Computational prediction of potential drug-like compounds from Cannabis sativa leaf extracts targeted towards Alzheimer therapy

This study was aimed at evaluating the inhibitory effects of the phytochemicals from the Cannabis sativa (Cannabis) leaf extracts against Alzheimer’s disease (AD) protein targets. Twelve compounds derived from the Cannabis sativa leaf extracts were evaluated as potential inhibitors of acetylcholinesterase (AChE), dopa decarboxylase (DDC), serotonin receptor 2C (HTR2C) and monoamine oxidase (MAO). Ligand-based and receptor-ligand complex were used to derive the pharmacophore hypothesis. In silico study through molecular docking simulation method was adopted to analyze the inhibitory activity of the compounds in question. Molecular dynamic simulation (MDs) was performed to assess the stability of the top-ranked phytochemicals. The binding energies of these compounds to the four targets were investigated by the Molecular Mechanics for the Generalized Born Model and Solvent Accessibility method (MM-GBSA). The binding-free energy suggests that cannabinol, cannabichromene, linoelaidic acid and morphinan-6-one can be utilized as lead compounds in drug discovery and development of AD to inhibit activity of AChE, DCC gene, MAO and HTR2C. The MDs indicated that AChE-Cannabinol, DCC-Cannabicoumaronone, MAO-Linoelaidic acid, and HTR2C-morphinan-6-one were stable over the entire course of 100 ns suggesting their role in the regulation of the diseases in which their respective receptors are implicated.