Live-Cell Protein Modification by Boronate-Assisted Hydroxamic Acid Catalysis
Bibliographic record
Abstract
Selective methods for introducing protein post-translational modifications (PTMs) within living cells have proven valuable for interrogating their biological function. In contrast to enzymatic methods, abiotic catalysis should offer access to diverse and new-to-nature PTMs. Herein, we report the boronate-assisted hydroxamic acid (BAHA) catalyst system, which comprises a protein ligand, a hydroxamic acid Lewis base, and a diol moiety. In concert with a boronic acid-bearing acyl donor, our catalyst leverages a local molarity effect to promote acyl transfer to a target lysine residue. Our catalyst system employs micromolar reagent concentrations and affords minimal off-target protein reactivity. Critically, BAHA is resistant to glutathione, a metabolite which has hampered many efforts toward abiotic chemistry within living cells. To showcase this methodology, we installed a variety of acyl groups in E. coli dihydrofolate reductase expressed within human cells. Our results further establish the well-known boronic acid–diol complexation as a bona fide bio-orthogonal reaction with applications in chemical biology and in-cell catalysis.
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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".