Bio-Incorporation of TePhe, a Tellurium-Containing Phenylalanine Analogue, Preserves Protein Structure and Stability
Bibliographic record
Abstract
The heavy chalcogen tellurium (52Te) is a versatile element with many potential applications in chemical biology and biochemistry, including mass cytometry, fluorescence imaging, and protein structure determination. Using L-tellurienylalanine (TePhe), a mimic of the natural amino acid L-phenylalanine (Phe) in which the phenyl side chain is replaced by a nearly isosteric tellurophene ring, tellurium can be covalently incorporated into the proteome of prokaryotes and eukaryotes by endogenous translation machinery. Our goal is to generate proteins with near stoichiometric levels of Phe to TePhe substitutions, verify preservation of protein structure and activity upon TePhe incorporation, and ultimately exploit the site-specific tellurium centres as handles for crystallographic phasing, protein NMR spectroscopy, and bio-orthogonal reactivity. Here we report conditions for the expression of TePhe containing proteins in a standard E. coli expression system and validate the ability of TePhe to act as an effective Phe analogue within a folded protein. Our target for TePhe incorporation is the streptococcal immunoglobulin-binding Protein G B1 domain (GB1), a remarkably heat-stable 56-residue domain containing 2 Phe residues which pack against one another within the domain’s hydrophobic core. In Phe-deficient media containing glyphosate as an inhibitor of aromatic amino acid biosynthesis, we obtained a GB1 mixture in which approximately 1 in 2 Phe sites were substituted by TePhe. Fractionation by reverse-phase HPLC allowed us to obtain a sample with 85% TePhe substitution as evidenced by amino acid analysis. Using 1H-15N HSQC and circular dichroism spectroscopy, we find that TePhe effectively takes on the role of Phe, and alters the melting temperature of the protein by less than 5 °C.
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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) | 0.000 | 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".