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Record W2109165566 · doi:10.1002/bip.20567

Three steps in the thermal unfolding of F‐actin: An experimental evidence

2006· article· en· W2109165566 on OpenAlexaff
C Gicquaud, Benoit Heppell

Bibliographic record

VenueBiopolymers · 2006
Typearticle
Languageen
FieldChemistry
Topicthermodynamics and calorimetric analyses
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsDifferential scanning calorimetryChemistryDenaturation (fissile materials)ActinBiophysicsCrystallographyCalorimetryNucleotideBiochemistryThermodynamicsBiology

Abstract

fetched live from OpenAlex

Abstract The development of differential scanning calorimetry has resulted in an increased interest in studies of the unfolding process in proteins with the aim of identifying domains and interactions with ligands or other proteins. Several of these studies were done with actin and showed that the thermal unfolding of F‐actin occurs in at least three steps; this was interpreted as the denaturation of independent domains. In the present work, we have followed the thermal unfolding of F‐actin using differential scanning calorimetry (DSC), CD spectroscopy, and probe fluorescence. We found that the three steps revealed through DSC are not the denaturation of independent domains. These three steps are a change in the environment of cys 374 at 49.5°C; a modification at the nucleotide‐binding site at 55°C; and the unfolding of the peptide chain at 64°C. Previous interpretations of the thermograms of F‐actin were thus erroneous. Since DSC is now widely used to study proteins, our experimental approach and conclusions may also be relevant in denaturation studies of proteins in general. © 2006 Wiley Periodicals, Inc. Biopolymers 83:374–380, 2006 This article was originally published online as an accepted preprint. The “Published Online” date corresponds to the preprint version. You can request a copy of the preprint by emailing the Biopolymers editorial office at biopolymers@wiley.com

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 score0.013
Threshold uncertainty score0.633

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 head0.033
GPT teacher head0.284
Teacher spread0.250 · 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

Citations5
Published2006
Admission routes1
Has abstractyes

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