Insights into the Oxygen-Based Ligand of the Low pH Component of the Cu<sup>2+</sup>-Amyloid-β Complex
Bibliographic record
Abstract
In spite of significant experimental effort dedicated to the study of Cu(2+) binding to the amyloid beta (Aβ) peptide, involved in Alzheimer's disease, the nature of the oxygen-based ligand in the low pH component of the Cu(2+)-Aβ(1-16) complex is still under debate. This study reports density-functional-theory-based calculations that explore the potential energy surface of Cu(2+) complexes including N and O ligands at the N-terminus of the Aβ peptide, with a focus on evaluating the role of Asp1 carboxylate in copper coordination. Model conformers including 3, 6, and 17 amino acids have been used to systematically study several aspects of the Cu(2+)-coordination such as the Asp1 side chain conformation, local peptide backbone geometry, electrostatic and/or hydrogen bond interactions, and number and availability of Cu(2+) ligands. Our results show that the Asp1 peptide carbonyl binds to Cu(2+) only if the coordination number is less than four. In contrast, if four ligands are available, the most stable structures include the Asp1 carboxylate in equatorial position instead of the Asp1 carbonyl group. The two lowest energy Cu(2+)-Aβ(1-17) models involve Asp1 COO(-), the N-terminus, and His6 and His14 as equatorial ligands, with either a carbonyl or a water molecule in the axial position. These models are in good agreement with experimental data reported for component I of the Cu(2+)-Aβ(1-16) complex, including EXAFS- and X-ray-derived Cu(2+)-ligand distances, Cu(2+) EPR parameters, and (14)N and (13)C superhyperfine couplings. Our results suggest that at low pH, Cu(2+)-Aβ species with Asp1 carboxylate equatorial coordination coexist with species coordinating the Asp1 carbonyl. Understanding the bonding mechanism in these species is relevant to gain a deeper insight on the molecular processes involving copper-amyloid-β complexes, such as aggregation and redox activity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".