Identification of p53-R175H Q167 and R248 as Residues Most Involved in Its Interaction with Plakoglobin
Bibliographic record
Abstract
Background: The conformational p53-R175H is the most frequently occurring p53 mutant in cancers and a focus of mutant p53 targeted therapies. Plakoglobin is a dual cell adhesion and signaling protein with tumor suppressor activity. We previously showed that plakoglobin interacts with p53 and restores tumor suppressive activity of p53 mutants, including p53-R175H, in vitro. Method: Here, we used in silico modeling to predict the residues in p53-R175H that contribute the most to its interaction with plakoglobin, which identified p53-R175H Q167 and R248 as residues most involved in this interaction. To validate our in silico results, constructs were developed in which the predicted residues were substituted by alanine and transfected into the p53 null and plakoglobin deficient H1299 cells with or without plakoglobin. Transfectants expressing substituted residues were characterized using various biochemical and functional assays. Results: Co-immunoprecipitation and GST pull down assays showed a significant reduction in p53-R175H-plakoglobin association in p53-R175H-(Q167A, R248A and Q167A-R248A) transfectants. Despite the reduced interaction, in vitro invasion assays showed plakoglobin expression decreased invasiveness of all transfectants with the highest reduction in p53-R175H-R248A and R175H-Q167A-R248A expressing transfectants. Conclusion: These studies demonstrate, for the first time, the role of Q167 and R248 residues in p53-R175H's interaction with plakoglobin. The larger implication of these observations is the potential for exploring plakoglobin's interaction with p53-R175H mutant for the development of cancer therapeutics that restores the wild-type transcriptional activity/function of mutant p53s.
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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 | 0.000 |
| 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".