Adhesion mechanism in a DOPA-deficient foot protein from green mussels
Bibliographic record
Abstract
The holdfast or byssus of Asian green mussels, Perna viridis, contains a foot protein, pvfp-1, that differs in two respects from all other known adhesive mussel foot proteins (mfp): (1) instead of the hallmark L-3,4-dihydroxyphenylalanine (DOPA) residues in mfp-1, for example, pvfp-1 contains C(2)-mannosyl-7-hydroxytryptophan (Man7OHTrp). (2) In addition, pvfp-1 chains are not monomeric like mfp-1 but trimerized by collagen and coiled-coil domains near the carboxy terminus after a typical domain of tandemly repeated decapeptides. Here, the contribution of these peculiarities to adhesion was examined using a surface forces apparatus (SFA). Unlike previously studied mfp-1s, pvfp-1 showed significant adhesion to mica and, in symmetric pvfp-1 films, substantial cohesive interactions were present at pH 5.5. The role of Man7OHTrp in adhesion is not clear, and a DOPA-like role for Man7OHTrp in metal complexation (e.g., Cu(2+), Fe(3+)) was not observed. Instead, cation-π interactions with low desolvation penalty between Man7OHTrp and lysyl side chains and conformational changes (raveling and unraveling of collagen helix and coiled-coil domains) are the best explanations for the strong adhesion between pvfp-1 monomolecular films. The strong adhesion mechanism induced by cation-π interactions and conformational changes in pvfp-1 provides new insights for the development of biomimetic underwater adhesives.
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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".