Arsenic Metalation of Seaweed <i>Fucus vesiculosus</i> Metallothionein: The Importance of the Interdomain Linker in Metallothionein
Bibliographic record
Abstract
The presence of metallothionein in seaweed Fucus vesiculosus has been suggested as the protecting agent against toxic metals in the contaminated waters it can grow in. We report the first kinetic pathway data for A3+ binding to an algal metallothionein, F. vesiculosus metallothionein (rfMT). The time and temperature dependence of the relative concentrations of apo-rfMT and the five As-containing species have been determined following mixing of As3+ and apo-rfMT using electrospray ionization mass spectrometry (ESI MS). Kinetic analysis of the detailed time-resolved mass spectral data for As3+ metalation allows the simulation of the metalation reactions showing the consumption of apo-rfMT, the formation and consumption of As1- to As4-rfMT, and subsequent, final formation of As5-rfMT. The kinetic model proposed here provides a stepwise analysis of the metalation reaction showing time-resolved occupancy of the Cys7 and the Cys9 domain. The rate constants (M(-1) s(-1)) calculated from the fits for the 7-cysteine gamma domain are k1gamma, 19.8, and k2gamma, 1.4, and for the 9-cysteine beta domain are k1beta, 16.3, k2beta, 9.1, and k3beta, 2.2. The activation energies and Arrhenius factors for each of the reaction steps are also reported. rfMT has a long 14 residue linker, which as we show from analysis of the ESI MS data, allows each of its two domains to bind As3+ independently of each other. The analysis provides for the first time an explanation of the differing metal-binding properties of two-domain MTs with linkers of varying lengths, suggesting further comparison between plant (with long linkers) and mammalian (with short linkers) metallothioneins will shed light on the role of the interdomain linker.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".