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

Abstract

The cannabinoid receptor 1 (CB1R) plays a pivotal role in regulating various physiopathological processes, thus positioning itself as a promising and sought-after therapeutic target. However, the search for specific and effective CB1R ligands has been challenging, prompting the exploration of drug repurposing (DR) strategies. In this study, we present an innovative DR approach that combines computational screening and experimental validation to identify potential Food and Drug Administration (FDA)-approved compounds that can interact with the CB1R. Initially, a large-scale virtual screening was conducted using molecular docking simulations, where a library of FDA-approved drugs was screened against the CB1R's three-dimensional structures. This in silico analysis allowed us to prioritize compounds based on their binding affinity through two different filters. Subsequently, the shortlisted compounds were subjected to in vitro assays using cellular and biochemical models to validate their interaction with the CB1R and determine their functional impact. Our results reveal FDA-approved compounds that exhibit promising interactions with the CB1R. These findings open up exciting opportunities for DR in various disorders where CB1R signaling is implicated. In conclusion, our integrated computational and experimental approach demonstrates the feasibility of DR for discovering CB1R modulators from existing FDA-approved compounds. By leveraging the wealth of existing pharmacological data, this strategy accelerates the identification of potential therapeutics while reducing development costs and timelines. The findings from this study hold the potential to advance novel treatments for a range of CB1R -associated diseases, presenting a significant step forward in drug discovery research.

Keywords: cannabinoid receptor 1; drug repurposing; structure-based virtual screening.

Figure 1

Cross-docking using two 3D structures (PDB 5XRA and 5U09) with AM11542 and Taranabant. ΔΔG = ΔGre-dock − ΔGcross-dock.

Figure 2

Representative examples of blind docking filter stage showing comparison between AM11542 (a), Raloxifene (b) and mupirocin (c), a discarded drug, in channel of 5XRA structure. Each blue dot represents a predicted pose with high affinity (from −12.0 to −9.0 kcal/mol). Light blue dots are poses with medium affinity (from −8.0 to −7.0 kcal/mol).

Figure 3

Competition of [³H]CP55,940 binding by Aminopterin (APGA), Avanafil, Ceftriaxone, Methotrexate, Miltefosine, PGE-1, Raloxifene, Raltegravir, Riociguat and Valsartan at 10 µM in membrane mouse brain. Data are presented as the mean (±SD) of two independent experiments, each performed in duplicate. * p < 0.05, ** p < 0.01 and *** p < 0.001.

Figure 4

Activity-based protein profiling of some of the main enzymes of the endocannabinoid system in the mouse brain, either in membrane fractions (a) or in cytosolic fractions (b). The samples are in the following order: control (DMSO), DH376, ABX1431, DO264, PF04458745, Raltegravir and Methotrexate (top panels); control (ethanol), DH376, ABX1431, DO264, PF04458745 and Miltefosine (bottom panels).

Figure 5

Dose- and time-dependence of HaCaT cell viability upon Miltefosine exposure (a). Live cells percentage after 4 h of incubation with Miltefosine (25 µM) and SR141716 (1 µM) at different preincubation times (30 min, 1 h, 90 min and 2 h) (b). * p < 0.05, ** p < 0.01 and *** p < 0.001.

Scheme 1

Graphic phases of the virtual screening.