2011 CCNP Heinz Lehman Award paper: Searching for an endogenous anti-Alzheimer molecule: identifying small molecules in the brain that slow Alzheimer disease progression by inhibition of β-amyloid aggregation
Bibliographic record
Abstract
BACKGROUND: Alzheimer disease is a neurodegenerative disorder that progresses with marked interindividual clinical variability. We postulate the existence of endogenous molecules within the human brain exerting an antiaggregant activity that will prevent/slow Alzheimer disease progression. METHODS: We performed in silico studies to determine if the small endogenous molecules L-phosphoserine (L-PS) and 3-hydroxyanthranilic acid (3-HAA) could bind to the target region of ß-amyloid responsible for protein misfolding. In vitro assays measured the antiaggregation effect of these molecules at varying concentrations. RESULTS: In silico studies demonstrated that L-PS and 3-HAA, both endogenous brain molecules, were capable of binding to the histidine(13)-histidine-glutamine-lysine(16) (HHQK) region of ß-amyloid involved in misfolding: these interactions were energetically favoured. The in vitro assays showed that both L-PS and 3-HAA were capable of inhibiting ß-amyloid aggregation in a dose-dependent manner, with 3-HAA being more potent than L-PS. LIMITATIONS: Studies were performed in silico and in vitro but not in vivo. CONCLUSION: We successfully identified 2 endogenous brain molecules, L-PS and 3-HAA, that were capable of binding to the region of ß-amyloid that leads to protein misfolding and neurotoxicity. Both L-PS and 3-HAA were able to inhibit ß-amyloid aggregation in varying concentrations; levels of these compounds in the brain may impact their effectiveness in slowing/preventing ß-amyloid aggregation.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.250 | 0.091 |
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".