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Record W1976116660 · doi:10.1038/srep02305

Binding of disordered proteins to a protein hub

2013· article· en· W1976116660 on OpenAlexafffund
Elio A. Cino, Ryan C. Killoran, Mikko Karttunen, Wing‐Yiu Choy

Bibliographic record

VenueScientific Reports · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPhotosynthetic Processes and Mechanisms
Canadian institutionsUniversity of WaterlooWestern University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchUniversity of WaterlooCompute Canada
KeywordsIsothermal titration calorimetryInteractomeAffinitiesBinding affinitiesMolecular dynamicsPlasma protein bindingKEAP1BiophysicsChemistryComputational biologyProtein–protein interactionBinding siteBiochemistryBiologyComputational chemistry

Abstract

fetched live from OpenAlex

A small number of proteins, called hubs, have high connectivity and are essential for interactome functionality and integrity. Keap1 is a crucial hub in the oxidative stress response and apoptosis. The Kelch domain of Keap1 preferentially binds to disordered regions of its partners, which share similar binding motifs, but have a wide range of binding affinities. Isothermal titration calorimetry (ITC) and multi-microsecond molecular dynamics (MD) simulations were used to determine the factors that govern the affinity of all currently known disordered binding partners to Kelch. Our results show that the affinities to this hub are largely determined by the extent of preformed bound state-like conformation in the free state structures of these disordered targets. Based on our findings, we have designed a high-affinity peptide that can specifically disrupt the Keap1-NRF2 interaction and has the potential for therapeutic applications.

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 score0.021
Threshold uncertainty score0.351

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 head0.007
GPT teacher head0.223
Teacher spread0.216 · 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

Citations35
Published2013
Admission routes2
Has abstractyes

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