Virtual screening using docking and molecular dynamics of cannabinoid analogs against CB₁ and CB₂ receptors

Cannabis sativa has been attributed to different pharmacological properties. A number of secondary metabolites such as tetrahydrocannabinol (THC), cannabinol (CBD), and different analogs, with highly promising biological activity on CB₁ and CB₂ receptors, have been identified.

Thus, this study aimed was to evaluate the activity of THC, CBD, and their analogs using molecular docking and molecular dynamics simulations (MD) methods. Initially, the molecules (ligands) were selected by bioinformatics searches in databases. Subsequently, CB₁ and CB₂ receptors were retrieved from the protein data bank database. Afterward, each receptor and its ligands were optimized to perform molecular docking. Then, MD Simulation was performed with the most stable ligand-receptor complexes. Finally, the Molecular Mechanics-Generalized Born Surface Area (MM-PBSA) method was applied to analyze the binding free energy between ligands and cannabinoid receptors.

The results obtained showed that ligand LS-61176 presented the best affinity in the molecular docking analysis. Also, this analog could be a CB₁ negative allosteric modulator like CBD and probably an agonist in CB₂ like THC and CBD according to their dynamic behavior in silico. The possibility of having a THC and a CBD analog (LS-61176) as a promising molecule for experimental evaluation since it could have no central side-effects on CB₁ and have effects of CB₂ useful in pain, inflammation, and some immunological disorders. Docking results were validate using ROC curve for both cannabinoids receptor where AUC for CB1 receptor was 0.894±0.024, and for CB2 receptor AUC was 0.832±0032, indicating good affinity prediction.