Roles of the Active Site Zn(II) and Residues in Substrate Discrimination by Threonyl-tRNA Synthetase: An MD and QM/MM Investigation
Bibliographic record
Abstract
Threonyl-tRNA synthetase (ThrRS) is a Zn(II) containing enzyme that catalyzes the activation of threonine and its subsequent transfer to the cognate tRNA. This process is accomplished with remarkable fidelity, with ThrRS being able to discriminate its cognate substrate from similar analogues such as serine and valine. Molecular dynamics (MD) simulations and hybrid quantum mechanics/molecular mechanics (QM/MM) methods have been used to elucidate the role of Zn(II) in the aminoacylation mechanism of ThrRS. More specifically, the role of Zn(II) and active site residues in ThrRS’s ability to discriminate between its cognate substrate l -threonine and the noncognate l -serine, l -valine, and d -threonine has been examined. The present results suggest that a role of the Zn(II) ion, with its Lewis acidity, is to facilitate deprotonation of the side chain hydroxyl groups of the aminoacyl moieties of cognate Thr-AMP and noncognate Ser-AMP substrates. In their deprotonated forms, these substrates are able to adopt a conformation preferable for aminoacyl transfer from aa-AMP onto the Ado-3′OH of the tRNA Thr cosubstrate. Relative to the neutral substrates, when the substrates are first deprotonated with the assistance of the Zn(II) ion, the barrier for the rate-limiting step is decreased significantly by 42.0 and 39.2 kJ mol –1 for l -Thr-AMP and l -Ser-AMP, respectively. An active site arginyl also plays a key role in stabilizing the buildup of negative charge on the substrate’s bridging phosphate oxygen during the mechanism. For the enantiomeric substrate analogue d -Thr-AMP, product formation is highly disfavored, and as a result, the reverse reaction has a very low barrier of 16.0 kJ mol –1 .
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".