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 Kim, Yong-Chul Goddard, William A., III 2024-01-19T19:02:03Z 2024-01-19T19:02:03Z 2021-09-05 2019-10-17 1860-7179 https://pubs.kist.re.kr/handle/201004/119438 G(i)-protein-biased agonists with minimal beta-arrestin recruitment represent opportunities to overcome the serious adverse effects of human mu opioid receptor (mu-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 mu-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 G(i)-protein-biased compound, 1-{5-(3-chlorophenyl)-7,8-dimethoxy-3-[4-(methylsulfonyl)benzyl]-3H-pyrazolo[3,4-c]isoquinolin-1-yl}-N,N-dimethylmethanamine, showed an EC50 value of 179 nm against the mu-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. English WILEY-V C H VERLAG GMBH PREDICTED STRUCTURES TRV130 ENSEMBLE MORPHINE AGONISM COMPLEX PAIN Discovery of Novel Biased Opioid Receptor Ligands through Structure-Based Pharmacophore Virtual Screening and Experiment Article 10.1002/cmdc.201900418 1 CHEMMEDCHEM, v.14, no.20, pp.1783 - 1794 CHEMMEDCHEM 14 20 1783 1794 scie scopus 000487771300001 2-s2.0-85073472095 Chemistry, Medicinal Pharmacology & Pharmacy Pharmacology & Pharmacy Article PREDICTED STRUCTURES TRV130 ENSEMBLE MORPHINE AGONISM COMPLEX PAIN G(i)-biased agonists opioids protein construction R-group screening virtual screening