The determination of tRNA<sup>Leu</sup> recognition nucleotides for <i>Escherichia coli</i> L/F transferase
Bibliographic record
Abstract
Escherichia coli leucyl/phenylalanyl-tRNA protein transferase catalyzes the tRNA-dependent post-translational addition of amino acids onto the N-terminus of a protein polypeptide substrate. Based on biochemical and structural studies, the current tRNA recognition model by L/F transferase involves the identity of the 3' aminoacyl adenosine and the sequence-independent docking of the D-stem of an aminoacyl-tRNA to the positively charged cluster on L/F transferase. However, this model does not explain the isoacceptor preference observed 40 yr ago. Using in vitro-transcribed tRNA and quantitative MALDI-ToF MS enzyme activity assays, we have confirmed that, indeed, there is a strong preference for the most abundant leucyl-tRNA, tRNA(Leu) (anticodon 5'-CAG-3') isoacceptor for L/F transferase activity. We further investigate the molecular mechanism for this preference using hybrid tRNA constructs. We identified two independent sequence elements in the acceptor stem of tRNA(Leu) (CAG)-a G₃:C₇₀ base pair and a set of 4 nt (C₇₂, A₄:U₆₉, C₆₈)-that are important for the optimal binding and catalysis by L/F transferase. This maps a more specific, sequence-dependent tRNA recognition model of L/F transferase than previously proposed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".