The α-Amino Group of the Threonine Substrate as The General Base During tRNA Aminoacylation: A New Version of Substrate-Assisted Catalysis Predicted by Hybrid DFT
Bibliographic record
Abstract
Density functional theory-based methods in combination with large chemical models have been used to investigate the mechanism of the second half-reaction catalyzed by Thr-tRNA synthetase: aminoacyl transfer from Thr-AMP onto the (A76)3'OH of the cognate tRNA. In particular, we have examined pathways in which an active site His309 residue is either protonated or neutral (i.e., potentially able to act as a base). In the protonated His309-assisted mechanism, the rate-limiting step is formation of the tetrahedral intermediate. The barrier for this step is 155.0 kJ mol(-1), and thus, such a pathway is concluded to not be enzymatically feasible. For the neutral His309-assisted mechanism, two models were used with the difference being whether Lys465 was included. For either model, the barrier of the rate-limiting step is below the upper thermodynamic enzymatic limit of ~125 kJ mol(-1). Specifically, without Lys465, the rate-limiting barrier is 122.1 kJ mol(-1) and corresponds to a rotation about the tetrahedral intermediate C(carb)-OH bond. For the model with Lys465, the rate-limiting barrier is slightly lower and corresponds to the formation of the tetrahedral intermediate. Importantly, for both "neutral His309" models, the neutral amino group of the threonyl substrate directly acts as the proton acceptor; in the formation of the tetrahedral intermediate, the (A76)3'OH proton is directly transferred onto the Thr-NH(2). Therefore, the overall mechanism follows a general substrate-assisted catalytic mechanism.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".