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Record W2123218964 · doi:10.1002/mas.10044

Protein‐folding kinetics and mechanisms studied by pulse‐labeling and mass spectrometry

2003· review· en· W2123218964 on OpenAlexaff
Lars Konermann, Douglas A. Simmons

Bibliographic record

VenueMass Spectrometry Reviews · 2003
Typereview
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsWestern University
Fundersnot available
KeywordsChemistryProtein foldingFolding (DSP implementation)Hydrogen–deuterium exchangeMass spectrometryKineticsIsotopic labelingChromatographyBiochemistry

Abstract

fetched live from OpenAlex

Abstract I. Introduction 2 A. The Protein‐Folding Problem 2 B. Protein‐Folding Mechanisms 3 C. The Role of Folding Intermediates 3 II. Studies on Protein‐Folding Intermediates by Isotopic Pulse‐Labeling 5 A. Continuous Isotopic Labeling 6 B. Isotopic Pulse‐Labeling 7 1. Pulse‐Labeling in Quench‐Flow Experiments 7 2. Pulse Intensity 9 3. Possible Artifacts in Pulse‐Labeling Experiments 9 C. Obligatory Intermediates and Parallel Folding Pathways: Studies by Quench‐Flow Pulsed HDX and ESI‐MS 10 1. Lysozyme 10 2. Interleukin‐1β 10 3. Apo‐Myoglobin 10 D. Analysis of Isotopically Pulse‐Labeled Proteins by Proteolytic Digestion/MS 12 1. Principles 12 2. Cytochrome c 12 E. Pulse‐Labeling with On‐Line ESI‐MS Analysis 13 1. ESI‐MS as a Probe for Conformational Changes and Non‐Covalent Interactions 13 2. Time‐Resolved ESI‐MS 14 3. Time‐Resolved ESI‐MS with On‐Line Isotopic Pulse‐Labeling 14 4. The Mechanism of Myoglobin Reconstitution 14 III. Other Pulse‐Labeling Methods 17 A. Covalent Labeling of Cysteinyl Residues 17 B. Synchrotron X‐Ray Radiolysis Techniques 18 IV. Conclusions and Outlook 18 A. Ultra‐Rapid Folding Triggers 19 B. MALDI‐MS 19 C. Gas‐Phase Fragmentation Methods 19 D. “Quasi‐Instantaneous” Analysis of Pulse‐Labeled Proteins 19 Acknowledgments 19 References 20 The “protein‐folding problem” refers to the question of how and why a denatured polypeptide chain can spontaneously fold into a compact and highly ordered conformation. The classical description of this process in terms of reaction pathways has been complemented by models that describe folding as a biased conformational diffusion on a multidimensional energy landscape. The identification and characterization of short‐lived intermediates provide important insights into the mechanism of folding. Pulsed hydrogen/deuterium exchange (HDX) methods are among the most powerful tools for studying the properties of kinetic intermediates. Analysis of pulse‐labeled proteins by mass spectrometry (MS) provides information that is complementary to that obtained in nuclear magnetic resonance (NMR) studies; NMR data represent an average of entire protein ensembles, whereas MS can detect co‐existing protein species. MS‐based pulse‐labeling experiments can distinguish between folding scenarios that involve parallel pathways, and those where folding is channeled through obligatory intermediates. The proteolytic digestion/MS technique provides spatially resolved information on the HDX pattern of folding intermediates. This method is especially important for proteins that are too large to be studied by NMR. Although traditional pulsed HDX protocols are based on quench‐flow techniques, it is also possible to use electrospray (ESI) MS to analyze the reaction mixture on‐line and “quasi‐instantaneously” after labeling. This approach allows short‐lived protein conformations to be studied by their HDX level, their ESI charge‐state distribution, and their ligand‐binding state. Covalent labeling of free cysteinyl residues provides an alternative approach to pulsed HDX experiments. Another promising development is the use of synchrotron X‐rays to induce oxidation at specific sites within a protein for studying their solvent accessibility during folding. © 2003 Wiley Periodicals, Inc., Mass Spec Rev 22:1–26, 2003; Published online in Wiley InterScience ( www.interscience.wiley.com )

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.039
GPT teacher head0.310
Teacher spread0.272 · 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 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

Citations163
Published2003
Admission routes1
Has abstractyes

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