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Record W2020771312 · doi:10.1111/febs.12332

Characterizing rapid, activity‐linked conformational transitions in proteins via sub‐second hydrogen deuterium exchange mass spectrometry

2013· review· en· W2020771312 on OpenAlexaff
Diana Resetca, Derek J. Wilson

Bibliographic record

VenueFEBS Journal · 2013
Typereview
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsYork University
Fundersnot available
KeywordsHydrogen–deuterium exchangeChemistryMass spectrometryMicrofluidicsElectrospray ionizationFolding (DSP implementation)Protein foldingQuenching (fluorescence)Analytical Chemistry (journal)NanotechnologyChromatographyMaterials scienceFluorescenceBiochemistryPhysics

Abstract

fetched live from OpenAlex

This review outlines the application of time-resolved electrospray ionization mass spectrometry (TRESI-MS) and hydrogen-deuterium exchange (HDX) to study rapid, activity-linked conformational transitions in proteins. The method is implemented on a microfluidic chip which incorporates all sample-handling steps required for a 'bottom-up' HDX workflow: a capillary mixer for sub-second HDX labeling, a static mixer for HDX quenching, a microreactor for rapid protein digestion, and on-chip electrospray. By combining short HDX labeling pulses with rapid digestion, this approach provides a detailed characterization of the structural transitions that occur during protein folding, ligand binding, post-translational modification and catalytic turnover in enzymes. This broad spectrum of applications in areas largely inaccessible to conventional techniques means that microfluidics-enabled TRESI-MS/HDX is a unique and powerful approach for investigating the dynamic basis of protein function.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0410.000

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 head0.033
GPT teacher head0.286
Teacher spread0.253 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations40
Published2013
Admission routes1
Has abstractyes

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