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Record W2556163884 · doi:10.1021/acs.biochem.6b00864

Multivalent Display of Antifreeze Proteins by Fusion to Self-Assembling Protein Cages Enhances Ice-Binding Activities

2016· article· en· W2556163884 on OpenAlexafffund
Sean Phippen, Corey A. Stevens, Tyler D. R. Vance, Neil P. King, David Baker, Peter L. Davies

Bibliographic record

VenueBiochemistry · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsQueen's University
FundersDivision of ChemistryDefense Advanced Research Projects AgencyCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaQueen's UniversityBill and Melinda Gates Foundation
KeywordsAntifreeze proteinIce crystalsChemistryAntifreezeRecrystallization (geology)MonomerBiophysicsFreezing pointProtein subunitNanoparticleBiochemistryCrystallographyPolymerBiologyNanotechnologyGeneOrganic chemistryMaterials science

Abstract

fetched live from OpenAlex

Antifreeze proteins (AFPs) are small monomeric proteins that adsorb to the surface of ice to inhibit ice crystal growth and impart freeze resistance to the organisms producing them. Previously, monomeric AFPs have been conjugated to the termini of branched polymers to increase their activity through the simultaneous binding of more than one AFP to ice. Here, we describe a superior approach to increasing AFP activity through oligomerization that eliminates the need for conjugation reactions with varying levels of efficiency. A moderately active AFP from a fish and a hyperactive AFP from an Antarctic bacterium were genetically fused to the C-termini of one component of the 24-subunit protein cage T33-21, resulting in protein nanoparticles that multivalently display exactly 12 AFPs. The resulting nanoparticles exhibited freezing point depression >50-fold greater than that seen with the same concentration of monomeric AFP and a similar increase in the level of ice-recrystallization inhibition. These results support the anchored clathrate mechanism of binding of AFP to ice. The enhanced freezing point depression could be due to the difficulty of overgrowing a larger AFP on the ice surface and the improved ice-recrystallization inhibition to the ability of the nanoparticle to simultaneously bind multiple ice grains. Oligomerization of these proteins using self-assembling protein cages will be useful in a variety of biotechnology and cryobiology 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 score0.002
Threshold uncertainty score0.353

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 head0.010
GPT teacher head0.228
Teacher spread0.219 · 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
Published2016
Admission routes2
Has abstractyes

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