Molecular Mechanism for the (−)-Epigallocatechin Gallate-Induced Toxic to Nontoxic Remodeling of Aβ Oligomers
Bibliographic record
Abstract
(−)-Epigallocatechin gallate (EGCG) effectively reduces the cytotoxicity of the Alzheimer’s disease β-amyloid peptide (Aβ) by remodeling seeding-competent Aβ oligomers into off-pathway seeding-incompetent Aβ assemblies. However, the mechanism of EGCG-induced remodeling is not fully understood. Here we combine 15 N and 1 H dark-state exchange saturation transfer (DEST), relaxation, and chemical shift projection NMR analyses with fluorescence, dynamic light scattering, and electron microscopy to elucidate how EGCG remodels Aβ oligomers. We show that the remodeling adheres to a Hill–Scatchard model whereby the Aβ(1–40) self-association occurs cooperatively and generates Aβ(1–40) oligomers with multiple independent binding sites for EGCG with a K d ∼10-fold lower than that for the Aβ(1–40) monomers. Upon binding to EGCG, the Aβ(1–40) oligomers become less solvent exposed, and the β-regions, which are involved in direct monomer–protofibril contacts in the absence of EGCG, undergo a direct-to-tethered contact shift. This switch toward less engaged monomer–protofibril contacts explains the seeding incompetency observed upon EGCG remodeling and suggests that EGCG interferes with secondary nucleation events known to generate toxic Aβ assemblies. Unexpectedly, the N-terminal residues experience an opposite EGCG-induced shift from tethered to direct contacts, explaining why EGCG remodeling occurs without release of Aβ(1–40) monomers. We also show that upon binding Aβ(1–40) oligomers the relative positions of the EGCG B and D rings change with respect to that of ring A. These distinct structural changes occurring in both Aβ(1–40) oligomers and EGCG during remodeling offer a foundation for understanding the molecular mechanism of EGCG as a neurotoxicity inhibitor. Furthermore, the results reported here illustrate the effectiveness of DEST-based NMR approaches in investigating the mechanism of low-molecular-weight amyloid inhibitors.
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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".