GPCR homomers and heteromers: a better choice as targets for drug development than GPCR monomers?

Abstract

G protein-coupled receptors (GPCR) are targeted by many therapeutic drugs marketed to fight against a variety of diseases. Selection of novel lead compounds are based on pharmacological parameters obtained assuming that GPCR are monomers. However, many GPCR are expressed as dimers/oligomers. Therefore, drug development may consider GPCR as homo- and hetero-oligomers. A two-state dimer receptor model is now available to understand GPCR operation and to interpret data obtained from drugs interacting with dimers, and even from mixtures of monomers and dimers. Heteromers are distinct entities and therefore a given drug is expected to have different affinities and different efficacies depending on the heteromer. All these concepts would lead to broaden the therapeutic potential of drugs targeting GPCRs, including receptor heteromer-selective drugs with a lower incidence of side effects, or to identify novel pharmacological profiles using cell models expressing receptor heteromers.

Fig. 1.

Saturation data for the [³H]estradiol binding to estrogen receptors from calf uteri. Data points obtained from Fig. 2 in Notides et al. (1981) were fitted assuming one or two affinity states (dashed line) or a two-state dimer. F test indicated that a significant improvement is obtained by assuming the two-state dimer receptor model; thus, in Table 1, only the parameter values obtained assuming dimers are shown.

Fig. 2.

Monophasic competition data for antagonist binding to dopamine D₁ receptors. Competition was performed using variable concentrations of non-radiolabeled SCH 23390 and 2.7 nM [³H]SCH 23390 in lamb brain striatal membranes (0.5 mg protein/ml) using the protocol described in Ferrada et al., 2009. Data were fitted using equations derived from the two-state dimer receptor model (solid line) or derived from the assumption of one-affinity (monomeric) state (dashed line). The parameter values obtained by non-linear regression are indicated in Table 2.

Fig. 3.

Biphasic competition curves for antagonist versus agonist binding to dopamine D₁ receptors. Competition was performed using variable concentrations of non-radiolabeled SKF 38393 (agonist) and 1.2 nM [³H]SCH 23390 (antagonist) in lamb brain striatal membranes (0.5 mg protein/ml) using the protocol described in Ferrada et al., 2009. Data were fitted using equations derived from the two-state dimer receptor model or derived from the assumption of two-affinity (monomeric) states. The two fittings led to indistinguishable curves. The parameter values obtained by non-linear regression are indicated in Table 3.

Fig. 4.

Competition assays simulation. Simulation was performed considering Eq. (3) (see Appendix A), 1 pmol/mg protein of maximum binding (RT=0.50 pmol/mg protein), the values of K_DA1, K_DB1, K_DB2 and K_DAB from Tables 2 and 3, different radioligand concentrations (A in Eq. (3); 0.05, 0.1, 0,2, 0.3, 0.5, 0.7, 1.0, 1.25, 1.5, 2.0, 3.0, 5.0 and 10 nM bottom to top) and different competitor concentrations (0.001 nM to 1 mM as for the D1 receptor agonist SKF 38393, B, in Eq. (3)).