Alternate glucocorticoid receptor ligand binding structures influence outcomes in an in vivo tissue regeneration model
- Authors
- Sengupta, S., Bisson, W.H., Mathew, L.K., Kolluri, S.K., and Tanguay, R.L.
- ID
- ZDB-PUB-120531-2
- Date
- 2012
- Source
- Comparative biochemistry and physiology. Toxicology & pharmacology : CBP 156(2): 121-129 (Journal)
- Registered Authors
- Mathew, Lijoy K., Tanguay, Robyn L.
- Keywords
- docking dynamics, glucocorticoids, in vivo, regeneration, SAR, tissue, zebrafish
- MeSH Terms
-
- Animals
- Regeneration/drug effects*
- Zebrafish/embryology
- Zebrafish/genetics
- Zebrafish/metabolism*
- PubMed
- 22634227 Full text @ Comp. Biochem. Physiol. C Toxicol. Pharmacol.
- CTD
- 22634227
Since their characterization, glucocorticoids (GCs), the most commonly prescribed immunomodulatory drugs, have undergone numerous structural modifications designed to enhance their activity. In vivo assessment of these corticosteroid analogs is essential to understand the difference in molecular signaling of the ligands that share the corticosteroid backbone. Our research identified a novel function of GCs as modulators of tissue regeneration and demonstrated that GCs activate the glucocorticoid receptor (GR) to inhibit early stages of tissue regeneration in zebrafish (Danio rerio). We utilized this phenomenon to assess the effect of different GC analogs on tissue regeneration and identified that some GCs such as beclomethasone dipropionate (BDP) possess inhibitory properties, while others, such as dexamethasone and hydrocortisone have no effect on regeneration. We performed in silico molecular docking and dynamic studies and demonstrated that type and size of substitution at the C17 position of the cortisol backbone confer a unique stable conformation to GR on ligand binding that is critical for inhibitory activity. In the field of tissue regeneration, our study is one of the first Structure Activity Relationship (SAR) investigations performed in vertebrates demonstrating that the in vivo tissue regeneration model is a powerful tool to probe structure function relationships, to understand regenerative biology, and to assist in rational drug design.