Comparative Structural Analysis of Human DEAD-Box RNA Helicases
Bibliographic record
Abstract
DEAD-box RNA helicases play various, often critical, roles in all processes where RNAs are involved. Members of this family of proteins are linked to human disease, including cancer and viral infections. DEAD-box proteins contain two conserved domains that both contribute to RNA and ATP binding. Despite recent advances the molecular details of how these enzymes convert chemical energy into RNA remodeling is unknown. We present crystal structures of the isolated DEAD-domains of human DDX2A/eIF4A1, DDX2B/eIF4A2, DDX5, DDX10/DBP4, DDX18/myc-regulated DEAD-box protein, DDX20, DDX47, DDX52/ROK1, and DDX53/CAGE, and of the helicase domains of DDX25 and DDX41. Together with prior knowledge this enables a family-wide comparative structural analysis. We propose a general mechanism for opening of the RNA binding site. This analysis also provides insights into the diversity of DExD/H- proteins, with implications for understanding the functions of individual family members.
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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) | 0.002 | 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".