| Literature DB >> 33510451 |
Nelson E Bruno1, Jerome C Nwachukwu1, Sathish Srinivasan1, Charles C Nettles1, Tina Izard1, Zhuang Jin2,3, Jason Nowak1, Michael D Cameron2, Siddaraju V Boregowda2, Donald G Phinney2, Olivier Elemento4, Xu Liu5, Eric A Ortlund5, René Houtman6, Diana A Stavreva7, Gordon L Hager7, Theodore M Kamenecka2, Douglas J Kojetin1,2, Kendall W Nettles8.
Abstract
Glucocorticoids display remarkable anti-inflammatory activity, but their use is limited by on-target adverse effects including insulin resistance and skeletal muscle atrophy. We used a chemical systems biology approach, ligand class analysis, to examine ligands designed to modulate glucocorticoid receptor activity through distinct structural mechanisms. These ligands displayed diverse activity profiles, providing the variance required to identify target genes and coregulator interactions that were highly predictive of their effects on myocyte glucose disposal and protein balance. Their anti-inflammatory effects were linked to glucose disposal but not muscle atrophy. This approach also predicted selective modulation in vivo, identifying compounds that were muscle-sparing or anabolic for protein balance and mitochondrial potential. Ligand class analysis defined the mechanistic links between the ligand-receptor interface and ligand-driven physiological outcomes, a general approach that can be applied to any ligand-regulated allosteric signaling system.Entities:
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Year: 2021 PMID: 33510451 PMCID: PMC8783757 DOI: 10.1038/s41589-020-00719-w
Source DB: PubMed Journal: Nat Chem Biol ISSN: 1552-4450 Impact factor: 15.040