Probing Alzheimer amyloid peptide aggregation using a cell-free fluorescent protein refolding method
Bibliographic record
Abstract
Fibrillation of the Alzheimer beta-amyloid peptide (Abeta) and (or) formation of toxic oligomers are key pathological events in Alzheimer's disease. Several strategies have been introduced to identify small molecule aggregation inhibitors, and based on these methods, a number of aggregation inhibitors have been identified. However, most of these methods use chemically synthesized Abeta42 peptides, which are difficult to maintain in a monomeric state at neutral pH where anti-aggregation screening is usually carried out. We have developed a cell-free Abeta42 aggregation assay based on fluorescence protein refolding. This assay utilizes nanomolar concentrations of protein. We genetically fused Abeta42 to the N-terminus of vYFP, a variant of of GFP, and expressed and purified the folded fusion protein. The refolding efficiency of Abeta42-vYFP fusion was inversely correlated with the solubility of Abeta42. Using fluorescence to monitor refolding of Abeta42-vYFP, we confirmed that Zn2+ binds to Abeta42 and increases its aggregation. The IC50 value estimated for Zn binding is 3.03 +/- 0.65 micromol/L. We also show that this technique is capable of monitoring the aggregation of chemically synthesized Abeta42.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".