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Record W2112634975 · doi:10.1002/prot.20889

Effect of a mutation on the structure and dynamics of an α‐helical antifreeze protein in water and ice

2006· article· en· W2112634975 on OpenAlexafffund
Steffen P. Graether, Carolyn M. Slupsky, Brian D. Sykes

Bibliographic record

VenueProteins Structure Function and Bioinformatics · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsAntifreeze proteinGlobular proteinChemistryProtein structureMolecular dynamicsBiophysicsHelix (gastropod)Freezing pointCrystallographyPsychrophileProtein dynamicsBiologyBiochemistryPhysicsEcologyComputational chemistryThermodynamics

Abstract

fetched live from OpenAlex

One strategy of psychrophilic organisms to survive subzero temperature is to produce antifreeze protein (AFPs), which inhibit the growth of macromolecular ice. To better understand the binding mechanism, the structure and dynamics of several AFPs have been studied by nuclear magnetic resonance (NMR) and X-ray crystallography. The results have shown that different organisms can use diverse structures (alpha-helix, beta-helix, or different globular folds) to achieve the same function. A number of studies have focused on understanding the relationship between the alpha-helical structure of fish type I AFP and its function as an inhibitor of ice growth. The results have not explained whether the 90% activity loss caused by the conservative mutation of two threonines to serines (Thr13Ser/Thr24Ser) is attributable to a change in protein structure in solution or in ice. We examine here the structure and dynamics of the winter flounder type I AFP and the mutant Thr13Ser/Thr24Ser in both solution and solid states using a wide range of NMR approaches. Both proteins remain fully alpha-helical at all temperatures and in ice, demonstrating that the activity change must therefore not be attributable to changes in the protein fold or dynamics but differences in surface properties.

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 score0.165
Threshold uncertainty score0.190

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 head0.003
GPT teacher head0.181
Teacher spread0.178 · 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

Citations9
Published2006
Admission routes2
Has abstractyes

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