What is in a name? Rethinking SMUG1 in genome maintenance
Bibliographic record
Abstract
Abstract Small base lesions in DNA are primarily repaired through the base excision repair pathway, which is initiated by DNA glycosylases. This review focuses on single-strand selective monofunctional uracil–DNA glycosylase (SMUG1), an enzyme whose name incompletely captures its broader biological roles. SMUG1 excises a wide range of substrates beyond uracil, shows a preference for double-stranded DNA, and has been reported to be a bifunctional DNA glycosylase with a weak lyase activity. Moreover, SMUG1 plays roles extending beyond DNA repair, including functions in RNA quality control and RNA biogenesis. Recently, genetic interactions have been described between SMUG1 and proteins that safeguard stressed replication forks, implicating a function for SMUG1 in cancer cell biology. Understanding SMUG1’s full repertoire is key to uncovering its role in genome maintenance and unlocking its potential as a therapeutic target. Here, we review the biochemical properties reported for SMUG1 and its distinct functions from other uracil–DNA glycosylases in vivo. We also highlight the emerging role of SMUG1 in cancer cells and its potential as a therapeutic target, emphasizing the need to define the genetic and molecular contexts in which its modulation may be beneficial.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".