An Eight Residue Fragment of an Acyl Carrier Protein Suffices for Post-Translational Introduction of Fluorescent Pantetheinyl Arms in Protein Modification <i>in vitro</i> and <i>in vivo</i>
Bibliographic record
Abstract
Genetically encoded tags for tracking a given protein continue to be of great interest in a multitude of in vitro and in vivo contexts. Acyl carrier proteins, both free-standing and as embedded 80-100 residue domains, contain a specific serine side chain that undergoes post-translational pantetheinylation from CoASH as donor substrate. We have previously used phage display methods to select a 12 residue fragment that retains recognition for modification by the Escherichia coli phosphopantetheinyltransferase (PPTase) AcpS. In this work, we have used (15)N-HSQC based NMR titration experiments of a 12-residue peptide substrate with AcpS to identify six specifically interacting residues (S3, L4, D5, M6, W9, and L11) without the formation of any notable secondary structure. Synthesis of a corresponding octapeptide containing 5 of the 6 interacting residues generated a minimal fragment capable of efficient post-translational phosphopantetheinylation. Genetic insertion of this eight residue coding sequence into the proteins sonic hedgehog and transferrin receptor enabled good in vitro and in vivo PPTase-mediated modification by a series of fluorescent CoAs, leading to a set of fluorescent proteins with a peptide tag minimally perturbant to protein folds.
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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".