Antifreeze protein from shorthorn sculpin: Identification of the ice‐binding surface
Bibliographic record
Abstract
Shorthorn sculpins, Myoxocephalus scorpius, are protected from freezing in icy seawater by alanine-rich, alpha-helical antifreeze proteins (AFPs). The major serum isoform (SS-8) has been reisolated and analyzed to establish its correct sequence. Over most of its length, this 42 amino acid protein is predicted to be an amphipathic alpha-helix with one face entirely composed of Ala residues. The other side of the helix, which is more heterogeneous and hydrophilic, contains several Lys. Computer simulations had suggested previously that these Lys residues were involved in binding of the peptide to the [11-20] plane of ice in the <-1102> direction. To test this hypothesis, a series of SS-8 variants were generated with single Ala to Lys substitutions at various points around the helix. All of the peptides retained significant alpha-helicity and remained as monomers in solution. Substitutions on the hydrophilic helix face at position 16, 19, or 22 had no obvious effect, but those on the adjacent Ala-rich surface at positions 17, 21, and 25 abolished antifreeze activity. These results, with support from our own modeling and docking studies, show that the helix interacts with the ice surface via the conserved alanine face, and lend support to the emerging idea that the interaction of fish AFPs with ice involves appreciable hydrophobic interactions. Furthermore, our modeling suggests a new N terminus cap structure, which helps to stabilize the helix, whereas the role of the lysines on the hydrophilic face may be to enhance solubility of the protein.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".