Oxidative pathways of apo, partially, and fully Zn(<scp>II</scp>)‐ and Cd(<scp>II</scp>)‐metalated human metallothionein‐3 are dominated by disulfide bond formation
Bibliographic record
Abstract
Oxidative stress is a key component of many diseases, including neurodegenerative diseases such as Alzheimer's disease. Reactive oxygen species (ROS) such as hydrogen peroxide and nitric oxide lead to disease progression by binding to proteins and causing their dysregulation. Metallothionein-3 (MT3), a cysteine-rich brain-located metalloprotein, has been proposed to be a key player in controlling oxidative stress in the central nervous system. We report data from a combination of electrospray ionization mass spectrometry (ESI-MS), ultraviolet (UV)-visible absorption spectroscopy, and circular dichroism spectroscopy that identify the oxidation pathway of MT3 fully bound to endogenous Zn(II) or exogenous Cd(II) together with the partially metalated species. We characterize the intermediate species formed during the oxidation of MT3, which is dominated by disulfide bond formation. We report the rates of oxidation. For both fully and partially metalated MT3, MT3 is oxidized at 5 to 10 times the rate of MT1, a similar but kidney-expressed isoform of MT. As oxidation progresses, MT3 follows a domain-specific demetallation pathway when it is fully metalated, and a domain-independent pathway when partially metalated. This suggests the presence of a significant susceptibility toward oxidation when MT3 is partially metalated, and, therefore, a possible protective role of Zn(II) when fully metalated. With the evidence for the rapid oxidation rate, our data support the proposals of MT3 as a key antioxidant in physiology.
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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".