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Record W2607465082 · doi:10.1039/c7mt00041c

Stepwise copper(<scp>i</scp>) binding to metallothionein: a mixed cooperative and non-cooperative mechanism for all 20 copper ions

2017· article· en· W2607465082 on OpenAlexafffund
Judith S. Scheller, Gordon W. Irvine, Daisy L. Wong, A. Hartwig, Martin J. Stillman

Bibliographic record

VenueMetallomics · 2017
Typearticle
Languageen
FieldNursing
TopicTrace Elements in Health
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCopperChemistryMetallothioneinCircular dichroismElectrospray ionizationMetalloproteinCrystallographyMetalZincCysteineBinding siteMass spectrometryInorganic chemistryBiochemistryChromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

Copper is a ubiquitous trace metal of vital importance in that it serves as a cofactor in many metalloenzymes. Excess copper becomes harmful if not sequestered appropriately in the cell. As a metal ion chaperone, metallothionein (MT) has been proposed as a key player in zinc and copper homeostasis within the cell. The underlying mechanisms by which MT sequesters and transfers copper ions, and subsequently achieves its proposed biological function remain unknown. Using a combination of electrospray ionization mass spectrometry (ESI-MS), circular dichroism (CD), and emission spectroscopy, we report that the Cu(i) to human apo-MT1a binding mechanism is highly pH-dependent. The 20 relative Kf-values for the binding of 1 to 20 Cu(i) to the 20 cysteines of MT were obtained from computational simulation of the experimental mass spectral results. These data identified the pH-dependent formation of three sequential but completely different Cu–SCYS clusters, as a function of Cu(i) loading. These data provide the first overall sequence for Cu(i) binding in terms of domain specificity and transient binding site structures. Under cooperative binding at pH 7.4, a series of four clusters form: Cu4SCYS-6, followed by Cu6SCYS-9 (β), then a second Cu4SCYS-6 (α), and finally Cu7SCYS-x (α) (x = up to 11). Upon further addition of Cu(i), a mixture of species is formed in a non-cooperative mechanism, saturating the 20 cysteines of MT1a. Using benzoquinone, a cysteine modifier, we were able to confirm that Cu6SCYS-9 formed solely in the N-terminal β-domain, as well as confirming the existence of the presumed Cu4SCYS-6 cluster in the α-domain. Based on the results of ESI-MS and computational simulation we were able to identify Cu:MT speciation that resulted in specific emission and CD spectral properties. Speciation resulting from 20 bimolecular, sequential reactions involving 20 Cu(i) ions binding to metallothionein at different pH-values is reported.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.046
GPT teacher head0.333
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations48
Published2017
Admission routes2
Has abstractyes

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