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Record W2074315771 · doi:10.1021/ja0508830

Probing Side-Chain Dynamics in High Molecular Weight Proteins by Deuterium NMR Spin Relaxation:  An Application to an 82-kDa Enzyme

2005· article· en· W2074315771 on OpenAlexaff
Vitali Tugarinov, Jason E. Ollerenshaw, Lewis E. Kay

Bibliographic record

VenueJournal of the American Chemical Society · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Structure and Dynamics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsChemistrySide chainIsotopomersDeuteriumMolecular dynamicsProtein dynamicsRelaxation (psychology)Methyl groupEnzymeInverseNuclear magnetic resonanceAnalytical Chemistry (journal)Computational chemistryMoleculeChromatographyOrganic chemistryPhysicsAtomic physicsPolymer

Abstract

fetched live from OpenAlex

New NMR experiments for the measurement of side-chain dynamics in high molecular weight ( approximately 100 kDa) proteins are presented. The experiments quantify (2)H spin relaxation rates in (13)CH(2)D or (13)CHD(2) methyl isotopomers and, for applications to large systems, offer significant gains both in sensitivity (2-3-fold) and resolution over previously published HSQC schemes. The methodology has been applied to investigate Ile dynamics in the 723-residue, single polypeptide chain enzyme, malate synthase G. Methyl-axis order parameters, S(axis), characterizing the amplitudes of motion of the methyl groups, have been derived from both (13)CH(2)D and (13)CHD(2) probes and are in excellent agreement. The distribution of order parameters is trimodal, reflecting the range of dynamics that are available to Ile residues. A reasonable correlation is noted between and inverse temperature factors from X-ray studies of the enzyme. The proposed methodology significantly extends the range of protein systems for which side-chain dynamics can be studied.

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 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 score0.019
Threshold uncertainty score0.585

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.003
GPT teacher head0.228
Teacher spread0.226 · 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

Citations63
Published2005
Admission routes1
Has abstractyes

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