The effects of biological crowders on fibrillization, structure, diffusion, and conformational dynamics of α‐synuclein
Bibliographic record
Abstract
Abstract α‐synuclein is an intrinsically disordered protein (IDP) whose aggregation in presynaptic neuronal cells is a pathological hallmark of Lewy body formation and Parkinson's disease. This aggregation process is likely affected by the crowded macromolecular cellular environment. In this study, α‐synuclein was studied in the presence of both a synthetic crowder, Ficoll70, and a biological crowder composed of lysed cells that better mimics the biocomplexity of the cellular environment. 15 N‐ 1 H HSQC NMR results show similar α‐synuclein chemical shifts in non‐crowded and all crowded conditions implying that it remains similarly unstructured in all conditions. Nevertheless, both HSQC NMR and fluorescence measurements indicate that, only in the cell lysate, α‐synuclein forms aggregates over a timescale of 48 h. 15 N‐edited diffusion measurements indicate that all crowders slow down the α‐synuclein's diffusivity. Interestingly, at high concentrations, α‐synuclein diffuses faster in cell lysate than in Ficoll70, possibly due to additional soft (e.g., electrostatic or hydrophobic) interactions. 15 N‐edited relaxation measurements show that some residues are more mobile in cell lysate than in Ficoll70; the rates that are most different are predominantly in hydrophobic residues. We thus examined cell lysates with reduced hydrophobicity and found slower dynamics (higher relaxation rates) in several α‐synuclein residues. Taken together, these experiments suggest that while cell lysate does not substantially affect α‐synuclein structure (HSQC spectra), it does affect chain dynamics and translational diffusion, and strongly affects aggregation over a timescale of days, in a manner that is different from either no crowder or an artificial crowder: soft hydrophobic interactions are implicated.
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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 | 0.000 | 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".