Development of computational models to understand the dynamic molecular recognition mechanisms of cannabinoid receptors

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Background: The use of cannabis has been legalized for both recreational and medical purposes in several countries worldwide including Canada. The latest data from Health Canada show that there were 329,038 active medical cannabis registrations during the first quarter of 2020. While the benefits of cannabis have been widely agreed, it is vital to enhance our understanding about the molecular mechanisms of how cannabinoids (CBs) - the active chemicals in cannabis- mediate their effects, which will help to develop safer and psychoactivity-free CBs. CBs are known to modulate the cannabinoid receptors (CBRs), CB1 and CB2, in humans. CB1 is expressed in the central nervous system, whereas the CB2 is mainly found in the immune system. The activation of these receptors by the binding of endogenous or exogenous CBs triggers a cascade of signaling pathways that is important for diverse physiological roles such as feeding, pain, emotional behaviour, immunity and lipid metabolism. Therefore, CB1 and CB2 have emerged as important class of enzymes. In the past decade, several synthetic and plant-based CBs have been developed. But, the modulation of CB1 in the leads to psychoactivity. On the contrary, since CB2 expression is concentrated in the immune system, and to a lesser extent in the brain, psychoactive side-effects can be evaded by regulating CB2. However, most of the known CBs non-specifically bind to both CB1 and CB2 and caused mild to severe psychoactivity. Therefore, it is crucial to identify molecular features that are unique to the two cannabinoid receptors to develop isoform-selective molecules. In addition, there remain numerous questions about the structural plasticity, ligand interactions, activation and signalling processes in cannabinoid receptors, which we seek to address in this research program. Objectives and methods: This research program aims at revealing molecular level details that are critical for isoform specificity in CBRs. Our objectives are to (O1) build comprehensive dynamical atomistic models of cannabinoid receptors, (O2) characterize the ligand-CB receptor interactions to elucidate the molecular processes behind ligand-mediated modulation of the cannabinoid receptors, and (O3) model specific protein-protein interactions that promote CBR signaling. We will use a combination of advanced computational modelling, molecular dynamics simulation approaches, machine learning methods and complementary experimental techniques to achieve our objectives. Impact: This research will contribute original knowledge in bioscience, chemical biology and train HQP by advancing our fundamental knowledge linked with mechanistic processes of molecular recognition in CBRs. Such insights could be useful to develop selective CBs without psychoactivity. The program will also be a suitable platform for training next generation of scientists in molecular modelling-driven endocannabinoid research.