Stereoselective Deuteration in Aspartate, Asparagine, Lysine, and Methionine Amino Acid Residues Using Fumarate as a Carbon Source for <i>Escherichia coli</i> in D<sub>2</sub>O
Bibliographic record
Abstract
Perdeuteration with selective 1 H, 13 C-enrichment of methyl groups has enabled solution NMR studies of large (>30 kDa) protein systems. However, we propose that for all non-methyl positions, only magnetization originating from 1 H– 12 C groups is sufficiently long-lived, and it can be transferred via through-space NOEs to slowly relaxing 1 H– 15 N or 1 H– 13 C methyl groups to achieve multidimensional solution NMR. We demonstrate stereoselective 1 H, 12 C-labeling by adding relatively inexpensive unlabeled carbon sources to Escherichia coli growth media in D 2 O. Using our model system, a mutant WW domain from human Pin1, we compare deuteration patterns in 19 amino acids (all except cysteine). Protein grown using glucose as the sole carbon source had high levels of protonation in aromatic rings and the H β positions of serine and tryptophan. In contrast, using our FROMP media (fumarate, rhamnose, oxalate, malonate, pyruvate), stereoselective protonation of H β2 with deuteration at H α and H β3 was achieved in Asp, Asn, Lys, and Met residues. In solution NMR, stereospecific chemical shift assignments for H β are typically obtained in conjunction with χ 1 dihedral angle determinations using 3-bond J -coupling ( 3 J N–Hβ, 3 J CO-Hβ, 3 J Hα-Hβ ) experiments. However, due to motional averaging, the assumption of a pure rotameric state can yield incorrect χ 1 dihedral angles with incorrect stereospecific assignments. This was the case for three residues in the Pin1 WW domain (Lys28, Met30, and Asn44). Thus, stereoselective 1 H, 12 C-labeling will be useful not only for NMR studies of large protein systems, but also for determining side chain rotamers and dynamics in any protein system.
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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".