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Record W3049094078 · doi:10.1042/bcj20200539

Crystal structure of an insect antifreeze protein reveals ordered waters on the ice-binding surface

2020· article· en· W3049094078 on OpenAlexafffund
Qilu Ye, Robert Eves, Robert L. Campbell

Bibliographic record

VenueBiochemical Journal · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsQueen's University
FundersCanadian Institutes of Health Research
KeywordsAntifreeze proteinIce crystalsCrystallographyCrystal structureChemistryAntifreezeBiologyBiochemistryPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

Antifreeze proteins (AFPs) are characterized by their ability to adsorb to the surface of ice crystals and prevent any further crystal growth. AFPs have independently evolved for this purpose in a variety of organisms that encounter the threat of freezing, including many species of polar fish, insects, plants and microorganisms. Despite their diverse origins and structures, it has been suggested that all AFPs can organize ice-like water patterns on one side of the protein (the ice-binding site) that helps bind the AFP to ice. Here, to test this hypothesis, we have solved the crystal structure at 2.05 Å resolution of an AFP from the longhorn beetle, Rhagium mordax with five molecules in the unit cell. This AFP is hyperactive, and its crystal structure resembles that of the R. inquisitor ortholog in having a β-solenoid fold with a wide, flat ice-binding surface formed by four parallel rows of mainly Thr residues. The key difference between these structures is that the R. inquisitor AFP crystallized with its ice-binding site (IBS) making protein-protein contacts that limited the surface water patterns. Whereas the R. mordax AFP crystallized with the IBSs exposed to solvent enabling two layers of unrestricted ordered surface waters to be seen. These crystal waters make close matches to ice lattice waters on the basal and primary prism planes.

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 categoriesInsufficient payload (model declined to judge)
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 score0.003
Threshold uncertainty score1.000

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)0.0010.000

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 head0.030
GPT teacher head0.222
Teacher spread0.192 · 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.

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

Citations29
Published2020
Admission routes2
Has abstractyes

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