of iso-receptor) from the iso-RMs (i.e. formed by different iso-receptors of the same GPCR) (see lower panels of Figure 3). A well-studied case is that of RM formed by the different subtypes of DA-R (Nimchinsky et al., 1997; Strange, 2005; Rashid et al., 2007; Fiorentini et al., 2008; Guitart et al., 2014; Fuxe et al., 2015). Since the monomers of these RM recognize the same Nt homotropic cooperativity is possible.
RM-type 2 (RM2): These are hetero-RMs formed by different types of receptors. Homotropic cooperativity is not possible, but allosteric interactions can occur, causing a change in the recognition/decoding processes of the monomers (see upper panel of Figure 3). Thus, it has been shown that depending on which partner is costimulated, the affinity of the D2 receptor for dopamine is either reduced (as in the adenosine A2A-D2 hetero-oligomer; Fuxe et al., 2003, 2014) or enhanced (as in the somatostatin SST5-D2 hetero-oligomer; Rocheville et al., 2000; Agnati et al., 2005b).
It can be surmised that if DA binding to a RM1 is considered, the iso-receptor with the highest affinity for DA (hub receptor of the RM1) regulates the affinity of the other iso-receptors of the RM1 positively or negatively in the case of positive or negative homotropic cooperativity, respectively.
Thus, in the presence of a low concentration of the ligand (e.g. DA), the positive cooperativity favors the activation also of the other iso-receptors of the RM1, while the negative cooperativity leads to the preferential activation of the hub receptor. In the presence of high concentrations of the ligand, negative cooperativity avoids the saturation of the no-hub receptors.
In particular, it has been proposed that cooperativity could play a role in the differentially tuning receptor sensitivity of intrasynaptic vs. extrasynaptic RM (Agnati et al., 2005b). Hence, we have hypothesized that negative cooperativity between receptors in RM1 is a mechanism important at the synaptic level where the transmitter concentrations are high (in the order of millimolar concentrations), whereas positive cooperativity between receptors in RM1 is a mechanism important at the extrasynaptic level since the concentration of the chemical signal is usually in the nanomolar range (Vizi, 2000).
In the case of RM1 formed by the same iso-receptor (i.e. a homomer RM1), it can be surmised that the topological arrangement (see Figure 5) and the possible allosteric effects of signals originated in one of the three environments (i.e. extracellular, intramembrane, or intracellular) can govern which iso-receptor will operate as a hub in RM1. Furthermore, it can be surmised that something like a ‘symmetry rule’ (Ackers et al., 1992) can be in operation in the allosteric interactions of RM formed by iso-receptors arranged according to a peculiar topology (see Agnati et al., 2005e, and lower panel of Figure 5).
In the case of hemoglobin, the symmetry rule states that a quaternary switching from the tense (T) form (i.e. the ‘deoxy’, low-affinity state) to the relaxed (R) form (i.e. ‘oxy’, high-affinity state) takes place whenever haem-site binding creates a tetramer with at least one ligated subunit on each dimeric half-molecule.
Although it is obvious that the symmetry rule has been proposed for hemoglobin and might not have a general validity for every tetrahomomeric protein, it clearly indicates that RM1s might have some, until now not deeply investigated, biochemical characteristics that can affect their integrative functions. It is therefore possible to surmise that especially the topological arrangements of iso-receptors indicated in the lower panel of Figure 5 can show allostery according to some sort of a symmetry rule. Such can be the case of DA-R tetramers that may mirror the hemoglobin structural organization. At least for D2-receptors, the assumption that dimers can be assembled into tetramers is supported by experimental observations (Zawarynski et al., 1998).
Actually, it has been shown that D2-receptor oligomerization is required for D2-receptor trafficking to the cell-surface; hence, dimers might represent the ‘building blocks’ of high-order oligomers (Lee et al., 2003) and D2-receptor tetramers may be possible. Previous data have indicated that also D3-receptor tetramers seem to be the dominant form in the cerebral cortex (Nimchinsky et al., 1997). Thus, if the restrictions imposed by the symmetry rule are in operation, RM formed by D2 or D3 tetramers could detect not only dopamine binding but also whether it has occurred on the same dimer or on the two dimers that form the tetramer via the absence or presence of the cooperative behavior as dictated by the symmetry rule (Agnati et al., 2005b). As discussed below (‘Biochemical and functional aspects of RM formed by DA iso-receptors’ section), it has been demonstrated that also D1-D3 is a tetrameric heteromer, constituted by two interacting D1R and D3R homodimers coupled to Gs and Gi proteins, respectively (Guitart et al., 2014).
Based on these data, it would be interesting to analyze the peculiar integrative capability of RM1 tetramers maybe having as starting assumption the symmetry rule.
Interaction interfaces and RM arrangement: a bioinformatics analysis of DA iso-receptors
As mentioned above, the possibility that iso-receptors could assemble according to different topologies, leading to different receptor complexes, dramatically increases the spectrum of recognition/decoding processes available to the cells even when the chemical signal impinging at plasma membrane level is the same. Bioinformatics methods represent a key tool to investigate this topic, since they allow a wide theoretical exploration useful to orient the experimental work. Two aspects, in particular, can be well addressed by bioinformatics analysis:
The first aspect concerns the identification of the possible interfaces that a receptor protein can exploit to interact with a receptor partner. The nature of the interface is important, since it influences the allosteric processes and, consequently, the functional features of the resulting complex. In this respect, the evidence that intrinsically disordered domains play a significant role in protein-protein interaction (Hilser and Thompson, 2007) was particularly intriguing, and the analysis of intrinsic disorder is a presently followed strategy to identify GPCR regions potentially linked to RRIs (Agnati et al., 2008b; Tovo-Rodrigues et al., 2014). The analysis of disordered domains, however, does not help in the prediction of putative interaction sites located in the TM helices and other methods are needed to estimate favorable contact surfaces on the TM helices of GPCR (see Nemoto and Toh, 2005).
The second aspect concerns the estimate of the possible geometrical arrangements the receptor complex can assume. This feature is a consequence of a number of conditions, including not only the physical properties of the interacting proteins (i.e. the available interaction interfaces) but also the microenvironment surrounding the interacting partners (i.e. the energy landscape; Frauenfelder et al., 1991), and can deeply influence the functional behavior of the RM (Agnati et al., 2007b).
An illustrative analysis focused on the dopamine iso-receptors is described in the Appendix. The interaction interfaces identified on these class A GPCR are reported in Table 1. As shown, each receptor can theoretically exploit multiple interaction interfaces located in both the TM helices and the intracellular domains. As far as the TM domains are concerned, TM5 and TM6 were predicted as possible interaction sites in all the DA-Rs. This result is consistent with available experimental data indicating these domains as the most frequently observed interfaces between class A GPCR heteromers (Guo et al., 2008; Borroto-Escuela et al., 2010a). Alternative interaction interfaces at the level of the TM4 domain were predicted for the D1-like family of DA-Rs. This result is also consistent with experimental data reporting the involvement of TM4 helix in a variety of interactions between GPCR (Fotiadis et al., 2003; Wu et al., 2012). Concerning the intracellular domains, ICL 3 was a predicted site of interaction in all the DA-Rs, while the C-terminal tail resulted as an additional possible interface in the D1-like family of DA-Rs. These results show consistency with the experimental results by Woods et al. (2005) demonstrating that strong electrostatic interactions can occur between intracellular domains (namely ICL3 and C-terminus) that are linked to the presence of a negatively charged serine-phosphate-containing intracellular motif of one receptor and a positively charged arginine-rich motif of a second receptor.
A major consequence of the possible existence of multiple interaction interfaces is that the assemblage of receptor molecules to form a RM could occur in a number of different geometrical arrangements. Bioinformatics predictions support this view. As illustrated in the Appendix, two types of arrangements can be predicted for the D1-D2 dimer: one involving an interaction between TM domains of the partners, and the second based on an interaction at the level of the intracellular domains. As discussed in the section that follows, the latter is consistent with recent experimental data (Hasbi et al., 2014).
Biochemical and functional aspects of RM formed by DA iso-receptors
In principle, all the DA iso-receptors may be involved in RM of the type RM1 that have different localizations and differential mechanisms to activate specific intracellular molecular pathways. Thus, as discussed in the ‘Possible speculations on the functional relevance of iso-receptors’ section, a complex interplay among the DA iso-receptors in integrating and mediating critical brain functions can take place.
Although these investigations are still at their beginning, important data are already available. In fact, in vitro and in vivo studies exist (see Fuxe et al., 2015, for a recent review) demonstrating that the following DA iso-receptor complexes are possible (Borroto-Escuela et al., 2014) and capable of ‘emergent’ recognition/decoding properties:
D1-D2 (Lee et al., 2004);
D1-D3 (Marcellino et al., 2008);
D2-D4 (Borroto-Escuela et al., 2011b; Gonzàles et al., 2012);
D2-D3 (Scarselli et al., 2001); and
D2-D5 (So et al., 2009).
Thus, DA iso-receptors can form novel pharmacological entities through the formation of receptor heteromeric complexes by oligomerization not only with other GPCR but also with other DA-iso-receptors (Chun et al., 2013; Hasbi et al., 2014).
Let us consider the first two DA homoisomers (according to the nomenclature of Figure 3) that have been investigated with detailed studies and have important pharmacological implications:
D1-D2 iso-RM: Dopamine D1R and D2R receptors are the most abundant dopaminergic receptors in the striatum, and the presence of D1-D2 oligomers with unique functional properties was first shown in transfected cells using different methods (Rashid et al., 2007; Hasbi et al., 2014).
Thus, a clear segregation between the pathways expressing these two receptors has been reported in certain subregions, and in addition, the presence of D1-D2 oligomers within a unique subset of neurons, forming a novel signaling transducing functional entity, has been shown (Hasbi et al., 2011). Furthermore, for the dopamine control of motor behavior or the dopamine-mediated reward, a concomitant stimulation of D1R and D2R receptor by means of specific drugs potentiates the effect exerted by each other even if the same drugs are ineffective when administered separately (Dziedzicka-Wasylewska, 2004).
This D1/D2 synergism demonstrates an obligatory participation of both receptors, and it can be based on the activation of dimers D1-D2. Recently, the amino acid sequence from the D1R C tail involved in forming an interaction interface with D2R has been identified (Hasbi et al., 2014). Thus, it was determined that D1R receptor carboxyl tail residues 404Glu and 405Glu were critical in mediating the interaction with the D2R receptor. Furthermore, a peptide capable of disrupting the D1-D2 oligomer, switching its G-protein coupling, abolishing its signaling, and functioning as a selective antagonist in vitro and in vivo has been synthesized.
The use of this peptide corresponding to a sequence containing these two aa and the six flanking residues on either side of this site not only blocked the interaction of the D1R and D2R shown by BRET analysis and coimmunoprecipitation studies but also blocked the calcium signal activated by the oligomer, usually seen as a fingerprint of D1-D2 oligomer activation. Furthermore, the treatment of cells expressing the D1-D2 oligomer with the D1 peptide switched the preference of D1R interaction from Gq in a D1-D2 oligomer context to a preference for interaction with Gs, usually seen in a D1R homomer context. As pointed out by Hasbi (Hasbi et al., 2011; O’Dowd et al., 2012), this D1-D2 receptor oligomer-calcium signal may represent a first common biochemical bridge between the dopaminergic system-CaMKII-BDNF, synaptic plasticity, and the occurrence of drug addiction and schizophrenia.
It should be noted that such a peptide may represent a novel pharmacological tool to elucidate the functional and behavioral consequences of D1-D2 oligomer activity, and, in a broader view, it gives further support to GPCR oligomers as new targets for drugs (Agnati et al., 2011; Guidolin et al., 2015).
D1-D3 iso-RM: Ferré and collaborators have demonstrated that also D1-D3 is a tetrameric oligomer, constituted by two dimers, each formed by interacting D1R and D3R protomers coupled to Gs and Gi proteins, respectively (Guitart et al., 2014). Coactivation of both receptors causes the canonical negative interaction at the level of adenylyl cyclase signaling, a strong recruitment of β-arrestin-1, and a positive cross-talk of D1R and D3R agonists at the level of mitogen-activated protein kinase (MAPK) signaling. Furthermore, D1R or D3R antagonists counteracted β-arrestin-1 recruitment and MAPK activation induced by D3R and D1R agonists, respectively (cross-antagonism). These investigations demonstrate the functional selectivity of allosteric modulations within the D1-D3 oligomer, which can be involved with the reported behavioral synergism of D1R and D3R agonists.
Thus, the proper modulatory actions via suitable selective drugs of this oligomer could be of importance for neuropsychiatric diseases and in drug addiction.
Analogies from the information theory
As mentioned above, communication among cells takes place by means of signals capable of being recognized/decoded by the target cells. These signals activate intracellular molecular cascades to produce the appropriate cell responses. In the information theory, ‘entropy’ is a measure of the information content of an event based on the unpredictability of its outcome. It will be high when there is no a priori way to predict the result of the event.
By applying this concept to living systems, we could say that the expression of multiple iso-receptors for a given chemical signal by cells and tissues is a way to increase the entropy of that signal, i.e. its information content, since it can provide a pattern of possible results after being recognized and decoded by the target cell.
Therefore, the presence of iso-receptors and their organization within RM allow the use of a reduced number of signals, since the target cells can recognize and decode them in different ways. This means that the target cells can produce appropriate different responses notwithstanding that they have been reached by the same triggering signals.
An analogy with some electronic apparatuses could be exploited to describe what has been stated above. In particular, the use of the ‘multiplexer’ and ‘demultiplexer’ concepts (see Glossary table for a definition) to model the iso-receptors role in information handling by the cell may be suggested.
Thus, two ‘biochemical devices’ can be briefly discussed as it follows:
Multiplexer. Actually, a RM can operate as a multiplexer when an allosteric modulator can act like a ‘selector’ by modifying the allosteric interactions between the partner protomers. A known example is homocysteine, which can disrupt the A2A-D2 allosteric interactions by interacting with a check-point controlling the allosteric pathway between A2A and D2 in the RM (see Agnati et al., 2010a).
Demultiplexer. A demultiplexer is a logic circuit allowing the selection of an output (among a set of available possibilities) based not simply on the features of the input signal but also on which iso-receptor is activated and the RM to which it belongs as well as all factors mentioned in Figure 1.
Possible speculations on the functional relevance of iso-receptors
The triggering of different intracellular molecular networks by the same neurotransmitter, thanks to its binding to different iso-receptors, has a great functional relevance since it allows the following:
Redundancy, i.e. alterations in a biochemical network in some cells do not prevent the proper integrative actions of the cellular network since it may be compensated by the activation by the same transmitter of other molecular networks that may carry out similar tasks.
A more complex pattern of cellular responses since several intracellular molecular networks are activated by the same neurotransmitter and can either work in parallel (redundancy) or interact with each other (integration) or independently but in a complementary fashion (complex patterns).
Against this background, we would like to introduce the concept that the extraordinary capability of information handling by CCN in the CNS is achieved not so much by an increase in the neurotransmitter numbers but thanks to iso-receptors, RM, and plasma membrane microdomains. These factors lead to an astonishing increase in the modes for the recognition/decoding processes that control the cellular biochemical machineries.
The special role for such a phenomenon of iso-receptors can be summarized as follows:
Iso-receptors can be coupled to different intracellular molecular networks.
Iso-receptors can selectively interact with other receptors in the membrane, and these RRIs can modify either the recognition (e.g. affinity) and/or the decoding processes.
Iso-receptors can selectively interact with other membrane molecules (e.g. lipids of the LRs, integrins, or tetraspanins; Chini and Parenti, 2004; Little et al., 2004; Agnati et al., 2009c) and/or extracellular molecules (e.g. tenascin; Dityatev and Schachner, 2006) and/or intracellular molecules (e.g. β-arrestins; Reiter and Lefkowitz, 2006).
Just to give an idea of the potential possibility of integrative actions carried out by RM thanks to the iso-receptors, let us examine the possible number of assembling of iso-receptors for 5HT considering only RM1 formed by two or four iso-receptors for such neurotransmitter. This means that not all of the possible oligomers formed by 5HT with other GPCRs are taken into account (González-Maeso et al., 2008; Borroto-Escuela et al., 2010b; Łukasiewicz et al., 2010). It has been suggested that 5HT can be recognized and decoded by at least 20 different iso-receptors (Pytliak et al., 2011). This means that, at least in principle, 400 iso-receptor dimers and 160 000 iso-receptor tetramers could be obtained. If the possible different topological arrangements and the order of activation of the partner protomers are also taken into account, the number of theoretically possible RM1s hugely increases.
This, of course, is just a theoretical extrapolation, since each cell expresses only a limited number of iso-receptor types. However, it underlines the potential capabilities of RM as recognition/decoding devices.
As far as the possible increase in the multiplicity of triggering the intracytoplasmic molecular networks, a very important finding is the biochemical and functional characterizations of the D1-D2 and D1-D3 heteromers mentioned above since they could be a potential therapeutic targets for neuropsychiatric disorders (Guitart et al., 2014; Hasbi et al., 2014).
GPCRs are complex multidomain proteins in which flexible and malleable domains (such as the intracellular and extracellular loops) alternate with well-structured transmembrane domains (TM helices). Thus, a panel of bioinformatics methods has to be used to explore their structure in terms of propensity to interact (see Guidolin et al., 2010). Based on the evidence that intrinsic disorder plays an important functional role in protein-protein interaction (Hilser and Thompson, 2007), a strategy followed to identify possible interaction sites in the flexible domains was the analysis of the intrinsic disorder (Agnati et al., 2008b; Tovo-Rodrigues et al., 2014). The analysis of disordered domains, however, does not help in the prediction of putative interaction sites located in the TM helices and has to be integrated with other approaches. Thus, in the present study, the following methods were applied to predict the most probable interfaces exploited by DA-Rs to interact with other proteins:
To estimate domain boundaries and the location of disordered sequences, the DisMeta server (http://www-nmr.cabm.rutgers.edu/bioinformatics/disorder/) was used. It provides a procedure (see Huang et al., 2014) generating a consensus analysis of eight sequence-based disorder predictors, including DISEMBL (Linding et al., 2003a), DISOPRED2 (Ward et al., 2004), DISPro (Cheng et al., 2005), FoldIndex (Prilusky et al., 2005), GlobPlot2 (Linding et al., 2003b), IUPred (Dosztányi et al., 2005), RONN (Yang et al., 2005), and VL2 (Vucetic et al., 2003). For a more detailed review on disorder prediction methods, see Guidolin et al. (2011). Following a consensus approach is of particular importance in this field (Ferron et al., 2006; Agnati et al., 2008b), since it increases the reliability of disorder prediction minimizing the false-positive rates (Huang et al., 2014).
Evolutionary trace method, in combination with experimentally determined structure data of rhodopsin and β-adrenergic receptors, has been proposed by Nemoto and Toh (2005) to predict the likely hetero- and homo-oligomerization interfaces of family A GPCR. Such a procedure can be accessed through the GRIP server (http://grip.cbrc.jp/GRIP/) and appears particularly suited to identify potential interaction interfaces present in the well-structured TM domains of DA-Rs (Guidolin et al., 2011).
The results obtained from the two abovementioned strategies when applied to human DA-Rs sequence data are summarized in Table 1. Consistent with similar analyses performed on other class A GPCRs (Guidolin et al., 2011), also DA-Rs can exploit (at least theoretically) multiple interaction interfaces. Some domains, however, are predicted more often than others as a site of possible interaction interfaces. They include, for instance, TM5 and TM6 regions and ICL 3. It is of substantial interest that available experimental investigations are, in general, supporting this prediction (Ciruela et al., 2004; Guo et al., 2008; Borroto-Escuela et al., 2010a). A significant consequence of the possible availability of multiple interaction interfaces is the possibility that the assemblage of the receptor molecules to form an oligomer could occur in a number of different geometrical arrangements (see Agnati et al., 2007b, 2010d; Guidolin et al., 2011).
As far as the experimentally identified (Rashid et al., 2007) D1R-D2R heterodimer is concerned, possible structures of the receptor complex were predicted here by using methods based on the analysis of the folded protein data, such as the Rosetta-docking method (available at http://rosie.rosettacommons.org/docking/) (Lyskov et al., 2013) and the COTH method (http://zhanglab.ccmb.med.umich.edu/COTH/) (Mukherjee and Zhangm, 2011). Since no experimentally determined tertiary structures of the D1 and D2 DA-Rs are currently available, the homology model of the D1 DA-R by Y.B. Vaddavalli (PDB code: 1OZ5) and the homology model of the D2 DA-R by Platania et al. (2012) were used for this type of analysis.
Among the obtained predictions, only those consistent with the correct orientation of both partners with respect to the plane of the membrane were considered. They were then submitted to PDBePISA (Krissinel and Henrick, 2007) to obtain an estimate of their stability. Basically, two classes of possible configurations were predicted for the D1-D2 oligomer complex. A first type resulted from the interaction between transmembrane domains of the two partners, while a second one involved interactions at the level of the intracellular regions. Representative arrangements are shown in Figure 6. As illustrated, the involved interaction interfaces are consistent with those predicted by the analysis of the protein sequence data (see Table 1). Interestingly, the arrangement shown in Figure 6B, in which the interaction occurs between the C-terminal tail of the D1 receptor and the ICL 3 of the D2 receptor, also shows some consistency (see ‘Biochemical and functional aspects of RM formed by DA iso-receptors’ section) with recent experimental findings pointing to the C-terminal tail of the D1 receptor as a key interaction interface in the D1-D2 dimer (Hasbi et al., 2014). The predicted stability of such an arrangement (as measured by the ΔG (p-value) parameter provided by PDBePISA), however, was quite low. In this respect, two concerns regarding the methods applied here to predict the structure of the receptor complex have to be addressed. First, they were applied to homology models of the two proteins designed primarily to model the binding pockets of the receptors with a greater accuracy than the intracellular flexible regions. Next, the available methods to model protein assemblage (included those used in the present study) are, in general, characterized by a better performance for regions where the protein backbone conformation typically do not change much upon association. Both these aspects can contribute to a lower accuracy of the provided estimates when mainly flexible and malleable regions are involved in the interaction.
Ackers, G.K., Doyle, M.L., Myers, D., and Daugherty, M.A. (1992). Molecular code of cooperativity in haemoglobin. Science 255, 54–63.Google Scholar
Agnati, L.F. and Fuxe, K. (2000). Volume transmission as a key feature of information handling in the central nervous system possible new interpretative value of the Turing’s B-type machine. Prog. Brain Res. 125, 3–19.CrossrefGoogle Scholar
Agnati, L.F., Fuxe, K., Zini, I., Lenzi, P., and Hökfelt T. (1980). Aspects on receptor regulation and isoreceptor identification. Med. Biol. 58, 182–187.Google Scholar
Agnati, L.F., Fuxe, K., Zoli, M., Rondanini, C., and Ogren, S.O. (1982). New vistas on synaptic plasticity: the receptor mosaic hypothesis on the engram. Med. Biol. 60, 183–190.Google Scholar
Agnati, L.F., Celani, M.F., and Fuxe, K. (1983a). Cholecystokinin peptides in vitro modulate the characteristics of the striatal 3H-N-propylnorapomorphine sites. Acta Physiol. Scand. 118, 79–81.Google Scholar
Agnati, L.F., Fuxe, K., Benfenati, F., Battistini, N., Harfstrand, A., Hökfelt, T., Cavicchioli, L., Tatemoto, K., and Mutt, V. (1983b). Failure of neuropeptide Y in vitro to increase the number of α2-adrenergic binding sites in membranes of medulla oblongata of the spontaneous hypertensive rat. Acta Physiol. Scand. 119, 309–312.CrossrefGoogle Scholar
Agnati L.F., Fuxe K., Andersson K., Hökfelt T., Skirboll L., Benfenati F., Battistini N., and Calzà, L. (1983c). Possible functional meaning of the coexistence of monoamines and peptides in the same neurons. A study on the interactions between cholecystokinin-8 and dopamine in the brain. Receptors as Supramolecular Entities. G. Biggio, E., Costa, G.L. Gessa, and P.F. Spano, eds. (New York: Pergamon Press), pp. 61–70.Google Scholar
Agnati, L.F., Fuxe, K., Benfenati, F., Zini, I., and Hökfelt, T. (1983d). On the functional role of coexistence of 5-HT and substance P in bulbospinal 5-HT neurons. Substance P reduces affinity and increases density of 3H-5-HT binding sites. Acta Physiol. Scand. 117, 229–301.CrossrefGoogle Scholar
Agnati, L.F., Fuxe, K., Battistini, N., and Benfenati, F. (1984). Aging brain and dopamine receptors: abnormal regulation by CCK-8 of [3H]-spiperone labeled dopamine receptors in striatal membranes. Acta Physiol. Scand. 120, 465–467.Google Scholar
Agnati, L.F., Fuxe, K., Giardino, L., Calza, L., Zoli, M., Battistini, N., Benfenati, F., Vanderhaeghen, J.J., Guidolin, D., Ruggeri, M., et al. (1985). Evidence for cholecystokinin-dopamine receptor interactions in the central nervous system of the adult and old rat. Studies on their functional meaning. Ann. NY Acad. Sci. 448, 315–333.Google Scholar
Agnati, L.F., Ferrè, S., Lluis, C., Franco, R., and Fuxe, K. (2003). Molecular mechanisms and therapeutical implications of intramembrane receptor/receptor interactions among heptahelical receptors with examples from the striatopallidal GABA neurons. Pharmacol. Rev. 55, 509–550.CrossrefGoogle Scholar
Agnati, L.F., Tarakanov, A.O., Ferrè, S., Fuxe, K., and Guidolin, D. (2005a). Receptor-receptor interactions, receptor mosaics, and basic principles of molecular network organization: possible implications for drug development. J. Mol. Neurosci. 26, 193–208.CrossrefGoogle Scholar
Agnati, L.F., Fuxe, K., Torvinen, M., Genedani, S., Franco, R., Watson. S., Nussdorfer, G.G., Leo, G., and Guidolin, D. (2005c). New methods to evaluate colocalization of fluorophores in immunocytochemical preparations as exemplified by a study on A2 and D2 receptors in Chinese hamster ovary cells. J. Histochem. Cytochem. 53, 941–953.CrossrefGoogle Scholar
Agnati, L.F., Guidolin, D., Genedani, S., Ferré, S., Bigiani, A., Woods, A.S., and Fuxe, K. (2005d). How proteins come together in the plasma membrane and function in macromolecular assemblies: focus on receptor mosaics. J. Mol. Neurosci. 26, 133–154.CrossrefGoogle Scholar
Agnati, L.F., Leo, G., Zanardi, A., Genedani, S., Rivera, A., Fuxe, K., and Guidolin, D. (2006a). Volume transmission and wiring transmission from cellular to molecular networks: history and perspectives. Acta Physiol. 187, 329–344.Google Scholar
Agnati, L.F., Ferré, S., Genedani, S., Leo, G., Guidolin, D., Filaferro, M., Carriba, P., Casado, V., Lluis, C., Franco, R., et al. (2006b). Allosteric modulation of dopamine D2 receptors by homocysteine. J. Proteome Res. 5, 3077–3083.CrossrefGoogle Scholar
Agnati, L.F., Guidolin, D., and Fuxe, K. (2007a). The brain as a system of nested but partially overlapping networks. Heuristic relevance of the model for brain physiology and pathology. J. Neural. Transm. 114, 3–19.CrossrefGoogle Scholar
Agnati, L.F., Guidolin, D., Leo, G., Genedani, S., Arhem, P., Forni, A., Andreoli, N., and Fuxe, K. (2007b). Role of cooperativity in protein folding and protein mosaic assemblage relevance for protein conformational diseases. Curr. Protein Pept. Sci. 8, 460–470.Google Scholar
Agnati, L.F., Guidolin, D., Leo, G., and Fuxe, K. (2007c). A Boolean network modelling of receptor mosaics relevance of topology and cooperativity. J. Neural. Transm. 114, 77–92.CrossrefGoogle Scholar
Agnati, L.F., Guidolin, D., Carone, C., Dam, M., Genedani, S., and Fuxe, K. (2008a). Understanding neuronal molecular networks builds on neuronal cellular network architecture. Brain Res. Rev. 58, 379–399.CrossrefGoogle Scholar
Agnati, L.F., Leo, G., Genedani, S., Andreoli, N., Marcellino, D., Woods, A.S., Piron, L., Guidolin, D., and Fuxe, K. (2008b). Structural plasticity in G-protein coupled receptors as demonstrated by the allosteric actions of homocysteine and computer-assisted analysis of disordered domains. Brain Res. Rev. 58, 459–474.CrossrefGoogle Scholar
Agnati, L.F., Guidolin, D., Genedani, S., Leo, G., Woods, A.S., Ferré, S., Franco, R., and Fuxe, K. (2009a). Relevance of receptor topology and allosteric modulators for the integrative functions of receptor mosaics. J. Recept. Signal Transduct. Res. 28, 543–565.Google Scholar
Agnati, L.F. Fuxe, K., Woods, A.S., Genedani, S., and Guidolin, D. (2009b). Theoretical considerations on the topological organization of receptor mosaics. Curr. Protein Pept. Sci. 10, 559–569.Google Scholar
Agnati, L.F., Fuxe, K., Baluska, F., and Guidolin, D. (2009c). Implications of the ‘Energide’ concept for communication and information handling in the central nervous system. J. Neural Transm. 116, 1037–1052.CrossrefGoogle Scholar
Agnati, L.F., Guidolin, D., Leo, G., Carone, C., Genedani, S., and Fuxe, K. (2010a). Receptor-receptor interactions: a novel concept in brain integration. Progr. Neurobiol. 90, 157–175.CrossrefGoogle Scholar
Agnati, L.F., Guidolin, D., Vilardaga, J.P., Ciruela, F., and Fuxe, K. (2010b). On the expanding terminology in the GPCR field: the meaning of receptor mosaics and receptor heteromers. J. Recept. Signal Transduct. Res. 30, 287–303.Google Scholar
Agnati, L.F., Guidolin, D., Albertin, G., Trivello, E., Ciruela, F., Genedani, S., Tarakanov, A.O., and Fuxe, K. (2010d). An integrated view on the role of receptor mosaics at perisynaptic level: focus on adenosine A2A, dopamine D2, cannabinoid CB1, and metabotropic glutamate mGlu5 receptors. J. Rec. Signal. Transduct. 30, 355–369.CrossrefGoogle Scholar
Agnati, L.F., Guidolin, D., Leo, G., Guescini, M., Pizzi, M., Stocchi, V., Spano, P.F., Ghidoni, R., Ciruela, F., Genedani, S., et al. (2011). Possible new targets for GPCR modulation: allosteric interactions, plasma membrane domains, intercellular transfer and epigenetic mechanisms. J. Recept. Signal Transduct. 3, 315–331.Google Scholar
Agnati, L.F., Guidolin, D., Woods, A.S., Ciruela, F., Carone, C., Vallelunga, A., Borroto-Escuela, D.O., Genedani, S., and Fuxe, K. (2013). A new interpretative paradigm for conformational protein diseases. Curr. Protein Pept. Sci. 14, 141–160.Google Scholar
Agnati, L.F., Guidolin, D., Marcoli, M., Genedani, S., Borroto-Escuela, D., Maura, G., and Fuxe, K. (2014a). “Neuro-semeiotics” and “free-energy minimization” suggest a unified perspective for integrative brain actions: focus on receptor heteromers and roamer type of volume transmission. Curr. Protein Pept. Sci. 15, 703–718.Google Scholar
Ahlquist, R.P. (1948). A study of the adrenotropic receptors. Am. J. Physiol. 153, 586–600.Google Scholar
Alexander, S.P.H., Benson, H.E., Faccenda, E., Pawson, A.J., Sharman, J.L., Spedding, M., Peters, J.A., Harmar, A.J., and CGTP Collaborators. (2013). The concise guide to pharmacology 2013/14: G protein-coupled receptors. Br. J. Pharmacol. 170, 1459–1581.Google Scholar
Anonymous. (1982). A randomized trial of propranolol in patients with acute myocardial infarction. I. Mortality results. J. Am. Med. Assoc. 247, 1707–1714.Google Scholar
Azdad, K., Gall, D., Woods, A.S., Ledent, C., Ferrè, S., and Schiffmann, S.N. (2009). Dopamine D2 and adenosine A2A receptors regulate NMDA mediated excitation in accumbens neurons through A2A-D2 receptor heteromerization. Neuropsychopharmacology 34, 972–986.CrossrefGoogle Scholar
Bhushan, R.G., Sharma, S.K., Xie, Z., Daniels, D.J., and Portoghese, P.S. (2004). A bivalent ligand (KDN-21) reveals spinal δ and κ opioid receptors are organized as heterodimers that give rise to δ(1) and κ(2) phenotypes. Selective targeting of δ-κ heterodimers. J. Med. Chem. 47, 2969–2972.Google Scholar
Borroto-Escuela, D.O., Romero-Fernandez, W., Tarakanov, A.O., Gómez-Soler, M., Corrales, F., Marcellino, D., Narvaez, M., Frankowska, M., Flajolet, M., Heintz, N., et al. (2010a). Characterization of the A2AR-D2R interface: focus on the role of the C-terminal tail and the transmembrane helices. Biochem. Biophys. Res. Commun. 26, 801–807.CrossrefGoogle Scholar
Borroto-Escuela, D.O., Romero-Fernandez, W., Tarakanov, A.O., Marcellino, D., Ciruela, F., Agnati, L.F., and Fuxe, K. (2010b). Dopamine D2 and 5-hydroxytryptamine 5-HT2A receptors assemble into functionally interacting heteromers. Biochem. Biophys. Res. Commun. 401, 605–610.Google Scholar
Borroto-Escuela, D.O., Tarakanov, A.O., Guidolin, D., Ciruela, F., Agnati, L.F., and Fuxe, K. (2011a). Moonlighting characteristics of G protein-coupled receptors: focus on receptor heteromers and relevance for neurodegeneration. IUBMB Life 63, 463–472.CrossrefGoogle Scholar
Borroto-Escuela, D.O., Van Craenenbroeck, K., Romero-Fernandez, W., Guidolin, D., Woods, A.S., Rivera, A., Haegeman, G., Agnati, L.F., Tarakanov, A.O., and Fuxe, K. (2011b). Dopamine D2 and D4 receptor heteromerization and its allosteric receptor-receptor interactions. Biochem. Biophys. Res. Commun. 404, 928–934.Google Scholar
Borroto-Escuela, D.O., Flajolet, M., Agnati, L.F., Greengard, P., and Fuxe, K. (2013a). Bioluminescence resonance energy transfer methods to study G protein-coupled receptor-receptor tyrosine kinase heteroreceptor complexes. Methods Cell Biol. 117, 141–164.CrossrefGoogle Scholar
Borroto-Escuela, D.O., Romero-Fernandez, W., Garriga, P., Ciruela, F., Narvaez, M., Tarakanov, A.O., Palkovits, M., Agnati, L.F., and Fuxe, K. (2013b). G protein-coupled receptor heterodimerization in the brain. Methods Enzymol. 521, 281–294.Google Scholar
Borroto-Escuela, D.O., Brito, I., Romero-Fernandez, W., Di Palma, M., Oflijan, J., Skieterska, K., Duchou, J., Van Craenenbroeck, K., Suárez-Boomgaard, D., Rivera, A., et al. (2014). The G protein-coupled receptor heterodimer network (GPCR-HetNet) and its hub components. Int. J. Mol. Sci. 15, 8570–8590.CrossrefGoogle Scholar
Bouvier, M. and Hébert, T.E. (2014). CrossTalk opposing view: weighing the evidence for class A GPCR dimers, the jury is still out. J. Physiol. 592, 2443–2445.Google Scholar
Bulenger, S., Marullo, S., and Bouvier, M. (2005). Emerging role of homo- and heterodimerization in G-protein-coupled receptor biosynthesis and maturation. Trends Pharmacol. Sci. 26, 131–137.CrossrefGoogle Scholar
Chaim, B.Y., Bochnik, S., Parnas, I., and Parnas, H. (2013). Voltage affects the dissociation rate constant of the m2 muscarinic receptor. PLoS 8, e74354.Google Scholar
Changeux, J.P. and Edelstein, S.J. (2005). Allosteric mechanisms of signal transduction. Science 308, 1424–1428.Google Scholar
Chun, L.S., Free, R.B., Doyle, T.B., Huang, X.P., Rankin, M.L., and Sibley, D.R. (2013). D1-D2 dopamine receptor synergy promotes calcium signaling via multiple mechanisms. Mol. Pharmacol. 84, 190–200.CrossrefGoogle Scholar
Ciruela, F., Burgueno, J., Casado, V., Canals, M., Marcelino, D., Goldberg, S.R., Bader, M., Fuxe, K., Agnati, L.F., Lluis, C., et al. (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. Anal. Chem. 76, 5354–5363.CrossrefGoogle Scholar
Ciruela, F., Canela, L., Burgueno, J., Soriguera, A., Cabello, N., Canela, E.I., Casado, V., Cortes, A., Mallol, J., Woods, A.S., et al. (2005). Heptaspanning membrane receptors and cytoskeletal/scaffolding proteins: focus on adenosine, dopamine, and metabotropic glutamate receptor function. J. Mol. Neurosci. 26, 277–292.CrossrefGoogle Scholar
Cooper, D.M.F. and Tabbasum, V.G. (2014). Adenylate cyclase-centred microdomains. Biochem. J. 462, 199–213.Google Scholar
Czysz, A.H., Schappi, J.M., and Rasenick, M.M. (2015). Lateral diffusion of Gαs in the plasma membrane is decreased after chronic but not acute antidepressant treatment: role of lipid raft and non-raft membrane microdomains. Neuropsychopharmacology 40, 766–773.CrossrefGoogle Scholar
Daniels, D.J., Lenard, N.R., Etienne, C.L., Law, P.Y., Roerig, S.C., and Portoghese, P.S. (2005). Opioid-induced tolerance and dependence in mice is modulated by the distance between pharmacophores in a bivalent ligand series. Proc. Natl. Acad. Sci. USA 102, 19208–19213.CrossrefGoogle Scholar
Dean, M.K., Higgs, C., Smith, R.E., Bywater, R.P., Snell, C.R., Scott, P.D., Upton, G.J., Howe, T.J., and Reynolds, C.A. (2001). Dimerization of G-protein-coupled receptors. J. Med. Chem. 44, 4595–4614.CrossrefGoogle Scholar
Dosztányi, Z., Csizmók, V., Tompa, P., and Simon, I. (2005). The pairwise energy content estimated from amino acid composition discriminates between folded and intrinsically unstructured proteins. J. Mol. Biol. 347, 827–839.Google Scholar
Dupre, D.J. and Hebert, T.E. (2006). Biosynthesis and trafficking of seven transmembrane receptor signalling complexes. Cellular Signal. 18, 1549–1559.Google Scholar
Dziedzicka-Wasylewska, M. (2004). Brain dopamine receptors – research perspectives and potential sites of regulation. Pol. J. Pharmacol. 56, 659–671.Google Scholar
Ferré, S., Baler, R., Bouvier, M., Caron, M.G., Devi, L.A., Durroux, T., Fuxe, K., George, S.R., Javitch, J.A., Lohse, M.J., et al. (2009). Building a new conceptual framework for receptor heteromers. Nat. Chem. Biol. 5, 131–134.CrossrefGoogle Scholar
Ferré, S., Woods, A.S., Navarro, G., Aymerich, M., Lluís, C., and Franco, R. (2010). Calcium-mediated modulation of the quaternary structure and function of adenosine A2A-dopamine D2 receptor heteromers. Curr. Opin. Pharmacol. 10, 67–72.CrossrefGoogle Scholar
Ferré, S., Casadó, V., Devi, L.A., Filizola, M., Jockers, R., Lohse, M.J., Milligan, G., Pin, J.P., and Guitart. X. (2014). G protein-coupled receptor oligomerization revisited: functional and pharmacological perspectives. Pharmacol. Rev. 66, 413–434.CrossrefGoogle Scholar
Fiorentini, C., Busi, C., Gorruso, E., Gotti, C., Spano, P., and Missale, C. (2008). Reciprocal regulation of dopamine D1 and D3 receptor function and trafficking by heterodimerization. Mol. Pharmacol. 74, 59–69.CrossrefGoogle Scholar
Fotiadis, D., Liang, Y., Filipek, S., Saperstein, D.A., Engel, A., and Palczewski, K. (2003). Atomic force microscopy: rhodopsin dimers in native disc membranes. Nature 421, 127–128.Google Scholar
Franco, R., Ferré, S., Agnati, L.F., Torvinen, M., Gines, S., Hillion, J., Casado, V., Lledo, P.M., Zoli, M., Lluis, C., et al. (2000). Evidence for adenosine/dopamine receptor interactions: indications for heteromerization. Neuropsychopharmacology 23, S50–S59.CrossrefGoogle Scholar
Franco, R., Lluis, C., Canela, E.I., Mallol, J., Agnati, L.F., Casadó, V., Ciruela, F., Ferré, S., and Fuxe, K. (2007). Receptor-receptor interactions involving adenosine A1 or dopamine D1 receptors and accessory proteins. J. Neural. Transm. 114, 93–104.CrossrefGoogle Scholar
Frauenfelder, H., Sligar, S.G., and Wolynes, P.G. (1991). The energy landscapes and motions of proteins. Science 254, 1598–1603.Google Scholar
Fuxe, K., Agnati, L.F., Benfenati, F., Cimmino, M., Algeri, S., Hökfelt, T., and Mutt, V. (1981). Modulation by cholecystokinins of 3H-spiroperidol binding in rat striatum: evidence for increased affinity and reduction in the number of binding sites. Acta Physiol. Scand. 113, 567–569.CrossrefGoogle Scholar
Fuxe, K., Agnati, L.F., Härfstrand, A., Lundberg, J., Hökfelt, T., Calza, L., Kimmel, J., and Bernardi, P. (1982). Intracisternal administration of avian pancreatic polypeptide lowers respiration rate and enhances the clonidine induced reduction of respiration rate in α-chloralose anesthetized rats: possible interactions with an α 2-adrenergic receptor. Acta Physiol. Scand. 115, 381–384.CrossrefGoogle Scholar
Fuxe, K., Agnati, L.F., Benfenati, F., Celani, M., Zini, I., Zoli, M., and Mutt, V. (1983a). Evidence for the existence of receptor-receptor interactions in the central nervous system. Studies on the regulation of monoamine receptors by neuropeptides. J. Neural. Transm. 18, 165–179.Google Scholar
Fuxe, K., Agnati, L.F., Harfstrand, A., Zini, I., Tatemoto, K., Pich, E.M., Hökfelt, T., Mutt, V., and Terenius, L. (1983b). Central administration of neuropeptide Y induces hypotension bradypnea and EEG synchronization in the rat. Acta Physiol. Scand. 118, 189–192.CrossrefGoogle Scholar
Fuxe, K., Agnati, L.F., Harfstrand, A., Martire, M., Goldstein, M., Grimaldi, R., Bernardi, P., Zini, I., Tatemoto, K., and Mutt, V. (1984). Evidence for a modulation by neuropeptide Y of the α-2 adrenergic transmission line in central adrenaline synapses. New possibilities for treatment of hypertensive disorders. Clin. Exp. Hypertens Part A 6, 1951–1956.Google Scholar
Fuxe, K., Agnati, L.F., Harfstrand, A., Janson, A.M., Neumeyer, A., Andersson, K., Ruggeri, M., Zoli, M., and Goldstein, M. (1986). Morphofunctional studies on the neuropeptide Y/adrenaline costoring terminal systems in the dorsal cardiovascular region of the medulla oblongata. Focus on receptor-receptor interactions in cotransmission. Prog. Brain Res. 68, 303–320.CrossrefGoogle Scholar
Fuxe, K. and Agnati, L.F. (1987a). Receptor-Receptor Interactions. A New Intramembrane Integrative Mechanism. K. Fuxe and L.F. Agnati, eds. (London, UK: Macmillan), pp. 14–18.Google Scholar
Fuxe, K. and Agnati, L.F. (1987b). Opening Address. Receptor-Receptor Interactions. A New Intramembrane Integrative Mechanism. K. Fuxe and L.F. Agnati, eds. (London, UK: MacMillan), pp. 14–18.Google Scholar
Fuxe, K., Ferré, S., Zoli, M., and Agnati, L.F. (1998). Integrated events in central dopamine transmission as analyzed at multiple levels. Evidence for intramembrane adenosine A2A/dopamine D2 and adenosine A1/dopamine D1 receptor interactions in the basal ganglia. Brain Res. Brain Res. Rev. 26, 258–273.CrossrefGoogle Scholar
Fuxe, K., Agnati, L.F., Jacobsen, K., Hillion, J., Canals, M., Torvinen, M., Tinner-Staines, B., Staines, W., Rosin, D., Terasmaa, A., et al. (2003). Receptor heteromerization in adenosine A2A receptor signaling: relevance for striatal function and Parkinson’s disease. Neurology 61, S19–S23.CrossrefGoogle Scholar
Fuxe, K., Ferrè, S., Canals, M., Torvinen, M., Terasmaa, A., Marcellino, D., Goldberg, S.R., Staines, W., Jacobsen, K.X., Lluis, C., et al. (2005). Adenosine A2A and dopamine D2 heteromeric receptor complexes and their function. J. Mol. Neurosci. 26, 209–220.CrossrefGoogle Scholar
Fuxe, K., Ferrè, S., Genedani, S., Franco, R., and Agnati, L.F. (2007a). Adenosine receptor-dopamine receptor interactions in the basal ganglia and their relevance for brain function. Physiol. Behav. 92, 210–217.CrossrefGoogle Scholar
Fuxe, K., Canals, M., Torvinen, M., Marcellino, D., Terasmaa, A., Genedani, S., Leo, G., Guidolin, D., Diaz-Cabiale, Z., Rivera, A., et al. (2007b). Intramembrane receptor-receptor interactions: a novel principle in molecular medicine. J. Neural. Transm. 114, 49–75.CrossrefGoogle Scholar
Fuxe, K., Marcellino, D., Guidolin, D., Woods, A.S., and Agnati, L.F. (2009a). Brain receptor mosaics and their intramembrane receptor-receptor interactions: molecular integration in transmission and novel targets for drug development. J. Acupunct. Meridian. Stud. 2, 1–25.CrossrefGoogle Scholar
Fuxe, K., Marcellino, D., Woods, A.S., Leo, G., Antonelli, T., Ferraro, L., Tanganelli, S., and Agnati, L.F. (2009b). Integrated signaling in heterodimers and receptor mosaics of different types of GPCRs of the forebrain: relevance for schizophrenia. J. Neural. Transm. 116, 923–939.CrossrefGoogle Scholar
Fuxe, K., Borroto-Escuela, D.O., Marcellino, D., Romero-Fernandez, W., Frankowska, M., Guidolin, D., Filip, M., Ferraro, L., Woods, A.S., Tarakanov, A., et al. (2012). GPCR heteromers and their allosteric receptor-receptor interactions. Curr. Med. Chem. 19, 356–363.CrossrefGoogle Scholar
Fuxe, K., Borroto-Escuela, D.O., Romero-Fernandez, W., Palkovits, M., Tarakanov, A.O., Ciruela, F., and Agnati, L.F. (2014). Moonlighting proteins and protein-protein interactions as neurotherapeutic targets in the G protein-coupled receptor field. Neuropsychopharmacology 39, 131–155.CrossrefGoogle Scholar
Fuxe, K., Guidolin, D., Agnati, L.F., and Borroto-Escuela, D.O. (2015). Dopamine heteroreceptor complexes as therapeutic targets in Parkinson’s disease. Expert. Opin. Ther. Targets 19, 377–398.CrossrefGoogle Scholar
Genedani, S., Guidolin, D., Leo, G., Filaferro, M., Torvinen, M., Woods, A.S., Fuxe, K., Ferré, S., and Agnati, L.F. (2005). Computer-assisted image analysis of caveolin-1 involvement in the internalization process of adenosine A2A-dopamine D2 receptor heterodimers. J. Mol. Neurosci. 26, 177–184.CrossrefGoogle Scholar
Genedani, S., Carone, C., Guidolin, D., Filaferro, M., Marcellino, D., Fuxe, K., and Agnati, L.F. (2010). Differential sensitivity of A2A and especially D2 receptor trafficking to cocaine compared with lipid rafts in cotransfected CHO cell lines. Novel actions of cocaine independent of the DA transporter. J. Mol. Neurosci. 41, 347–357.CrossrefGoogle Scholar
Gonzàles, S., Rangel-Barajas, C., Peper, M., Lorenzo, R., Moreno, E., Ciruela, F., Borycz, J., Ortiz, J., Lluis, C., Franco, R., et al. (2012). Dopamine D4 receptor, but not the ADHD-associated D4.7 variant, forms functional heteromers with the dopamine D2S receptor in the brain. Mol. Psychiatry 17, 650–662.CrossrefGoogle Scholar
González-Maeso, J., Ang, R.L., Yuen, T., Chan, P., Weisstaub, N.V., Lopez- Gimenez, J.F., Zhou, M., Okawa, Y., Callado, L.F., Milligan, G., et al. (2008). Identification of a serotonin/glutamate receptor complex implicated in psychosis. Nature 452, 93–97.Google Scholar
Guidolin, D., Fuxe, K., Neri, G., Nussdorfer, G.G., and Agnati, L.F. (2007). On the role of receptor-receptor interactions and volume transmission in learning and memory. Brain Res. Rev. 55, 119–133.CrossrefGoogle Scholar
Guidolin, D., Ciruela, F., Genedani, S., Guescini, M., Tortorella, C., Albertin, G., Fuxe, K., and Agnati, L.F. (2010). Bioinformatics and mathematical modelling in the study of receptor-receptor interactions and receptor oligomerization: focus on adenosine receptors. Biochim. Biophys. Acta 1808, 1267–1283.Google Scholar
Guidolin, D., Ciruela, F., Genedani, S., Guescini, M., Tortorella, C., Albertin, G., Fuxe, K., and Agnati, L.F. (2011). Bioinformatics and mathematical modelling in the study of receptor-receptor interactions and receptor oligomerization: Focus on adenosine receptors. Biochim. Biophys. Acta Biomembr. 1808, 1267–1283.Google Scholar
Guidolin, D., Agnati, L.F., Marcoli, M., Borroto-Escuela, D.O., and Fuxe, K. (2015). G-protein-coupled receptor type A heteromers as an emerging therapeutic target. Expert Opin. Ther. Targets 19, 265–283.CrossrefGoogle Scholar
Guitart, X., Navarro, G., Moreno, E., Yano, H., Cai, N.S., Sánchez-Soto, M., Kumar-Barodia, S., Naidu, Y.T., Mallol, J., Cortés, A., et al. (2014). Functional selectivity of allosteric interactions within G protein-coupled receptor oligomers: the dopamine D1–D3 receptor heterotetramer. Mol. Pharmacol. 86, 417–429.CrossrefGoogle Scholar
Guo, W., Urizar, E., Kralikova, M., Mobarec, J.C., Shi, L., Filizola, M., and Javitch, J.A. (2008). Dopamine D2 receptors form higher order oligomers at physiological expression levels. Eur. Mol. Biol. Organ. J. 27, 2293–2304.CrossrefGoogle Scholar
Hasbi, A., Perreault, M.L., Shen, M.Y., Zhang, L., To, R., Fan, T., Nguyen, T., Ji, X., O’Dowd, B.F., and George, S.R. (2014). A peptide targeting an interaction interface disrupts the dopamine D1-D2 receptor heteromer to block signaling and function in vitro and in vivo: effective selective antagonism. FASEB J. 28, 4806–4820.CrossrefGoogle Scholar
Hebebrand, J., Friedl, W., and Propping, P. (1988). The concept of isoreceptors: application to the nicotinic acetylcholine receptor and the γ-aminobutyric acidA/benzodiazepine receptor complex. J. Neural. Transm. 71, 1–9.CrossrefGoogle Scholar
Hilser, V.J., Dowdy, D., Oas, T.G., and Freire, E. (1998). The structural distribution of cooperative interactions in proteins: analysis of the native state ensemble. Proc. Natl. Acad. Sci. USA 95, 9903–9908.CrossrefGoogle Scholar
Hökfelt, T., Lundberg, J.M., Tatemoto, K., Mutt, V., Terenius, L., Polak, J., Bloom, S., Sasek, C., Elde, R., and Goldstein, M. (1983). Neuropeptide Y (NPY)- and FMRFamide neuropeptide-like immunoreactivities in catecholamine neurons of the rat medulla oblongata. Acta Phys. Scand. 117, 315–318.CrossrefGoogle Scholar
Hökfelt, T., Holets, V.R., Staines, W., Meister, B., Melander, T., Schalling, M., Schultzberg, M., Freedman, J., Björklund, H., Olson, L., et al. (1986). Coexistence of neuronal messengers–an overview. Progr. Brain Res. 68, 33–70.CrossrefGoogle Scholar
Hökfelt, T., Millhorn, D., Seroogy, K., Tsuruo, Y., Ceccatelli, S., Lindh, B., Meister, B., Melander, T., Schalling, M., Bartfai, T., et al. (1987). Coexistence of peptides with classical neurotransmitters. Experientia 43, 768–780.CrossrefGoogle Scholar
Huang, Y.J., Acton, T.B., and Montelione, G.T. (2014). DisMeta-A meta server for construct design and optimization. Methods Mol. Biol. 1091, 3–16.Google Scholar
Ji, T.H., Grossmann, M., and Ji, I. (1998). G protein-coupled receptors. I. Diversity of receptor-ligand interactions. J. Biol. Chem. 273, 17299–17302.Google Scholar
Kenakin, T. (2010). G protein coupled receptors as allosteric proteins and the role of allosteric modulators. J. Recept. Signal Transduct Res. 30, 313–321.Google Scholar
Kenakin, T. and Miller, L.J. (2010). Seven transmembrane receptors as shapeshifting proteins: the impact of allosteric modulation and functional selectivity on new drug discovery. Pharmacol. Rev. 62, 265–304.CrossrefGoogle Scholar
Kenakin, T., Agnati, L.F., Caron, M., Fredholm, B., Guidolin, D., Kobilka, B., Lefkowitz, R.W., Lohse, M., Woods, A.S., and Fuxe, K. (2010). International Workshop at the Nobel Forum, Karolinska Institutet on G protein-coupled receptors: finding the words to describe monomers, oligomers, and their molecular mechanisms and defining their meaning. Can a consensus be reached? J. Recept. Signal Transduct. Res. 30, 284–286.Google Scholar
Krissinel, E. and Henrick, K. (2007). Inference of macromolecular assemblies from crystalline state. J. Mol. Biol. 372, 774–797.Google Scholar
LaHoste, G.J., Swanson, J.M., Wigal, S.B., Glabe, C., Wigal, T., King, N., and Kennedy, J.L. (1996). Dopamine D4 receptor gene polymorphism is associated with attention deficit hyperactivity disorder. Mol. Psychiatry 1, 121–124.Google Scholar
Lambert, N.A. and Javitch, J.A. (2014). CrossTalk opposing view: weighing the evidence for class A GPCR dimers, the jury is still out. J. Physiol. 592, 2443–2445.Google Scholar
Lee, S.P., So, C.H., Rashid, A.J., Varghese, G., Cheng, R., Lanca, A.J., O’Dowd, B.F., and George, S.R. (2004). Dopamine D1 and D2 receptor coactivation generates a novel phospholipase C-mediated calcium signal. J. Biol. Chem. 279, 35671–35678.Google Scholar
Lefkowitz, R.J. and Shenoym S.K. (2005). Transduction of receptor signals by β-arrestins. Science 308, 512–517.Google Scholar
Levant, B. (1997). The D3 dopamine receptor: neurobiology and potential clinical relevance. Pharmacol. Rev. 3, 231–252.Google Scholar
Linding, R., Jensen, L.J., Diella, F., Bork, P., Gibson, T.J., and Russell, R.B. (2003a). Protein disorder prediction: implications for structural proteomics. Structure 11, 1453–1459.CrossrefGoogle Scholar
Little, K.D., Hemler, M.E., and Stipp, C.S. (2004). Dynamic regulation of a GPCR-tetraspanin-G protein complex on intact cells: central role of CD81 in facilitating GPR56-Gα q/11 association. Mol. Biol. Cell. 15, 2375–2387.CrossrefGoogle Scholar
Lohse, M.J., Benovic, J.L., Codina, J., Caron, M.G., and Lefkowitz, R.J. (1990). β-Arrestin: a protein that regulates β-adrenergic receptor function. Science 248, 547–1550.Google Scholar
Łukasiewicz, S., Polit, A., Kędracka-Krok, S., Wędzony, K., Maćkowiak, M., and Dziedzicka-Wasylewska, M. (2010). Hetero-dimerization of serotonin 5-HT2A and dopamine D2 receptors. Biochim. Biophys. Acta Mol. Cell. Res. 1803, 1347–1358.Google Scholar
Lyskov, S., Chou, F.C., Conchúir, S.Ó., Der, B.S., Drew, K., Kuroda, D., Xu, J., Weitzner, B.D., Renfrew, P.D., Sripakdeevong, P., et al. (2013). Serverification of molecular modeling applications: the Rosetta Online Server That Includes Everyone (ROSIE). PLoS One 8, e63906.Google Scholar
Magalhaes, A.C., Dunn, H., and Ferguson, S.S.G. (2012). Regulation of GPCR activity, trafficking and localization by GPCR-interacting proteins. Br. J. Pharmacol. 165, 1717–1736.Google Scholar
Marcellino, D., Ferrè, S., Casado, V., Corte, A., Le Foll, B., Mazzola, C., Drago, F., Saur, O., Stark, H., Soriano, A., et al. (2008). Identification of dopamine D1-D3 receptor heteromers. Indications for a role of synergistic D1-D3 receptor interactions in the striatum. J. Biol. Chem. 283, 26016–26025.Google Scholar
Maurice, P., Guillaume, J.L., Benleulmi-Chaachoua, A., Daulat, A.M., Kamal, M., and Jockers, R. (2011). 11-GPCR-interacting proteins, major players of GPCR function. Adv. Pharmacol. 62, 349–380.Google Scholar
Missale, C., Nash, S.R., Robinson, S.W., Jaber, M., and Caron, M.G. (1998). Dopamine receptors: from structure to function. Physiol. Rev. 78, 189–225.Google Scholar
Monod, J. (1979). Chance and Necessity: An Essay on the Natural Philosophy of Modern Biology (Glasgow, UK: William Collins Sons & Co. Ltd.).Google Scholar
Motlagh, H.N., Wrabl, J.O., Li, J., and Hilser, V.J. (2014). The ensemble nature of allostery. Nature 508, 331–339.Google Scholar
Navarro, G., Aymerich, M.S., Marcellino, D., Cortés, A., Casadó, V., Mallol, J., Canela, E.I., Agnati, L.F., Woods, A.S., Fuxe, K., et al. (2009). Interactions between calmodulin, adenosine A2A, and dopamine D2 receptors. J. Biol. Chem. 284, 28058–28068.CrossrefGoogle Scholar
Navarro, G., Ferré, S., Cordomi, A., Moreno, E., Mallol, J., Casadó, V., Cortés, A., Hoffmann, H., Ortiz, J., Canela, E.I., et al. (2010). Interactions between intracellular domains as key determinants of the quaternary structure and function of receptor heteromers. J. Biol. Chem. 285, 27346–27359.CrossrefGoogle Scholar
Nimchinsky, E.A., Hof, P.R., Janssen, W.G.M., Morrison, J.H., and Schmaussi, C. (1997). Expression of dopamine D3 receptor dimers and tetramers in brain and in transfected cells. J. Biol. Chem. 272, 29229–29237.Google Scholar
Nussinov, R. and Tsai, C.J. (2013). Allostery in disease and in drug discovery. Cell 153, 293–305.Google Scholar
O’Dowd, B.F., Ji, X., Nguyen, T., and George, S.R. (2012). Two amino acids in each of D1 and D2 dopamine receptor cytoplasmic regions are involved in D1-D2 heteromer formation. Biochem. Biophys. Res. Commun. 417, 23–28.Google Scholar
Pei, L., Li, S., Wang, M., Diwan, M., Anisman, H., Fletcher, P.J., Nobrega, J.N., and Liu, F. (2010). Uncoupling the dopamine D1-D2 receptor complex exerts antidepressant-like effects. Nat. Med. 16, 1393–1395.CrossrefGoogle Scholar
Platania, C.B.M., Salomone, S., Leggio, G.M., Drago, F., and Bucolo, C. (2012). Homology modeling of dopamine D2 and D3 receptors: molecular dynamics refinement and docking evaluation. PLoS One 7, e44316.Google Scholar
Prilusky, J., Felder, C.E., Zeev-Ben-Mordehai, T., Rydberg, E.H., Man, O., Beckmann, J.S., Silman, I., and Sussman, J.L. (2005). FoldIndex: a simple tool to predict whether a given protein sequence is intrinsically unfolded. Bioinformatics 21, 3435–3458.CrossrefGoogle Scholar
Pytliak, M., Vargová, V., Mechírová, V., and Felšöci, M. (2011). Serotonin receptors – from molecular biology to clinical applications. Physiol. Res. 60, 15–25.Google Scholar
Rankin, M.L., Hazelwood, L.A., Free, R.B., Namkung, Y., Rex, E.B., Roof, R.A., and Sibley, D.R. (2010). Molecular pharmacology of the dopamine receptors, in Dopamine Handbook. L.L. Iversen, S.B. Dunnett, S.D. Iversen, and A. Bjorklund, eds. (NY, USA: Oxford University Press), pp. 63–87.Google Scholar
Rashid, A.J., So, C.H., Kong, M.M.C., Furtak, T., El-Ghundi, M., Cheng, R., O’Dowd, B.F., and George, S.R. (2007). D1-D2 dopamine receptor heterooligomers with unique pharmacology are coupled to rapid activation of Gq/11 in the striatum. Proc. Natl. Acad. Sci. USA 104, 654–659.Google Scholar
Reiter, E. and Lefkowitz, R.J. (2006). GRKs and b-arrestins: roles in receptor silencing, trafficking and signaling. Trends Endocrinol. Metab. 17, 159–165.Google Scholar
Rocheville, M., Lange, D.C., Kumar, U., Patel, S.C., Patel, R.C., and Patel, Y.C. (2000). Receptors for dopamine and somatostatin: formation of hetero-oligomers with enhanced functional activity. Science 288, 154–157.Google Scholar
Sahlholm, K., Barchad-Avitzur, O., Marcellino, D., Gómez-Soler, M., Fuxe, K., Ciruela, F., and Arhem, P. (2011). Agonist-specific voltage sensitivity at the dopamine D2S receptor – molecular determinants and relevance to therapeutic ligands. Neuropharmacology 61, 937–949.CrossrefGoogle Scholar
Scarselli, M., Novi, F., Schallmach, E., Lin, R., Baragli, A., Colzi, A., Griffon, N., Corsini, G.U., Sokoloff, P., Levenson, R., et al. (2001). D2/D3 dopamine receptor heterodimers exhibit unique functional properties. J. Biol. Chem. 276, 30308–30314.CrossrefGoogle Scholar
Shenoy, S.K. and Lefkowitz, R.J. (2011). β-arrestin-mediated receptor trafficking and signal transduction. TiPS. 32, 521–533.Google Scholar
Shpakov, A.O. (2011). Signal protein-derived peptides as functional probes and regulators of intracellular signaling. J. Amino Acids 2011, 656051.Google Scholar
Skieterska, K., Duchou, J., Lintermans, B., and Van Craenenbroeck, K. (2013). Detection of G protein-coupled receptor (GPCR) dimerization by coimmunoprecipitation. Methods Cell Biol. 117, 323–340.CrossrefGoogle Scholar
So, C.H., Verma, V., Alijaniaram, M., Cheng, R., Rashid, A.J., O’Dowd, B.F., and George, S.R. (2009). Calcium signaling by dopamine D5 receptor and D5-D2 receptor heterooligomers occurs by a mechanism distinct from that for dopamine D1-D2 receptor hetero-oligomers. Mol. Pharmacol. 75, 843–854.CrossrefGoogle Scholar
Sokoloff, P., Diaz, J., Le Foll, B., Guillin, O., Leriche, L., Bezard, E., and Gross, C. (2006). The dopamine D3 receptor: a therapeutic target for the treatment of neuropsychiatric disorders. CNS Neurol. Disord. Drug Targets 5, 25–43.Google Scholar
Suzuki, M., Hurd, Y.L., Sokoloff, P., Schwartz, J.C., and Sedvall, G. (1998). D3 dopamine receptor mRNA is widely expressed in the human brain. Brain Res. 779, 58–74.Google Scholar
Tovo-Rodrigues, L., Roux, A., Hutz, M.H., Rohde, L.A., and Woods, A.S. (2014). Functional characterization of G-protein-coupled receptors: a bioinformatics approach. Neuroscience 277, 764–779.Google Scholar
Trifilieff, P., Rives, M.L., Urizar, E., Piskorowski, R.A., Vishwasrao, H.D., Castrillon, J., Schmauss, C., Slättman, M., Gullberg, M., and Javitch, J.A. (2011). Detection of antigen interactions ex vivo by proximity ligation assay: endogenous dopamine D2-adenosine A2A receptor complexes in the striatum. Biotechniques 51, 111–118.Google Scholar
Venkatakrishnan, A.J., Deupi, X., Lebon, G., Tate, C.G., Schertler, G.F., and Babu, M.M. (2013). Molecular signatures of G-protein-coupled receptors. Nature 494, 185–194.Google Scholar
Vizi, E.S. (2000). Role of high-affinity receptors and membrane transporters in nonsynaptic communication and drug action in the central nervous system. Pharmacol. Rev. 52, 63–89.Google Scholar
von Zastrow, M. and Kobilka, B.K. (1994). Antagonist-dependent and -independent steps in the mechanism of adrenergic receptor internalization. J. Biol. Chem. 269, 18448–18452.Google Scholar
Wang, E., Dingm, Y.C., Flodman, P., Kidd, J.R., Kidd, K.K., Grady, D.L., Ryder, O.A., Spence, M.A., Swanson, J.M., and. Moyzis, R.K. (2004). The genetic architecture of selection at the human dopamine receptor D4 (DRD4) gene locus. Am. J. Hum. Genet. 74, 931–944.CrossrefGoogle Scholar
Ward, J.J., Sodhi, J.S., McGuffin, L.J., Buxton, B.F., and Jones, D.T. (2004). Prediction and functional analysis of native disorder in proteins from the three kingdoms of life. J. Mol. Biol. 337, 635–645.Google Scholar
Woods, A.S., Ciruela, F., Fuxe, K., Agnati, L.F., Lluis, C., Franco, R., and Ferré, S. (2005). Role of electrostatic interaction in receptor-receptor heteromerization. J. Mol. Neurosci. 26, 125–132.CrossrefGoogle Scholar
Woods, A.S. and Jackson, S.N. (2013). How adenylate cyclase choreographs the pas de deux of the receptors heteromerization dance. Neuroscience 238, 335–344.Google Scholar
Wu, H., Wacker, D., Mileni, M., Katritch, V., Han, G.W., Vardy, E., Liu, W., Thompson, A.A., Huang, X.P., Carrol, F.I., et al. (2012). Structure of the human κ-opioid receptor in complex with JDTic. Nature 485, 327–332.Google Scholar
Xie, Z., Lee, S.P., O’Dowd, B.F., and George, S.R. (1999). Serotonin 5-HT1B and 5-HT1D receptors form homodimers when expressed alone and heterodimers when co-expressed. FEBS Lett. 456, 63–67.Google Scholar
Xu, R., Hranilovic, D., Fetsko, L.A., Bucanm, M., and Wangm, Y. (2002). Dopamine D2S and D2L receptors may differentially contribute to the actions of antipsychotic and psychotic agents in mice. Mol. Psychiatry 7, 1075–1082.CrossrefGoogle Scholar
Yang, Z.R., Thomson, R., McNeil, P., and Esnouf, R.M. (2005). RONN: the bio-basis function neural network technique applied to the detection of natively disordered regions in proteins. Bioinformatics 21, 3369–3376.CrossrefGoogle Scholar
Yekkirala, A.S., Kalyuzhny, A.E., and Portoghese, P.S. (2013). An immunocytochemical-derived correlate for evaluating the bridging of heteromeric μ-δ opioid protomers by bivalent ligands. ACS Chem. Biol. 8, 1412–1416.CrossrefGoogle Scholar
Zawarynski, P., Tallerico, T., Seeman, P., Lee, S.P., O’Dowd, B.F., and George, S.R. (1998). Dopamine D2 receptor dimers in human and rat brain FEBS Lett. 441, 383–386.Google Scholar
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Published Online: 2015-09-29
Published in Print: 2016-01-01