Comparative Profiling and Chemogenomics Application of Chemical Tools for NR4A Nuclear Receptors
Bibliographic record
Abstract
The ligand-activated transcription factors of the NR4A family are implicated as promising drug targets with neuroprotective and anticancer potential and attract strong attention in drug discovery. Several NR4A modulators have been described, but a validated set of direct ligands for biological studies is lacking. Here, we profiled the reported and commercially available agonists and inverse agonists under uniform conditions in several orthogonal test systems to establish a highly annotated tool and gain comprehensive insights into the NR4A modulator characteristics. This comparative profiling revealed a lack of on-target binding and modulation for several putative NR4A ligands and validated a set of chemically diverse compounds as direct NR4A modulators for chemogenomics-based target identification studies. Prospective applications unveiled roles of NR4A receptors in endoplasmic reticulum stress and adipocyte differentiation, demonstrating suitability of the set to link the orphan targets with phenotypic effects.
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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 | 0.001 | 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".