Targeting Cavity-Creating p53 Cancer Mutations with Small-Molecule Stabilizers: the Y220X Paradigm
Bibliographic record
Abstract
We have previously shown that the thermolabile, cavity-creating p53 cancer mutant Y220C can be reactivated by small-molecule stabilizers. In our ongoing efforts to unearth druggable variants of the p53 mutome, we have now analyzed the effects of other cancer-associated mutations at codon 220 on the structure, stability, and dynamics of the p53 DNA-binding domain (DBD). We found that the oncogenic Y220H, Y220N, and Y220S mutations are also highly destabilizing, suggesting that they are largely unfolded under physiological conditions. A high-resolution crystal structure of the Y220S mutant DBD revealed a mutation-induced surface crevice similar to that of Y220C, whereas the corresponding pocket's accessibility to small molecules was blocked in the structure of the Y220H mutant. Accordingly, a series of carbazole-based small molecules, designed for stabilizing the Y220C mutant, also bound to and stabilized the folded state of the Y220S mutant, albeit with varying affinities due to structural differences in the binding pocket of the two mutants. Some of the compounds also bound to and stabilized the Y220N mutant, but not the Y220H mutant. Our data validate the Y220S and Y220N mutants as druggable targets and provide a framework for the design of Y220S or Y220N-specific compounds as well as compounds with dual Y220C/Y220S specificity for use in personalized cancer therapy.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".