Probing the Reversible Fe<sup>3+</sup>–DOPA-Mediated Bridging Interaction in Mussel Foot Protein-1
Bibliographic record
Abstract
Mussel wet adhesion mechanisms have attracted much research interest and have been studied through nanomechanical measurements over the past decade. In this work, the self-healing process of Fe 3+ -mediated bridging interaction in mussel foot protein-1 (mfp-1) is investigated at theory level of B3LYP/LACVP* using Gaussian 09. The computational results in the gas phase show that strong adhesion is present between ferric ions and 3,4-dihydroxyphenylalanine (DOPA) ligands, and the complex [Fe(DOPA) 3 ] 3– is most inclined to break through a route during which one DOPA dissociates from the iron center via tandem cleavage of two Fe–O bonds. Considering the effects of solvent molecules (i.e., water), [Fe(DOPA) 3 ] 3– bounded by three water molecules can satisfy the saturated coordination of the iron atom in order to compensate the entropic penalty that is induced by the increase of water molecules. The retrieving process of [Fe(DOPA) 2 ] − ·2H 2 O and (DOPA) 2– ·H 2 O is a thermodynamically spontaneous process as compared with the breaking process of [Fe(DOPA) 3 ] 3–, which is the main driving interaction for the reconstruction of [Fe(DOPA) 3 ] 3– and the self-healing of mfp-1. In addition, hydrogen bonding interactions between water and [Fe(DOPA) 3 ] 3– can effectively facilitate the reversible cohesion between two mfp-1 layers, enhancing the mechanical strength and stability of the mytilus byssal cuticle. The computational results are in good agreement with our previous surface force measurements and provide insights into the design and development of DOPA-mediated self-healing materials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 teacher head, 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".