The human pseudouridine synthase PUS7 recognizes RNA with an extended multi-domain binding surface
Bibliographic record
Abstract
The human pseudouridine synthase PUS7 is a versatile RNA modification enzyme targeting many RNAs thereby playing a critical role in development and brain function. Whereas all target RNAs of PUS7 share a consensus sequence, additional recognition elements are likely required, and the structural basis for RNA binding by PUS7 is unknown. Here, we characterize the structure-function relationship of human PUS7 reporting its X-ray crystal structure at 2.26 Å resolution. Compared to its bacterial homolog, human PUS7 possesses two additional subdomains, and structural modeling studies suggest that these subdomains contribute to tRNA recognition through increased interactions along the tRNA substrate. Consistent with our modeling, we find that all structural elements of tRNA are required for productive interaction with PUS7 as the consensus sequence of target RNA alone is not sufficient for pseudouridylation by human PUS7. Moreover, PUS7 binds several, non-modifiable RNAs with medium affinity which likely enables PUS7 to screen for productive RNA substrates. Following tRNA modification, the product tRNA has a significantly lower affinity for PUS7 facilitating its dissociation. Taken together our studies suggest a combination of structure-specific and sequence-specific RNA recognition by PUS7 and provide mechanistic insight into its function.
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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".