A rapid in vivo pipeline to identify small molecule inhibitors of amyloid aggregation
Bibliographic record
Abstract
Amyloids are associated with over 50 human diseases and have inspired significant effort to identify small molecule remedies. Here, we present an in vivo platform that efficiently yields small molecule inhibitors of amyloid formation. We previously identified small molecules that kill the nematode C. elegans by forming membrane-piercing crystals in the pharynx cuticle, which is rich in amyloid-like material. We show here that many of these molecules are known amyloid-binders whose crystal-formation in the pharynx can be blocked by amyloid-binding dyes. We asked whether this phenomenon could be exploited to identify molecules that interfere with the ability of amyloids to seed higher-order structures. We therefore screened 2560 compounds and found 85 crystal suppressors, 47% of which inhibit amyloid formation. This hit rate far exceeds other screening methodologies. Hence, in vivo screens for suppressors of crystal formation in C. elegans can efficiently reveal small molecules with amyloid-inhibiting potential. In this work, Kamal, Knox et al develop a high-throughput system to identify small molecules that disrupt amyloid formation by pre-selecting compounds that suppress molecular interactions within the cuticle of the C. elegans pharynx.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".