Identification of CB1 Ligands among Drugs, Phytochemicals and Natural-Like Compounds: Virtual Screening and In Vitro Verification

Abstract

Cannabinoid receptor type 1 (CB1) is an important modulator of many key physiological functions and thus a compelling molecular target. However, safe CB1 targeting is a non-trivial task. In recent years, there has been a surge of data indicating that drugs successfully used in the clinic for years (e.g. paracetamol) show CB1 activity. Moreover, there is a lot of promise in finding CB1 ligands in plants other than Cannabis sativa. In this study, we searched for possible CB1 activity among already existing drugs, their metabolites, phytochemicals, and natural-like molecules. We conducted two iterations of virtual screening, verifying the results with in vitro binding and functional assays. The in silico procedure consisted of a wide range of structure- and ligand-based methods, including docking, molecular dynamics, and quantitative structure–activity relationship (QSAR). As a result, we identified travoprost and ginkgetin as CB1 ligands, which provides a starting point for future research on the impact of their metabolites or preparations on the endocannabinoid system. Moreover, we found five natural-like compounds with submicromolar or low micromolar affinity to CB1, including one mixed partial agonist/antagonist viable for hit-to-lead phase. Finally, the computational procedure established in this work will be of use for future screening campaigns for novel CB1 ligands.

Identification of Novel CB2 Ligands through Virtual Screening and In Vitro Evaluation

“…In silico methods that are often used for the screening campaigns, such as molecular docking, usually struggle with cases in which protein–ligand binding modes are determined mainly by multiple nonspecific, hydrophobic interactions. As this is the case with CBRs, effective utilization of docking is a challenging task, as there may be issues with both proper pose and binding affinity prediction …”

“…As this is the case with CBRs, effective utilization of docking is a challenging task, as there may be issues with both proper pose and binding affinity prediction. 81 …”

Goods and Bads of the Endocannabinoid System as a Therapeutic Target: Lessons Learned after 30 Years

“…Overall, the same potentialities and limitations revealed by accumulated evidence in so many studies on CB 1 R, CB 2 R, FAAH and MAGL are likely to apply also to the more recently characterized elements of the ECS, and hopefully will be instructive to avoid making again the same mistakes. In particular, a better appreciation of the 3D structure of the desired targets, also via cryo-electron microscopy (Hua et al, 2020), and the application of powerful in silico tools like CADD, virtual screening (Stasiulewicz et al, 2022) and machine learning (Atz et al, 2023) hold promise to shorten the path from the bench to the patient's bed in drug discovery programmes oriented toward the ECS. This knowledge of structural details will also help to decipher complex interactions between pCBs/eCBs and other bioactive lipids (e.g., eicosanoids and specialized pro-resolving mediators) that are receiving increasing attention for their therapeutic potential to treat human diseases (Maccarrone, 2023).…”

Computational and Experimental Drug Repurposing of FDA-Approved Compounds Targeting the Cannabinoid Receptor CB1

“…DR also promises high approval rates, because the safety of any commercially available drug has been already assessed in preclinical and clinical trials; thus, the time (and money) needed for drug development can be reduced using this approach [6,7]. Aspirin is the oldest example of DR.…”