Functional characterization of the mammalian mRNA decapping enzyme hDcp2
Bibliographic record
Abstract
Regulation of decapping is a critical determinant of mRNA stability. We recently identified hDcp2 as a human decapping enzyme with intrinsic decapping activity. This activity is specific to N(7)-methylated guanosine containing RNA. The hDcp2 enzyme does not function on the cap structure alone and is not sensitive to competition by cap analog, suggesting that hDcp2 requires the RNA for cap recognition. We now demonstrate that hDcp2 is an RNA-binding protein and its recognition and hydrolysis of the cap substrate is dependent on an initial interaction with the RNA moiety. A biochemical characterization of hDcp2 revealed that a 163 amino acid region containing two evolutionarily conserved regions, the Nudix fold hydrolase domain and the adjacent Box B region contained methyl-cap-specific hydrolysis activity. Maximum decapping activity for wild-type as well as truncation mutants of hDcp2 required Mn(2+) as a divalent cation. The demonstration that hDcp2 is an RNA-binding protein with an RNA-dependent decapping activity will now provide new approaches to identify specific mRNAs that are regulated by this decapping enzyme as well as provide novel avenues to control mRNA decapping and turnover by influencing the RNA-binding property of hDcp2.
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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 | 0.000 |
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".