Discovery of Nanomolar-Affinity Pharmacological Chaperones Stabilizing the Oncogenic p53 Mutant Y220C
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The tumor suppressor protein p53 is inactivated in the majority of human cancers and remains a prime target for developing new drugs to reactivate its tumor suppressing activity for anticancer therapies. The oncogenic p53 mutant Y220C accounts for approximately 125,000 new cancer cases per annum and is one of the most prevalent p53 mutants overall. It harbors a narrow, mutationally induced pocket at the surface of the DNA-binding domain that destabilizes p53, leading to its rapid denaturation and aggregation. Here, we present the structure-guided development of high-affinity small molecules stabilizing p53-Y220C in vitro, along with the synthetic routes developed in the process, in vitro structure–activity relationship data, and confirmation of their binding mode by protein X-ray crystallography. We disclose two new chemical probes displaying sub-micromolar binding affinity in vitro, marking an important milestone since the discovery of the first small-molecule ligand of Y220C in 2008. New chemical probe JC744 displayed a K d = 320 nM, along with potent in vitro protein stabilization. This study, therefore, represents a significant advance toward high-affinity Y220C ligands for clinical evaluation.
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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) | 0.002 | 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".