Abstract

Pharmacodynamic efficacy of drugs to activate their receptors is a key determinant of drug effects, and intermediate-efficacy agonists are often useful clinically because they retain sufficient efficacy to produce therapeutically desirable effects while minimizing undesirable effects. Molecular mechanisms of efficacy are not well understood, so rational drug design to control efficacy is not yet possible; however, receptor theory predicts that fixed-proportion mixtures of an agonist and antagonist for a given receptor can be adjusted to precisely control net efficacy of the mixture in activating that receptor. Moreover, the agonist proportion required to produce different effects provides a quantitative scale for comparing efficacy requirements across those effects. To test this hypothesis, the present study evaluated effectiveness of fixed-proportion agonist/antagonist mixtures to produce in vitro and in vivo effects mediated by mu opioid receptors (MOR) and cannabinoid type-1 receptors (CB₁R). Mixtures of the MOR agonist fentanyl and antagonist naltrexone, and of the CB₁R agonist CP55,940 and antagonist/inverse agonist rimonabant, were evaluated in an in vitro assay of ligand-stimulated [³⁵S]GTPgS binding and an in vivo assay of thermal nociception in mice. For both agonist/antagonist pairs in both assays, increasing agonist proportions produced graded increases in maximal mixture effects, and lower agonist proportions were sufficient to produce in vivo than in vitro effects. These findings support the utility of agonist/antagonist mixtures as a strategy to control net efficacy of receptor activation and to quantify and compare efficacy requirements across a range of in vitro and in vivo endpoints.

Significance Statement Significance Statement: Manipulation of agonist proportion in agonist/antagonist mixtures governs net mixture efficacy at the target receptor. Parameters of agonist/antagonist mixture effects can provides a quantitative metric for comparison of efficacy requirements across a wide range of conditions.