Response to crowded conditions reveals compact nucleus for amyloid formation of folded protein
Bibliographic record
Abstract
Abstract Although the consequences of the crowded cell environments may affect protein folding, function and misfolding reactions, these processes are often studied in dilute solutions in vitro. We here used biophysical experiments to investigate the amyloid fibril formation process of the fish protein apo-β-parvalbumin in solvent conditions that mimic steric and solvation aspects of the in vivo milieu. Apo-β-parvalbumin is a folded protein that readily adopts an amyloid state via a nucleation–elongation mechanism. Aggregation experiments in the presence of macromolecular crowding agents (probing excluded volume, entropic effects) as well as small molecule osmolytes (probing solvation, enthalpic effects) revealed that both types of agents accelerate overall amyloid formation, but the elongation step was faster with macromolecular crowding agents but slower in the presence of osmolytes. The observations can be explained by the steric effects of excluded volume favoring assembled states and that amyloid nucleation does not involve monomer unfolding. In contrast, the solvation effects due to osmolyte presence promote nucleation but not elongation. Therefore, the amyloid-competent nuclei must be compact with less osmolytes excluded from the surface than either the folded monomers or amyloid fibers. We conclude that, in contrast to other amyloidogenic folded proteins, amyloid formation of apo-β-parvalbumin is accelerated by crowded cell-like conditions due to a nucleation process that does not involve large-scale protein unfolding.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".