A mechanistic model explaining ligand affinity for, and partial agonism of, cannabinoid receptor 1

CB1, a member of the G protein-coupled receptor class, is the putative protein target of THC, the psychoactive component of cannabis. To better identify new synthetic cannabinoids with increased activity, all cannabinoids with reported experimental binding to the CB1 receptor were modelled in silico to build a predictive model for CB1 affinity of small molecules. Computationally derived affinity is not sufficient in and of itself to predict binding, but coupled with the experimental evidence that ligands enter the receptor from the membrane rather than solvent, we provide a model that accurately describes the binding of these molecules by incorporating a correction factor for relative hydrophobicity. In addition, we propose a mechanism of action for partial CB1 agonists based on molecular dynamics simulations of THC homologues, modelling long time scale structural changes in the CB1 receptor. Together, the affinity model, and the mechanism of agonism/antagonism can allow for the computational prediction of both the effective behaviour and potency of novel cannabinoids, and several such predictions are made.