Small molecule sequestration of amyloid-β as a drug discovery strategy for Alzheimer’s disease
Bibliographic record
Abstract
Abstract Disordered proteins are challenging therapeutic targets, and no drug is currently in clinical use that has been shown to modify the properties of their monomeric states. Here, we identify a small molecule capable of binding and sequestering the amyloid-β peptide (Aβ) in its monomeric, soluble state. Our analysis reveals that this compound interacts with Aβ and inhibits both the primary and secondary nucleation pathways in its aggregation process. We characterise this interaction using biophysical experiments and integrative structural ensemble determination methods. We thus observe that this small molecule has the remarkable effect of increasing the conformational entropy of monomeric Aβ while decreasing its hydrophobic surface area. We then show that this small molecule rescues a Caenorhabditis elegans model of Aβ-associated toxicity in a manner consistent with the mechanism of action identified from the in silico and in vitro studies. These results provide an illustration of the strategy of targeting the monomeric states of disordered proteins with small molecules to alter their behaviour for therapeutic purposes.
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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) | 0.001 | 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".