Candidate Therapeutics by Screening for Multitargeting Ligands: Combining the CB2 Receptor With CB1, PPARγ and 5-HT4 Receptors - El-Atawneh, Shayma; Goldblum, Amiram (Frontiers in Pharmacology, 2022)
In recent years, the cannabinoid type 2 receptor (CB2R) became a major target for treating neuropathic pain, neurodegenerative and inflammatory conditions, addiction, and cancer. During those years, the paradigm of "one disease-one target-one drug" has transformed to "one disease-many targets-one drug", particularly in such multifactorial disorders due to their polygenic nature. Multitargeting, therefore, attracts much attention as a promising approach for many complex disorders. We focus on designing single multitargeting agents (MTAs), which have many advantages over combined therapies. Using our ligand-based approach, the "Iterative Stochastic Elimination" (ISE) algorithm, we produce activity models of agonists and antagonists for desired therapeutic targets and anti-targets. These models are used for sequential virtual screening and scoring libraries of molecules to pick top-scored candidates for testing in vitro and in vivo. In this study, we built activity models for CB2R and other targets for combinations that could be used for several indications. Those targets are the cannabinoid 1 receptor (CB1R), peroxisome proliferator-activated (PPAR)-γ, and 5-Hydroxytryptamine receptor 4 (5-HT4). All models have good classification performance and high AUC. Screening through CB2 and CB1 agonist models as desired targets and the antagonist models as anti-targets yields 7422 candidates, while CB2 agonist and CB1 antagonist activity yield 452 molecules. CB2R agonism combined with PPARγ or 5-HT4R agonist activity may be used for treating Inflammatory Bowel Disease (IBD). Combining CB2R agonism with 5-HT4R generates more candidates (572) than combining CB2R agonism with agonists for the nuclear receptor PPARγ (34 candidates). The number of candidates may be minimized by increasing the ISE score cutoff or by performing docking. Those candidates can be purchased and tested experimentally to validate their activity. Further, we performed docking to CB2R structures and found lower statistical performance of the docking compared to ISE modeling. Therefore, ISE and -in general- ligand-based modeling may be a better starting point for molecular discovery than docking.