Analysis of FK506, timcodar (VX‐853) and FKBP51 and FKBP52 chaperones in control of glucocorticoid receptor activity and phosphorylation
Bibliographic record
Abstract
The immunosuppressive ligand FK506 and the FK506-binding protein FKBP52 are stimulatory to glucocorticoid receptor (GR) activity. Here, we explore the underlying mechanism by comparing GR activity and phosphorylation status in response to FK506 and the novel nonimmunosuppressive ligand timcodar (VX-853) and in the presence and absence of FKBP52 and the closely related protein FKBP51. Using mouse embryonic fibroblast cells (MEFs) deficient knockout (KO) in FKBP51 or FKBP52, we show decreased GR activity at endogenous genes in 52KO cells, but increased activity in 51KO cells. In 52KO cells, elevated phosphorylation occurred at inhibitory serine 212 and decreased phosphorylation at the stimulatory S220 residue. In contrast, 51KO cells showed increased GR phosphorylation at the stimulatory residues S220 and S234. In wild-type (WT) MEF cells, timcodar, like FK506, potentiated dexamethasone-induced GR transcriptional activity at two endogenous genes. Using 52KO and 51KO MEF cells, FK506 potentiated GR activity in 51KO cells but could not do so in 52KO cells, suggesting FKBP52 as the major target of FK506 action. Like FK506, timcodar potentiated GR in 51KO cells, but it also increased GR activity in 52KO cells. Knock-down of FKBP51 in the 52KO cells showed that the latter effect of timcodar required FKBP51. Thus, timcodar appears to have a dual specificity for FKBP51 and FKBP52. This work demonstrates phosphorylation as an important mechanism in FKBP control of GR and identifies the first nonimmunosuppressive macrolide capable of targeting GR action.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".