Cu(I) binds to Zn7-MT2 via two parallel pathways
Bibliographic record
Abstract
Metallothionein proteins are essential for Cu(I) and Zn(II) homeostasis as well as heavy metal detoxification. The metallation properties of MT2 are of great interest due to their wide patterns of expression and correlation with multiple diseases including cancers, neurological disorders, and respiratory diseases. Use of isotopically pure 63Cu(I) and 68Zn(II) eliminates the complexity of the Cu, Zn-MT2 mass spectral peaks due to significant overlap of naturally abundant isotopes. This allows for the resolution of the precise Cu(I) and Zn(II) stoichiometries when both Cu(I) and Zn(II) are bound to MT2 at physiological pH as expected in vivo. Exact Cu: Zn ratios were determined from mass spectral simulations carried out for every point in the titration. We report that Cu(I) metallation of Zn7-MT2 can only be understood in terms of two pathways occurring in parallel with pathway ① resulting in Cu5Zn5-MT2 and Cu9Zn3-MT2. Pathway ② results in Cu6Zn4-MT2 and Cu10Zn2-MT2, which are the major products of the reaction. From the electrospray ionization (ESI)-mass spectral data we report a series of formation constants (KF) for species starting from Zn7-MT2 up to Cu11Zn2-MT2. Room temperature phosphorescence and circular dichroism (CD) spectra were measured in parallel with the ESI-mass spectrometry data allowing for the assignment of specific species to specific spectral bands. Through analysis of the CD spectral bands, we propose that Cu(I) binds to the β domain first to form a Cu5Zn1 cluster or Cu6 cluster with emission at 670 and 750 nm, respectively, leaving the Zn4 cluster in the α domain.
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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) | 0.002 | 0.001 |
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".