Mass Spectrometric Determination of the Coordination Geometry of Potential Copper(II) Surrogates for the Mammalian Prion Protein Octarepeat Region
Bibliographic record
Abstract
The N-terminal domain of mammalian prion proteins contains several tandem repeats of the octapeptide PHGGGWGQ, each one capable of selectively binding up to 1 equiv of Cu2+. Under saturating conditions Cu2+ is known to coordinate the HGG portion of the repeat sequence via the histidine imidazole side chain, two deprotonated amide N-atoms, and a backbone carbonyl O-atom. Using appropriate selection criteria, we have generated a short list of candidate metal ions (Co3+, Ni2+, Pd2+, Pt2+) that can serve as potential surrogates for Cu2+. The selected metal ions were screened for binding interactions with the OR-derived peptide fragment AcHGGGWNH2 (Ac = acetyl, amino acid residues in italics) using electrospray ionization mass spectrometry. The coordination geometries of these metal ions with the synthetic OR peptide were subsequently determined from fragment analysis using collision-induced dissociation tandem mass spectrometry. Our results indicate that, although Co3+, Pd2+, and Pt2+ all bind to the OR fragment via the peptide backbone to varying extents, each of these metal ions appears to associate with the peptide in a unique manner, which is distinct from the way in which Cu2+ is coordinated. This work illustrates the extremely strong selectivity for Cu2+ of this highly conserved region of the mammalian prion protein.
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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".