Mixed Fluorotryptophan Substitutions at the Same Residue Expand the Versatility of <sup>19</sup>F Protein NMR Spectroscopy
Bibliographic record
Abstract
Abstract The strategy of applying fluorine NMR to characterize ligand binding to a membrane protein prepared with mixtures of tryptophans substituted with F at different positions on the indole ring was tested. The 19F NMR behavior of 4‐, 5‐, 6‐, and 7‐fluorotryptophan were directly compared as a function of both micellar environment and fragment size for two overlapping apelin receptor (AR/APJ) segments; one with a single transmembrane (TM) helix and two tryptophan residues, the other with three TM helices and two additional tryptophan residues. Chemical shifts, peak patterns, and nuclear spin relaxation rates were observed to vary as a function of micellar conditions and F substitution position in the indole ring, with the exposure of a given residue to micelle or solvent being the primary differentiating factor. Titration of the 3‐TM AR segment biosynthetically prepared as a mixture of 5‐ and 7‐fluorotryptophan‐containing isoforms by two distinct peptide ligands (apelin‐36 and apela‐32) demonstrated site‐specific 19F peak intensity changes for one ligand but not the other. In contrast, both ligands perturbed 1H–15N HSQC peak patterns to a similar degree. Characterization of multiple fluorotryptophan types for a given set of tryptophan residues, thus, significantly augments the potential to apply 19F NMR to track otherwise obscure modulation of protein conformation and dynamics without an explicit requirement for mutagenesis or chemical modification.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".