PT  - JOURNAL ARTICLE
AU  - Nelson E. Bruno
AU  - Jerome C. Nwachukwu
AU  - Sathish Srinivasan
AU  - Charles C. Nettles
AU  - Tina Izard
AU  - Zhuang Jin
AU  - Siddaraju V. Boregowda
AU  - Donald G. Phinney
AU  - Olivier Elemento
AU  - Xu Liu
AU  - Eric A. Ortlund
AU  - René Houtman
AU  - Diana A. Stavreva
AU  - Gordon L. Hager
AU  - Theodore M. Kamenecka
AU  - Douglas J. Kojetin
AU  - Kendall W. Nettles
TI  - Chemical Systems Biology Reveals Mechanisms of Glucocorticoid Receptor Signaling
AID  - 10.1101/2020.06.15.153270
DP  - 2020 Jan 01
TA  - bioRxiv
PG  - 2020.06.15.153270
4099  - http://biorxiv.org/content/early/2020/10/16/2020.06.15.153270.short
4100  - http://biorxiv.org/content/early/2020/10/16/2020.06.15.153270.full
AB  - 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 (LCA), 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. LCA 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.Competing Interest StatementThe authors have declared no competing interest.