An arginine-aspartate network in the active site of bacterial TruB is critical for catalyzing pseudouridine formation
Bibliographic record
Abstract
Pseudouridine synthases introduce the most common RNA modification and likely use the same catalytic mechanism. Besides a catalytic aspartate residue, the contributions of other residues for catalysis of pseudouridine formation are poorly understood. Here, we have tested the role of a conserved basic residue in the active site for catalysis using the bacterial pseudouridine synthase TruB targeting U55 in tRNAs. Substitution of arginine 181 with lysine results in a 2500-fold reduction of TruB's catalytic rate without affecting tRNA binding. Furthermore, we analyzed the function of a second-shell aspartate residue (D90) that is conserved in all TruB enzymes and interacts with C56 of tRNA. Site-directed mutagenesis, biochemical and kinetic studies reveal that this residue is not critical for substrate binding but influences catalysis significantly as replacement of D90 with glutamate or asparagine reduces the catalytic rate 30- and 50-fold, respectively. In agreement with molecular dynamics simulations of TruB wild type and TruB D90N, we propose an electrostatic network composed of the catalytic aspartate (D48), R181 and D90 that is important for catalysis by fine-tuning the D48-R181 interaction. Conserved, negatively charged residues similar to D90 are found in a number of pseudouridine synthases, suggesting that this might be a general mechanism.
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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 | 0.001 | 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".