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Record W4401640626 · doi:10.1002/pro.5137

Molecular basis of the interactions between the disordered <scp>Neh4</scp> and <scp>Neh5</scp> domains of <scp>Nrf2</scp> and <scp>CBP</scp>/p300 in oxidative stress response

2024· article· en· W4401640626 on OpenAlexaff
Nadun C. Karunatilleke, Anne Brickenden, Wing‐Yiu Choy

Bibliographic record

VenueProtein Science · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics, phytochemicals, and oxidative stress
Canadian institutionsWestern University
Fundersnot available
KeywordsTransactivationTranscription factorCell biologyChemistryBiologyGeneBiochemistry

Abstract

fetched live from OpenAlex

Nuclear factor erythroid 2-related factor 2 (Nrf2) is a major transcription factor that functions in maintaining redox homeostasis in cells. It mediates the transcription of cytoprotective genes in response to environmental and endogenous stresses to prevent oxidative damage. Thus, Nrf2 plays a significant role in chemoprevention. However, aberrant activation of Nrf2 has been shown to protect cancer cells from apoptosis and contribute to their chemoresistance. The interaction between Nrf2 and CBP is critical for the gene transcription activation. CBP and its homologue p300 interact with two transactivation domains in Nrf2, Neh4, and Neh5 domains through their TAZ1 and TAZ2 domains. To date, the molecular basis of this crucial interaction is not known, hindering a more detailed understanding of the regulation of Nrf2. To close this knowledge gap, we have used a set of biophysical experiments to dissect the Nrf2-CBP/p300 interactions. Structural properties of Neh4 and Neh5 and their binding with the TAZ1 and TAZ2 domains of CBP/p300 were characterized. Our results show that the Neh4 and Neh5 domains of Nrf2 are intrinsically disordered, and they both can bind the TAZ1 and TAZ2 domains of CBP/p300 with micromolar affinities. The findings provide molecular insight into the regulation of Nrf2 by CBP/p300 through multi-domain interactions.

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)0.002
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
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 score0.047
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.010
GPT teacher head0.263
Teacher spread0.253 · 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.

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

Citations9
Published2024
Admission routes1
Has abstractyes

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