Major reorientation of tRNA substrates defines specificity of dihydrouridine synthases
Bibliographic record
Abstract
The reduction of specific uridines to dihydrouridine is one of the most common modifications in tRNA. Increased levels of the dihydrouridine modification are associated with cancer. Dihydrouridine synthases (Dus) from different subfamilies selectively reduce distinct uridines, located at spatially unique positions of folded tRNA, into dihydrouridine. Because the catalytic center of all Dus enzymes is conserved, it is unclear how the same protein fold can be reprogrammed to ensure that nucleotides exposed at spatially distinct faces of tRNA can be accommodated in the same active site. We show that the Escherichia coli DusC is specific toward U16 of tRNA. Unexpectedly, crystal structures of DusC complexes with tRNA(Phe) and tRNA(Trp) show that Dus subfamilies that selectively modify U16 or U20 in tRNA adopt identical folds but bind their respective tRNA substrates in an almost reverse orientation that differs by a 160° rotation. The tRNA docking orientation appears to be guided by subfamily-specific clusters of amino acids ("binding signatures") together with differences in the shape of the positively charged tRNA-binding surfaces. tRNA orientations are further constrained by positional differences between the C-terminal "recognition" domains. The exquisite substrate specificity of Dus enzymes is therefore controlled by a relatively simple mechanism involving major reorientation of the whole tRNA molecule. Such reprogramming of the enzymatic specificity appears to be a unique evolutionary solution for altering tRNA recognition by the same protein fold.
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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) | 0.000 | 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) | 0.001 | 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".