Bibliographic record
Abstract
Abstract “Biomimetic Aminoacylation” Svetlana K. Tzvetkova Doctor of Philosophy, 2008 Graduate Department of Chemistry University of Toronto The accuracy of ribosomal protein synthesis depends on the fidelity of highly specific enzymes, aminoacyl tRNA synthetases, towards amino acid – tRNA pairs. These biological catalysts are responsible for activating the amino acids as aminoacyl adenylates and for their subsequent attachment to the 2’- or 3’-OH at the 3’-terminal of the correct tRNA to give aminoacyl-tRNA. Extended diversity in protein structure and function could be achieved if non-natural side chains can be introduced in protein synthesis. This requires that the acceptor stem of a tRNA molecule be synthetically aminoacylated. The most widely used methods for charging tRNA with non-natural amino acids involve multi-step synthesis of an aminoacyl-pCpA and its consequent enzymatic ligation to truncated tRNA. No direct route to these species has been reported. We have developed a method for direct biomimetic aminoacylation of the 3’-terminal hydroxyls of tRNA. Our approach shows to be promising in reactions leading to direct 2’- or 3’-O-aminoacylation of not only nucleosides and nucleotides but also RNA in general and tRNA in particular. The system we have developed provides: 1) efficient activation of the amino acids as aminoacyl phosphates, analogues of the enzymatic intermediates, and 2) specific recognition of the 3’-terminal of tRNA by lanthanide ions present in the reaction. The aminoacylating reagents used in our studies were carefully selected to provide handles to follow the reaction: UV absorbance, fluorescence spectroscopy and 19F NMR. Lanthanide (III) ions can play a role similar to a key part of the aminoacyl tRNA synthetases – they bring the aminoacyl close to the 3’-terminal of tRNA, in this case by forming a bis-bidentate complex with the aminoacyl phosphate and the 2’,3’-diol functionality of the 3’-terminal adenosine. This process relies on the specificity towards the unique 3’-terminal diol on tRNA, provided by the metal ion and the simultaneous complexation of the aminoacyl phosphate.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".