Model Peptides Uncover the Role of the β-Secretase Transmembrane Sequence in Metal Ion Mediated Oligomerization
Bibliographic record
Abstract
The β-secretase or β-site amyloid precursor protein cleaving enzyme 1 (BACE1) is the enzyme responsible for the formation of amyloid-β peptides, which have a major role in Alzheimer pathogenesis. BACE1 has a transmembrane sequence (TMS), which makes it unique among related proteases. We noticed that the BACE1 TMS contains an uncommon sulfur-rich motif. The sequence MxxxCxxxMxxxCxMxC spans the entire TMS, resembles metal ion binding motifs, and is highly conserved among homologues. We used a synthetic 31-mer model peptide comprising the TMS to study metal ion binding and oligomerization. Applying diverse biochemical and biophysical techniques, we detected dimer and trimer formation of the TMS peptide with copper ions. Replacement of the central Cys466 by Ala essentially abolished these effects. We show that the peptide undergoes a redox reaction with copper ions resulting in a disulfide bridge involving Cys466. Further, we find peptide trimerization that depends on the presence of monovalent copper ions and the sulfhydryl group of Cys466. We identified Cys466 as a key residue for metal ion chelation and to be the core of an oligomerization motif of the BACE1-TMS peptide. Our results demonstrate a novel metal ion controlled oligomerization of the BACE1 TMS, which could have an enormous therapeutic importance against Alzheimer disease.
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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".