Human apo-metallothionein 1a is not a random coil: Evidence from guanidinium chloride, high temperature, and acidic pH unfolding studies
Bibliographic record
Abstract
The structures of apo-metallothioneins (apo-MTs) have been relatively elusive due to their fluxional, disordered state which has been difficult to characterize. However, intrinsically disordered protein (IDP) structures are rather diverse, which raises questions about where the structure of apo-MTs fit into the protein structural spectrum. In this paper, the unfolding transitions of apo-MT1a are discussed with respect to the effect of the chemical denaturant GdmCl, temperature conditions, and pH environment. Cysteine modification in combination with electrospray ionization mass spectrometry was used to probe the unfolding transition of apo-MT1a in terms of cysteine exposure. Circular dichroism spectroscopy was also used to monitor the change in secondary structure as a function of GdmCl concentration. For both of these techniques, cooperative unfolding was observed, suggesting that apo-MT1a is not a random coil. More GdmCl was required to unfold the protein backbone than to expose the cysteines, indicating that cysteine exposure is likely an early step in the unfolding of apo-MT1a. MD simulations complement the experimental results, suggesting that apo-MT1a adopts a more compact structure than expected for a random coil. Overall, these results provide further insight into the intrinsically disordered structure of apo-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 | 0.000 | 0.001 |
| 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) | 0.000 | 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 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".