Applying Hsp104 to protein-misfolding disordersThis paper is one of a selection of papers published in this special issue entitled 8th International Conference on AAA Proteins and has undergone the Journal's usual peer review process.
Bibliographic record
Abstract
Hsp104, a hexameric AAA+ ATPase found in yeast, transduces energy from cycles of ATP binding and hydrolysis to resolve disordered protein aggregates and cross-beta amyloid conformers. These disaggregation activities are often co-ordinated by the Hsp70 chaperone system and confer considerable selective advantages. First, renaturation of aggregated conformers by Hsp104 is critical for yeast survival after various environmental stresses. Second, amyloid remodeling by Hsp104 enables yeast to exploit multifarious prions as a reservoir of beneficial and heritable phenotypic variation. Curiously, although highly conserved in plants, fungi and bacteria, Hsp104 orthologues are absent from metazoa. Indeed, metazoan proteostasis seems devoid of a system that couples protein disaggregation to renaturation. Here, we review recent endeavors to enhance metazoan proteostasis by applying Hsp104 to the specific protein-misfolding events that underpin two deadly neurodegenerative amyloidoses. Hsp104 potently inhibits Abeta42 amyloidogenesis, which is connected with Alzheimer's disease, but appears unable to disaggregate preformed Abeta42 fibers. By contrast, Hsp104 inhibits and reverses the formation of alpha-synuclein oligomers and fibers, which are connected to Parkinson's disease. Importantly, Hsp104 antagonizes the degeneration of dopaminergic neurons induced by alpha-synuclein misfolding in the rat substantia nigra. These studies raise hopes for developing Hsp104 as a therapeutic agent.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".