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Record W2029957363 · doi:10.1021/ja909294n

Determination of Leu Side-Chain Conformations in Excited Protein States by NMR Relaxation Dispersion

2009· article· en· W2029957363 on OpenAlexafffund
D. Flemming Hansen, Philipp Neudecker, Pramodh Vallurupalli, Frans A. A. Mulder, Lewis E. Kay

Bibliographic record

VenueJournal of the American Chemical Society · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Structure and Dynamics
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsChemistryConformational isomerismExcited stateFolding (DSP implementation)Relaxation (psychology)Side chainCrystallographyDispersion (optics)Protein foldingChemical shiftSH3 domainComputational chemistryChemical physicsMoleculePhysical chemistryAtomic physicsPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

Fits of Carr-Purcell-Meiboom-Gill (CPMG) relaxation dispersion profiles allow extraction of the kinetics and thermodynamics of exchange reactions that interconvert highly populated, ground state and low populated, excited state conformers. Structural information is also available in the form of chemical shift differences between the interconverting protein states. Here we present a very simple method for extracting chi(2) rotamer distributions of Leu side chains in 'invisible' excited protein states based on measurement of their (13)C(delta1)/(13)C(delta2) chemical shifts using methyl CPMG dispersion experiments. The methodology is applied to study the protein folding reaction of the Fyn SH3 domain. A uniform chi(2) rotamer distribution is obtained for Leu residues of the unfolded state, with each Leu occupying the trans and gauche+ conformations in a 2:1 ratio. By contrast, leucines of an 'invisible' Fyn SH3 domain folding intermediate show a much more heterogeneous distribution of chi(2) rotamer populations. The experiment provides an important tool toward the quantitative characterization of both the structural and dynamics properties of states that cannot be studied by other biophysical tools.

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 score0.007
Threshold uncertainty score0.203

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 head0.003
GPT teacher head0.229
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

Citations73
Published2009
Admission routes2
Has abstractyes

Explore more

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