Bepridil and Amiodarone Simultaneously Target the Alzheimer's Disease - and -Secretase via Distinct Mechanisms
Bibliographic record
Abstract
The two proteases beta-secretase and gamma-secretase generate the amyloid beta peptide and are drug targets for Alzheimer's disease. Here we tested the possibility of targeting the cellular environment of beta-secretase cleavage instead of the beta-secretase enzyme itself. beta-Secretase has an acidic pH optimum and cleaves the amyloid precursor protein in the acidic endosomes. We identified two drugs, bepridil and amiodarone, that are weak bases and are in clinical use as calcium antagonists. Independently of their calcium-blocking activity, both compounds mildly raised the membrane-proximal, endosomal pH and inhibited beta-secretase cleavage at therapeutically achievable concentrations in cultured cells, in primary neurons, and in vivo in guinea pigs. This shows that an alkalinization of the cellular environment could be a novel therapeutic strategy to inhibit beta-secretase. Surprisingly, bepridil and amiodarone also modulated gamma-secretase cleavage independently of endosomal alkalinization. Thus, both compounds act as dual modulators that simultaneously target beta- and gamma-secretase through distinct molecular mechanisms. In addition to Alzheimer's disease, compounds with dual properties may also be useful for drug development targeting other membrane proteins.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".