Discovery of Novel Biased Opioid Receptor Ligands through Structure‐Based Pharmacophore Virtual Screening and Experiment. (26th September 2019) - Jeong, Pyeonghwa; Kim, Soo‐Kyung; Li, Quanjie; Oh, Su‐jin; Son, Seonil; Chen, Guangju; Tan, Hongwei; Kim, Siwon; Park, Jong‐Hyun; Park, Ki Duk; Kim, Yeo Ok; Yoon, Myung Ha; et al.
Abstract: Gi ‐protein‐biased agonists with minimal β‐arrestin recruitment represent opportunities to overcome the serious adverse effects of human mu opioid receptor (μ‐OR) agonists and developing alternative and safe treatments for pain. In order to discover novel non‐morphinan opioid receptor agonists, we applied hierarchical virtual screening of our in‐house database against a pharmacophore based on modeling the active conformations of opioid receptors. We discovered an initial hit compound, a novel μ‐OR agonist with a pyrazoloisoquinoline scaffold. We applied computational R‐group screening to this compound and synthesized 14 derivatives predicted to be the best. Of these, a new Gi ‐protein‐biased compound, 1‐5‐(3‐chlorophenyl)‐7, 8‐dimethoxy‐3‐[4‐(methylsulfonyl)benzyl]‐3 H ‐pyrazolo[3, 4‐ c ]isoquinolin‐1‐yl‐ N, N ‐dimethylmethanamine, showed an EC50 value of 179 nm against the μ‐OR. This resulted in significant pain relief for mice in the phase II period of formalin response tests. This study provides a new strategy to identify diverse sets of promising compounds that might prove useful for the development of drugs that target other G‐protein‐coupled receptors. Abstract : Bias abound ! To discover Gi ‐protein‐biased opioid receptor agonists, we built active homology models from a vast number of potential packings (13 trillion) of opioid receptors and processed structure‐based drug design. Novel pyrazolo[3, 4‐ c ]isoquinoline derivatives were synthesized by step‐by‐step computational optimization and one compound selectively activated the human mu opioid receptor with minimal β‐arrestin recruitment.