A TR3/Nur77 Peptide-Based High-Throughput Fluorescence Polarization Screen for Small Molecule Bcl-B Inhibitors
Bibliographic record
Abstract
Nuclear receptor TR3/Nur77/NR4A1 binds several antiapoptotic Bcl-2-family proteins (Bcl-B, Bcl-2, Bfl-1) in a non-BH3-dependent manner. A 9-amino-acid peptide derived from full-length TR3 with polyarginine tail (TR3-r8) recapitulates TR3's binding specificity, displaying high affinity for Bcl-B. TR3-r8 peptide was used to screen for small molecule Bcl-B inhibitors. A fluorescence polarization assay (FPA) employing fluorescein isothiocyanate (FITC)-labeled TR3-r8 peptide (FITC-TR3-r8) and Bcl-B protein was optimized, with nonfluorescent TR3-r8 serving to demonstrate reversible, competitive binding. Approximately 50,000 compounds were screened at 3.75 mg/L, yielding 145 reproducible hits with > or =50% FITC-TR3-r8 displacement (a confirmed hit rate of 0.29%). After dose-response analyses and counterscreening with an unrelated FITC-based FPA, 6 candidate compounds remained. Nuclear magnetic resonance (NMR) showed that 2 of these compounds bound Bcl-B, but not glutathione S-transferase (GST) control protein. One Bcl-B-binding compound was unable to displace FITClabeled BH3 peptides from Bcl-B, confirming a unique binding mechanism compared with traditional antagonists of antiapoptotic Bcl-2-family proteins. This compound bound Bcl-B with Kd 1.94 +/- 0.38 microM, as determined by isothermal titration calorimetry. Experiments using Bcl-B overexpressing HeLa cells demonstrated that this compound induced Bcl-B-dependent cell death. The current FPA represents a screen that can identify noncanonical inhibitors of Bcl-2-family proteins.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".