Chemical Instability and Promiscuity of Arylmethylidenepyrazolinone-Based MDMX Inhibitors
Bibliographic record
Abstract
Targeting the protein-protein interaction between p53 and MDM2/MDMX (MDM4) represents an attractive anticancer strategy for the treatment of p53-competent tumors. Several selective and potent MDM2 inhibitors have been developed and entered the clinic; however, the repertoire of MDMX antagonists is still limited. The arylmethylidenepyrazolinone SJ-172550 has been reported as a selective MDMX antagonist; yet, uncertainties about its mechanism of action have raised doubts about its use as a chemical probe. Here, we show that, in addition to its unclear mode of action, SJ-172550 is unstable in aqueous buffers, giving rise to side products of unknown biological activity. Using an SJ-172550-derived affinity probe, we observed promiscuous binding to cellular proteins whereas cellular thermal shift assays did not reveal a stabilizing effect on MDMX. Overall, our results raise further questions about the interpretation of data using SJ-172550 and related compounds to investigate cellular phenotypes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".