“The growing interest on the therapeutic potential against neurodegeneration of Cannabis sativa extracts, and of phytocannabinoids in particular, is paralleled by a limited understanding of the undergoing biochemical pathways in which these natural compounds may be involved. Computational tools are nowadays commonly enrolled in the drug discovery workflow and can guide the investigation of macromolecular targets for such molecules. In this contribution, in silico techniques have been applied to the study of C. sativa constituents at various extents, and a total of 7 phytocannabinoids and 4 terpenes were considered. On the side of ligand-based virtual screening, physico-chemical descriptors were computed and evaluated, highlighting the phytocannabinoids possessing suitable drug-like properties to potentially target the central nervous system. Our previous findings and literature data prompted us to investigate the interaction of these molecules with phosphodiesterases (PDEs), a family of enzymes being studied for the development of therapeutic agents against neurodegeneration. Among the compounds, structure-based techniques such as docking and molecular dynamics (MD), highlighted cannabidiol (CBD) as a potential and selective PDE9 ligand, since a promising calculated binding energy value (-9.1 kcal/mol) and a stable interaction in the MD simulation timeframe were predicted. Additionally, PDE9 inhibition assay confirmed the computational results, and showed that CBD inhibits the enzyme in the nanomolar range in vitro, paving the way for further development of this phytocannabinoid as a therapeutic option against neurodegeneration.”
