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Record W4399532434 · doi:10.1038/s41419-024-06739-x

Structural basis of p53 inactivation by cavity-creating cancer mutations and its implications for the development of mutant p53 reactivators

2024· article· en· W4399532434 on OpenAlexafffund
Dimitrios-Ilias Balourdas, Anja M. Markl, Andreas Krämer, Giovanni Settanni, Andreas C. Joerger

Bibliographic record

VenueCell Death and Disease · 2024
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsStructural Genomics Consortium
FundersOntario Genomics InstituteEuropean Federation of Pharmaceutical Industries and AssociationsMerck KGaAOntario GenomicsGenome CanadaMcGill UniversityGenentechBayerPfizerDeutsche ForschungsgemeinschaftBristol-Myers Squibb
KeywordsMutantMutationCancerCancer researchCell biologyBiologyGeneticsComputational biologyChemistryGene

Abstract

fetched live from OpenAlex

The cavity-creating p53 cancer mutation Y220C is an ideal paradigm for developing small-molecule drugs based on protein stabilization. Here, we have systematically analyzed the structural and stability effects of all oncogenic Tyr-to-Cys mutations (Y126C, Y163C, Y205C, Y220C, Y234C, and Y236C) in the p53 DNA-binding domain (DBD). They were all highly destabilizing, drastically lowering the melting temperature of the protein by 8-17 °C. In contrast, two non-cancerous mutations, Y103C and Y107C, had only a moderate effect on protein stability. Differential stabilization of the mutants upon treatment with the anticancer agent arsenic trioxide and stibogluconate revealed an interesting proximity effect. Crystallographic studies complemented by MD simulations showed that two of the mutations, Y234C and Y236C, create internal cavities of different size and shape, whereas the others induce unique surface lesions. The mutation-induced pockets in the Y126C and Y205C mutant were, however, relatively small compared with that of the already druggable Y220C mutant. Intriguingly, our structural studies suggest a pronounced plasticity of the mutation-induced pocket in the frequently occurring Y163C mutant, which may be exploited for the development of small-molecule stabilizers. We point out general principles for reactivating thermolabile cancer mutants and highlight special cases where mutant-specific drugs are needed for the pharmacological rescue of p53 function in tumors.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.259
Threshold uncertainty score0.253

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.293
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations17
Published2024
Admission routes2
Has abstractyes

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