Farnesyl Pyrophosphate Is a Novel Transcriptional Activator for a Subset of Nuclear Hormone Receptors
Bibliographic record
Abstract
In silico docking of a chemical library with the ligand-binding domain of thyroid hormone nuclear receptor-beta (TRbeta) suggested that farnesyl pyrophosphate (FPP), a key intermediate in cholesterol synthesis and protein farnesylation, might function as an agonist. Surprisingly, addition of FPP to cells activated TR as well as the classical steroid hormone receptors but not peroxisome proliferative-activating receptors, farnesoid X receptor, liver X receptor, or several orphan nuclear receptors the ligands of which are unknown. FPP enhanced receptor-coactivator binding in vitro and in vivo, and elevation of FPP levels in cells by squalene synthetase or farnesyl transferase inhibitors leads to activation. The FPP effect was blocked by selective receptor antagonists, and in silico docking with 143 nuclear receptor ligand-binding domain structures revealed that FPP only docked with the agonist conformation of those receptors activated by FPP. Our results suggest that certain nuclear receptors maintain a common structural feature that may reflect an action of FPP on an ancient nuclear receptor or that FPP could function as a ligand for one of the many orphan nuclear receptors the ligands of which have not yet been identified. This finding also has potential interesting implications that may, in part, explain the pleotropic effects of statins as well as certain actions of farnesylation inhibitors in cells.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".