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Record W2039754775 · doi:10.1021/ja021452+

Side Chain Assignments of Ile δ1 Methyl Groups in High Molecular Weight Proteins:  an Application to a 46 ns Tumbling Molecule

2003· article· en· W2039754775 on OpenAlexaff
Vitali Tugarinov

Bibliographic record

VenueJournal of the American Chemical Society · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Structure and Dynamics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsChemistryProtonationMoleculeChemical shiftSide chainStereochemistryPulse sequenceSpectral lineCrystallographyIonPhysical chemistryNuclear magnetic resonanceOrganic chemistry

Abstract

fetched live from OpenAlex

A sensitive 3D NMR pulse scheme, (H)C(CA)NH-COSY, is presented for the assignment of (13)C(delta)(1) Ile chemical shifts in large perdeuterated, methyl-protonated proteins. The nonlinearity of branched amino acids, such as Ile, significantly degrades the quality of TOCSY schemes which transfer magnetization from methyl carbons to the backbone (13)C(alpha) positions, and in applications to high molecular weight proteins (correlation times on the order of 40-50 ns), this compromises the sensitivity of spectra used for methyl assignment. The experiment presented utilizes COSY-based transfer steps and refocuses undesirable (13)C-(13)C scalar couplings that degrade the efficiency of TOCSY transfers. The (H)C(CA)NH-COSY scheme is tested on an (15)N,(13)C,(2)H-[Leu, Val, Ile (delta 1 only)]-methyl-protonated maltose binding protein (MBP)/beta-cyclodextrin complex at 5 degrees C (molecular tumbling time 46 +/- 2 ns), facilitating the assignment of (13)C(delta 1) chemical shifts for 18 of the 19 Ile residues for which backbone assignments were previously obtained. Both sensitivity and resolution of the resulting spectra are shown to be significantly better than those for a similar TOCSY-based approach.

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 score0.017
Threshold uncertainty score0.462

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 science0.0000.000
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 head0.004
GPT teacher head0.241
Teacher spread0.237 · 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

Citations44
Published2003
Admission routes1
Has abstractyes

Explore more

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