Different folding mechanisms in prion proteins from mammals with different disease susceptibility observed at the single-molecule level
Bibliographic record
Abstract
Misfolding of the protein PrP causes prion diseases in mammals. Disease susceptibility varies widely among species, despite PrP sequences differing by only a few amino acids. How these differences alter PrP folding and misfolding remains unclear. We compared the folding dynamics of single PrP molecules from three species with different disease susceptibility: dogs (immune), hamsters (susceptible), and bank voles (extremely susceptible). Measurements with optical tweezers revealed important differences between the folding cooperativity, pathways, energy barriers, and kinetics of these proteins. In contrast to the two-state folding of hamster PrP, dog PrP always folded through multiple intermediates. However, both featured rapid native folding, homogeneous energy barriers, and no readily observable misfolding. Bank vole PrP also folded via intermediates, but more slowly and via inhomogeneous barriers. Most notably, it formed several metastable misfolded states starting from the unfolded state. Analyzing the sequence of intermediates seen in pulling curves, we found significant differences in the folding pathways for dog and bank vole PrP, implying that sequence mutations altered energy barriers so as to redirect folding pathways. These results show that subtle differences in PrP sequence between species produce profound changes in folding behavior, providing insight into the factors underlying misfolding propensity.
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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".