On the expanding terminology in the GPCR field: The meaning of receptor mosaics and receptor heteromers

Abstract

The oligomerization of G protein-coupled receptors (GPCRs) is a fact that deserves further attention as increases both the complexity and diversity of the receptor-mediated signal transduction, thus enriching the cell signaling. Consequently, in the present review we tackle among others the problems concerning the terminology used to describe aspects surrounding the GPCRs oligomerization phenomenon. Therefore, the theoretical implications of the GPCR oligomerization will be briefly discussed together with possible implications of this phenomenon especially for new strategies in drug development.

Keywords::

• Oligomerization
• receptor–receptor interactions
• stoichiometry
• spatial arrangement

Acknowledgements

This work was supported by IRCCS San Camillo (L.F.A.), Swedish Research Council, Swedish Brain Fund and Torsten and Ragnar Söderberg’s Foundation (K.F.) and by grants SAF2008-01462 and Consolider-Ingenio CSD2008-00005 from Ministerio de Ciencia e Innovación to F.C. who belong to the “Neuropharmacology and Pain” accredited research group (Generalitat de Catalunya, 2009 SGR 232).

Declaration of interest

The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.

APPENDIX: Theoretical ligand binding curves

As illustrated in Figure 3, a cluster of receptors can in principle be arranged in different ways, depending on the physical constraints of the membrane environment in which the subunits are placed and on the interaction interfaces available to them.

To analyze the influence of the geometrical arrangement on the properties of the receptor clusters, theoretical ligand binding curves will be here derived for the different arrangements available to a trimeric receptor mosaic of identical subunits.

The analysis will be performed in the framework of the well-known Koshland–Nemethy–Filmer (KNF) model (127), based on a sequential scheme for the binding to a multisubunit protein:

For each binding step we have an equilibrium condition of the form (see (128)):

Where L denotes the ligand, R_i the protein complex with i occupied sites and ΔG⁰ is the change in free energy involved in the transition. The multiplicity factor n_i accounts for the number of ways to achieve i occupied sites.

According to the KNF model, ligand binding at one subunit is assumed to cause a local conformational change (“induced fit”) leading to conformational changes at nearby subunits, affecting their affinity for the ligand. Thus, for each binding step the change in free energy at the equilibrium will depend on three energetic factors: the binding energy, the intrinsic energy difference associated with the conformational change of a subunit and the subunit-subunit interaction energy. To simplify things, however, it was also assumed that the conformational transition of each subunit is concomitant with ligand binding. As a consequence each subunit can be considered to have only two possible configurations (F or “free” and B or “bound”) and the contributions due to ligand binding and conformational change can be lumped together taking the energy per binding event as the free energy difference per subunit between the completely free and completely occupied states. Considering as G⁰=0 the free energy of the completely unoccupied receptor cluster, we can denote the free energy change associated with the binding of a ligand as:

Where K_L is a binding constant including not only the energies directly relating to protein-ligand interactions, but also the energy of the obligatory conformational transition.

As far as the subunit-subunit interactions are concerned, they can be similarly denoted as:

Where K_FB and K_BB express the interaction energy between F-B and B-B pairs of interfaced subunits respectively.

Thus, for a state with i occupied sites, j F-B and z B-B interfaces between subunits, the free energy change relative to the completely unoccupied state is:

The different states available to a trimer arranged according to a linear or triangular topology are illustrated in Figure 6 together with the corresponding values of the parameters n, i, j, z.

Figure 6.  Possible states available to a trimer arranged according to a linear or a triangular structure. Circles indicate subunits and pairs of interacting subunit are connected by a line segment. Black circles represent subunits in the “bound” configuration. The parameters (see text for a definition) i, n, j, and z characterizing each possible state are indicated.

Thus, with a ligand concentration of L, by using the equations (1) and (3) the equilibrium between a trimer with zero and one occupied site can be espressed as:

for a linear trimer

for a triangular trimer

And the concentration at equilibrium of single bound trimers (i.e., R₁) will be:

R₂ and R₃ can be obtained following the same approach by using the corresponding data reported in Figure 6. We have:

Being the fraction of occupied binding sites:

by substituting R₁, R₂ and R₃ with the expressions provided by (4a-b), (5a-b) and (6a-b) we finally obtain:

representing the saturation curves of the trimer in the two configurations.

It is noteworthy that with zero interaction energy, according to equations (2b) and (2c) we have K_FB=K_BB=1 and both (7a) and (7b) become:

This is what one would expect for a cluster of completely independent subunits (Michaelis-Menten curve).

When subunit-subunit interactions are established, however, (7a) and (7b) define substantially different saturation curves as illustrated in Figure 7A, indicating that the existence of receptor–receptor interactions lead to a significant dependence of the receptor cluster response on the geometrical arrangement of the subunits within the cluster. In particular, on comparing the curves obtained with identical values for the constants, it can be seen that the steepness of the curve increases and the mid-point shifts as the number of interactions increases.

Figure 7.  Examples of saturation curves having the binding and interaction constants indicated and comparing the various interaction geometries (schematically shown at the bottom) of a trimer (A) and a tetramer (B). As illustrated, although the curves were characterized by the same set of constants, they showed a clear-cut dependence on the way the receptor cluster was arranged.

The analysis of the tetramer further confirms this point. Three arrangements will be here considered for a cluster of four identical subunits: linear (in which the two interior subunits interact with each of the two neighbours, whereas the two terminal subunits interact with only one neighbour), square (in which the subunit are in a square pattern in which no interactions across the diagonal occur) and tetrahedral (in which each subunit interact with the other three). They are shown in Figure 7B together with their saturation curves, corresponding to the following equations as reported by Leskovac ((129); see also (130)):

for the linear, square and tetrahedral arrangements respectively.

Thus, not only the stoichiometry of a receptor cluster (i.e., the number of component subunits), but also its topological arrangement (in particular the topological organization of the interactions between subunits) determines its behaviour. Stoichiometry and topology should, therefore, be considered as different and complementary characteristics of a receptor cluster, both significantly influencing its response to an incoming ligand.