Immobilization of Lipid Vesicles on Polymer Support via an Amphiphilic Peptidic Anchor: Application to a Membrane Enzyme
Bibliographic record
Abstract
To immobilize lipid vesicles on a polymer support, we have used a peptidic anchor with the following sequence: Ala-Ala-Leu-Leu-Leu-Ala-Ala-Ala-Ala-Ala-Ala-Ala-Ala-Ala-Ala-Ala-Ala-A la-Ala-Ala-Ala-Ala-Ala-Ala-Trp-Lys-Lys-Lys-Lys-Lys-Lys. This amphiphilic peptide was previously designed in our group to interact spontaneously and strongly with vesicles without perturbing their permeability. At the end of the solid-phase peptide synthesis, the peptide was left on the polymer beads and this novel polymer-peptide system was used for vesicle immobilization. It was shown that this polymer-peptide system could immobilize as much as 200 micromol of lipids per gram of dry resin. The amount of immobilized vesicles was decreased by a reduction of the proportion of the negatively charged lipids in the vesicles, indicating the importance of electrostatic interactions in the immobilization of the vesicles. The integrity of the vesicles was mostly preserved after the immobilization. This new polymer-peptide system was used easily and successfully to immobilize a membrane-bound enzyme, gamma-glutamyl transpeptidase. The activity of the membrane-bound enzyme was studied by monitoring the release of p-nitroaniline. The activity of the enzyme was still retained, even after being re-used eight times, indicating the strong immobilization of the enzyme in its active form. The polymer-peptide support could be regenerated by washing with ethanol and reused.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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; both teacher heads agree on what is shown here.
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".