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Record W2338569611 · doi:10.1038/ncomms10357

Protein unfolding as a switch from self-recognition to high-affinity client binding

2016· article· en· W2338569611 on OpenAlexafffund
Bastian Groitl, Scott Horowitz, Karl A.T. Makepeace, Evgeniy V. Petrotchenko, Christoph H. Borchers, Dana Reichmann, James C.A. Bardwell, Ursula Jakob

Bibliographic record

VenueNature Communications · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHeat shock proteins research
Canadian institutionsUniversity of Victoria
FundersNational Institute of General Medical SciencesNatural Sciences and Engineering Research Council of CanadaNational Institutes of HealthGenome British ColumbiaGenome CanadaHoward Hughes Medical Institute
KeywordsLinkerChaperone (clinical)BiophysicsPlasma protein bindingCrystallographyDocking (animal)Binding siteChemistryMetastabilityUnfolded protein responseIntrinsically disordered proteinsCell biologyBiologyEndoplasmic reticulumBiochemistryComputer scienceMedicine

Abstract

fetched live from OpenAlex

Stress-specific activation of the chaperone Hsp33 requires the unfolding of a central linker region. This activation mechanism suggests an intriguing functional relationship between the chaperone's own partial unfolding and its ability to bind other partially folded client proteins. However, identifying where Hsp33 binds its clients has remained a major gap in our understanding of Hsp33's working mechanism. By using site-specific Fluorine-19 nuclear magnetic resonance experiments guided by in vivo crosslinking studies, we now reveal that the partial unfolding of Hsp33's linker region facilitates client binding to an amphipathic docking surface on Hsp33. Furthermore, our results provide experimental evidence for the direct involvement of conditionally disordered regions in unfolded protein binding. The observed structural similarities between Hsp33's own metastable linker region and client proteins present a possible model for how Hsp33 uses protein unfolding as a switch from self-recognition to high-affinity client binding.

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)0.001
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 score0.136
Threshold uncertainty score0.655

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.025
GPT teacher head0.326
Teacher spread0.300 · 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

Citations46
Published2016
Admission routes2
Has abstractyes

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