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Record W2403404860 · doi:10.1021/acs.biochem.5b00452

Domain Selection in Metallothionein 1A: Affinity-Controlled Mechanisms of Zinc Binding and Cadmium Exchange

2015· article· en· W2403404860 on OpenAlexafffund
Tyler B. J. Pinter, Gordon W. Irvine, Martin J. Stillman

Bibliographic record

VenueBiochemistry · 2015
Typearticle
Languageen
FieldNursing
TopicTrace Elements in Health
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Saskatchewan
KeywordsChemistryCadmiumMetallothioneinZincMetalBinding siteDivalentStereochemistryBiophysicsBiochemistryOrganic chemistryBiology

Abstract

fetched live from OpenAlex

Mammalian metallothioneins (MTs) are small, metal binding proteins implicated in cellular metal ion homeostasis and heavy metal detoxification. Divalent, metal-saturated MTs form two distinct domains; the N-terminal β domain binds three metals using nine Cys residues, and the C-terminal α domain binds four metals with 11 Cys residues. Domain selection during zinc binding and cadmium exchange to human MT1A was examined using a series of competition reactions with mixtures of the isolated domain fragments. These experiments were conducted at two biologically significant pH conditions where MTs exist in vivo. Neither zinc binding nor cadmium exchange showed any significant degree of specificity or selectivity based on detailed analysis of electrospray ionization mass spectrometric and circular dichroic data. Under acidic conditions, zinc binding and cadmium exchange showed slight α domain selectivity because of the increased preference for cooperative clustering of the α domain. Modeling of the reactions showed that at both physiological (7.4) and acidic (5.8) pHs, zinc binding and cadmium exchanges occur essentially randomly between the two fragments. The metal binding affinity distributions between the domain fragments are comingled and not significantly separated as required for a domain specific mechanism. The models show rather that the order of the binding events follows the order of the binding affinities that are distributed across both domains and that this can be considered quantitatively by the KF(Cd)/KF(Zn) binding constant ratio for each metal bound.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.006
Threshold uncertainty score0.671

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.290
Teacher spread0.265 · 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 teacher head, 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

Citations26
Published2015
Admission routes2
Has abstractyes

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