Cost-effective selective deuteration of aromatic amino acid residues produces long-lived solution 1H NMR magnetization in proteins
Bibliographic record
Abstract
Solution NMR studies of large proteins are hampered by rapid signal decay due to short-range dipolar 1H–1H and 1H–13C interactions. These are attenuated by rapid rotation in methyl groups and by deuteration (2H), so selective 1H,13C-isotope labelling of methyl groups in otherwise perdeuterated proteins, combined with methyl transverse relaxation optimized spectroscopy (methyl-TROSY), is now standard for solution NMR of large protein systems > 25 kDa. For non-methyl positions, long-lived magnetization can be introduced as isolated 1H–12C groups. We have developed a cost-effective chemical synthesis for producing selectively deuterated phenylpyruvate and hydroxyphenylpyruvate. Feeding these amino acid precursors to E. coli in D2O, along with selectively deuterated anthranilate and unlabeled histidine, results in isolated and long-lived 1H magnetization in the aromatic rings of Phe (HD, HZ), Tyr (HD), Trp (HH2, HE3) and His (HD2 and HE1). We are additionally able to obtain stereoselective deuteration of Asp, Asn, and Lys amino acid residues using unlabeled glucose and fumarate as carbon sources and oxalate and malonate as metabolic inhibitors. Combining these approaches produces isolated 1H–12C groups in Phe, Tyr, Trp, His, Asp, Asn, and Lys in a perdeuterated background, which is compatible with standard 1H–13C labeling of methyl groups in Ala, Ile, Leu, Val, Thr, Met. We show that isotope labeling of Ala is improved using the transaminase inhibitor L-cycloserine, and labeling of Thr is improved through addition of Cys and Met, which are known inhibitors of homoserine dehydrogenase. We demonstrate the creation of long-lived 1H NMR signals in most amino acid residues using our model system, the WW domain of human Pin1, as well as the bacterial outer membrane protein PagP.
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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 | 0.001 |
| 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".