Conformational Changes and Association of Membrane-Interacting Peptides in Myelin Membrane Models: A Case of the C-Terminal Peptide of Proteolipid Protein and the Antimicrobial Peptide Melittin
Bibliographic record
Abstract
Model membranes composed of various lipid mixtures can segregate into liquid-ordered (Lo) and liquid-disordered (Ld) phases. In this study, lipid vesicles composed of mainly Lo or Ld phases as well as complex lipid systems representing the cytosolic leaflet of the myelin membrane were characterized by fluorescence resonance energy transfer with a donor/acceptor pair that preferentially partitioned into Lo or Ld phases, respectively. The fluidity of the lipid systems containing >30% cholesterol was modulated in the presence of the amphipathic peptide melittin. With all the studied lipid systems, melittin attained an α-helical conformation as determined by CD spectroscopy and attained varying degrees of membrane association and penetration as determined by intrinsic Trp fluorescence. The other protein domain utilized was a putative amphipathic helical peptide derived from the cytosolic C-terminal sequence of proteolipid protein (PLP) which is the most abundant protein in the myelin membrane. The C-terminal PLP peptide transitioned from a random coil to an α-helix in the presence of trifluoroethanol. Upon interacting with each of lipid vesicle system, the PLP peptide also folded into a helix; however, at high concentrations of the peptide with fluid lipid systems, associated helices transmuted into a β-sheet conformer. The membrane-associated aggregation of the cytosolic C-termini could be a mechanism by which the transmembrane PLP multimerizes in the myelin membrane.
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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".