Scaffold Hopping from Amodiaquine to Novel Nurr1 Agonist Chemotypes via Microscale Analogue Libraries
Bibliographic record
Abstract
Several lines of evidence suggest the ligand-sensing transcription factor Nurr1 as a promising target to treat neurodegenerative diseases. Nurr1 modulators to validate and exploit this therapeutic potential are rare, however. To identify novel Nurr1 agonist chemotypes, we have employed the Nurr1 activator amodiaquine as template for microscale analogue library synthesis. The first set of analogues was based on the 7-chloroquiolin-4-amine core fragment of amodiaquine and revealed superior N-substituents compared to diethylaminomethylphenol contained in the template. A second library of analogues was subsequently prepared to replace the chloroquinolineamine scaffold. The two sets of analogues enabled a full scaffold hop from amodiaquine to a novel Nurr1 agonist sharing no structural features with the lead but comprising superior potency on Nurr1. Additionally, pharmacophore modeling based on the entire set of active and inactive analogues suggested key features for Nurr1 agonists.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".