Bibliographic record
Abstract
Metallothioneins (MT) are a family of small cysteine rich proteins, which since their discovery in 1957, have been implicated in a range of roles including toxic metal detoxification, protection against oxidative stress, and as a metallochaperone involved in the homeostasis of both zinc and copper. The most well studied member of the family is the mammalian metallothionein, which consists of two domains: a β-domain with 9 cysteine residues, which sequesters 3 Cd(2+) or Zn(2+) or 6 Cu(+) ions, and an α-domain with 11 cysteine residues and, which sequesters 4 Cd(2+) or Zn(2+) or 6 Cu(+) ions. Despite over half a century of research, the exact functions of MT are still unknown. Much of current research aims to elucidate the mechanism of metal binding, as well as to isolate intermediates in metal exchange reactions; reactions necessary to maintain homeostatic equilibrium. These studies further our understanding of the role(s) of this remarkable and ubiquitous protein. Recently, supermetallated forms of the protein, where supermetallation describes metallation in excess of traditional levels, have been reported. These species may potentially be the metal exchange intermediates necessary to maintain homeostatic equilibrium. This review focuses on recent advances in the understanding of the mechanistic properties of metal binding, the implications for the metal induced protein folding reactions proposed for metallothionein metallation, the value of "magic numbers", which we informally define as the commonly determined metal-to-protein stoichiometric ratios and the significance of the new supermetallated states of the protein and the possible interpretation of the structural properties of this new metallation status. Together we provide a commentary on current experimental and theoretical advances and frame our consideration in terms of the possible functions of MT.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".