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Record W2052867937 · doi:10.1021/ja0264549

<sup>15</sup>N,H Heteronuclear Correlation NMR of Gramicidin A in DMPC-<i>d</i><sub>67</sub>

2002· article· en· W2052867937 on OpenAlexaff
Christophe Farès, Frances J. Sharom, James H. Davis

Bibliographic record

VenueJournal of the American Chemical Society · 2002
Typearticle
Languageen
FieldNeuroscience
TopicPhotoreceptor and optogenetics research
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsChemistryHeteronuclear moleculeGramicidinCrystallographyMagnetic dipole–dipole interactionNuclear magnetic resonance spectroscopyHelix (gastropod)DeuteriumDipoleGramicidin SMicelleTwo-dimensional nuclear magnetic resonance spectroscopyMagic angle spinningAnalytical Chemistry (journal)Nuclear magnetic resonanceStereochemistryMembraneAqueous solutionPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

We have studied gramicidin A, an environmentally sensitive polymorphic pentadecapeptide, fully 15N-labelled and dispersed in a highly deuterated phospholipid bilayer system. By submitting the sample to fast magic angle spinning, we were able to reduce the polypeptide amide hydrogen linewidths to 160 Hz, and hence to partially resolve them. By correlating these resonances with the 40 Hz wide dipolar coupled 15N in a 2D-CROPSY (cross-polarization spectroscopy) experiment, it was possible to observe the 20 partially overlapping 1H-15N signal pairs from the polypeptide backbone and sidechains. Both chemical shift distributions closely match those of the same peptide in SDS micelles, but only poorly match those of conformationally different gramicidin A in trifluoroethanol, dimethylsulfoxide, or methanol/chloroform mixture. Our results are indicative of the N-to-N right-handed beta6.3-helix conformation of gramicidin A and offer sufficient resolution to encourage development of experiments to measure orientational or distance restraints using through-space dipolar couplings.

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)0.001
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 score0.027
Threshold uncertainty score0.446

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.027
GPT teacher head0.269
Teacher spread0.242 · 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

Citations13
Published2002
Admission routes1
Has abstractyes

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