Kinetic and molecular dynamics studies on the metal‐dependent folding of metallothionein (MT)
Bibliographic record
Abstract
Metal‐induced chelation is the driving force for the folding of the α and β domains of MT, however, the exact mechanism is unknown. Elucidation of this mechanistic process extends beyond MT to encompass other metalloproteins that rely on metal coordination to achieve a properly folded conformation. In this study, kinetic measurements were made of the metallation reaction to the individual domains of MT using stopped‐flow (SF) spectroscopy. Metal coordination was monitored by UV absorption at 250 nm corresponding to the ligand‐to‐metal charge transfer of the cysteinyl sulfur to the Cd 2+ ion. The metallation reaction was complete within the 2 ms dead time of the instrument at low temperature (8 °C) and low concentration (1.25 μM). This fast rate of reaction was confirmed using SF‐circular dichroism spectroscopy on the α fragment of MT. Molecular modeling was used to investigate the behavior of the protein backbone upon demetallation and to search for stable peptide conformations in the metal‐free state. The molecular dynamics (MM3) calculations showed an increase in the number of H‐bonds upon sequential demetallation suggesting possible structural stabilization via a H‐bonding network. In addition, the MD calculations showed movement of the Cys side chains from the inside of the domain core when in the metallated state to the outside surface upon metal removal. Financial support provided by NSERC (equipment/operating to MJS and Post‐Graduate Scholarships A & D to KERD) and ADF at UWO.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".