Putting the pieces into place: Properties of intact zinc metallothionein 1A determined from interaction of its isolated domains with carbonic anhydrase
Bibliographic record
Abstract
Mammalian metallothioneins (MTs) bind up to seven Zn(2+) using a large number of cysteine residues relative to their small size and can act as zinc-chaperones. In metal-saturated Zn7-MTs, the seven zinc ions are co-ordinated tetrahedrally into two distinct clusters separated by a linker; the N-terminal β-domain [(Zn3Cys9)(3-)] and C-terminal α-domain [(Zn4Cys11)(3-)]. We report on the competitive zinc metalation of apo-carbonic anhydrase [CA; metal-free CA (apo-CA)] in the presence of apo-metallothionein 1A domain fragments to identify domain specific determinants of zinc binding and zinc donation in the intact two-domain Znn-βαMT1A (human metallothionein 1A isoform; n=0-7). The apo-CA is shown to compete effectively only with Zn2-3-βMT and Zn4-αMT. Detailed modelling of the ESI mass spectral data have revealed the zinc-binding affinities of each of the zinc-binding sites in the two isolated fragments. The three calculated equilibrium zinc affinities [log(KF)] of the isolated β-domain were: 12.2, 11.7 and 11.4 and the four isolated α-domain affinities were: 13.5, 13.2, 12.7 and 12.6. These data provide guidance in identification of the location of the strongest-bound and weakest-bound zinc in the intact two-domain Zn7βαMT. The β-domain has the weakest zinc-binding site and this is where zinc ions are donated from in the Zn7-βαMT. The α-domain with the highest affinity binds the first zinc, which we propose leads to an unscrambling of the cysteine ligands from the apo-peptide bundle. We propose that stabilization of the intact Zn6-MT and Zn7-MT, relative to that of the sum of the separated fragments, is due to the availability of additional cysteine ligand orientations (through interdomain interactions) to support the clustered structures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".