Cannabinoids are a group of chemical compounds that have been used for hundreds of years due to their psychoactive function and systemic physiological effects. There are at least two types of cannabinoid receptors, CB1 and CB2, which belong to the G protein-coupled receptor superfamily and can trigger different signaling pathways to exert their physiological functions. In this study, several representative agonists and antagonists of both CB1 and CB2 were studied to predict their binding affinities and selectivity against both cannabinoid receptors using a set of hierarchical molecular modeling & simulation techniques, including homology modeling, molecular docking, molecular dynamics (MD) simulations, endpoint binding free energy calculations using the MM/PBSA-WSAS method, and MM/GBSA free energy decomposition. First, we performed MD simulations followed by the MM/PBSA-WSAS binding free energy calculations. Encouragingly, the calculated binding free energies correlated very well with the experimental values and the correlation coefficient, 0.81, was much higher than the cheap docking scoring function (R=0.38). We then conducted MM/GBSA free energy decomposition to identify the hotspot residues for CB1 and CB2 in both active and inactive conformations. The comparison of binding free energies, ligand-receptor interaction patterns and hotspot residues among four systems, namely, agonist-bound CB1, agonist-bound CB2, antagonist-bound CB1 and antagonist-bound CB2, can facilitate us to investigate and identify distinct binding features of these four systems. Last, we conducted residue-residue coupling analysis using the collected MD snapshots. Using the established residue-residue correlation matrix, we were able to identify and differentiate interaction pathways triggered by agonists and antagonists binding for both CB1 and CB2. The multiscale molecular modeling and simulation studies not only enable us to elucidate the molecular mechanisms for the two cannabinoid receptors, but also guide us to design novel compounds which can act as CB1/CB2-selective agonists/antagonists.

Systematically predict and analyze binding affinity, selectivity, signaling pathways of CB1 and CB2 ligands using molecular modeling approaches

Macromolecular Chemistry: The Second Century

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ACS Spring 2020 National Meeting & Expo

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.