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Record W2093951019 · doi:10.1021/ac902633d

Direct Quantification of Protein−Metal Ion Affinities by Electrospray Ionization Mass Spectrometry

2010· letter· en· W2093951019 on OpenAlexaff
Lu Deng, Nian Sun, Elena N. Kitova, John S. Klassen

Bibliographic record

VenueAnalytical Chemistry · 2010
Typeletter
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsAlberta Glycomics CentreUniversity of Alberta
Fundersnot available
KeywordsChemistryAffinitiesElectrospray ionizationMass spectrometryChromatographyProtein mass spectrometryElectrosprayTop-down proteomicsSample preparation in mass spectrometryMetalAnalytical Chemistry (journal)Organic chemistryStereochemistry

Abstract

fetched live from OpenAlex

The application of the direct electrospray ionization mass spectrometry (ES-MS) assay for quantifying the stoichiometry and absolute affinity of protein-metal ion binding in vitro is described. Control ES-MS experiments performed on solutions containing calcium chloride or calcium acetate and a pair of proteins that do not bind calcium ions in solution revealed that the nonspecific association of metal ions to proteins during ES is a random process, independent of protein size and structure. These results establish the reliability of the reference protein method for quantitatively correcting ES mass spectra for the occurrence of nonspecific metal ion binding to proteins during ES-MS analysis. To demonstrate the utility of the direct ES-MS assay, when carried out using the reference protein method, the calcium binding stoichiometry of bovine alpha-lactalbumin and the calcium ion affinity of bovine beta-lactoglobulin were established.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.808
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0130.000

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 head0.011
GPT teacher head0.243
Teacher spread0.232 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreOther

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

Citations39
Published2010
Admission routes1
Has abstractyes

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