Vibrational Circular Dichroism Reveals Supramolecular Chirality Inversion of α-Synuclein Peptide Assemblies upon Interactions with Anionic Membranes
Bibliographic record
Abstract
Parkinson’s disease is an incurable neurodegenerative disorder caused by the aggregation of α-synuclein (AS). This amyloid protein contains a 12-residue-long segment, AS 71–82, that triggers AS pathological aggregation. This peptide is then essential to better understand the polymorphism and the dynamics of formation of AS fibrillar structures. In this work, vibrational circular dichroism showed that AS 71–82 is random coil in solution and forms parallel β-sheet fibrillar aggregates in the presence of anionic vesicles. Vibrational circular dichroism, with transmission electronic microscopy, revealed that the fibrillar structures exhibit a nanoscale tape-like morphology with a preferential supramolecular helicity. Whereas the structure handedness of some other amyloid peptides has been shown to be driven by pH, that of AS 71–82 is controlled by peptide concentration and peptide-to-lipid (P:L) molar ratio. At low concentrations and low P:L molar ratios, AS 71–82 assemblies have a left-twisted handedness, whereas at high concentrations and high P:L ratios, a right-twisted handedness is adopted. Left-twisted assemblies interconvert into right-twisted ones with time, suggesting a maturation of the amyloid structures. As fibril species with two chiralities have also been reported previously in Parkinson’s disease Lewy bodies and fibrils, the present results seem relevant to better understand AS amyloid assembly and fibrillization in vivo . From a diagnosis or therapeutic point of view, it becomes essential that future fibril probes, inhibitors, or breakers target pathological assemblies with specific chirality and morphology, in particular, because they may change with the stage of the disease.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".