ADP-ribose contributions to genome stability and PARP enzyme trapping on sites of DNA damage; paradigm shifts for a coming-of-age modification
Bibliographic record
Abstract
ADP-ribose is a versatile modification that plays a critical role in diverse cellular processes. The addition of this modification is catalyzed by ADP-ribosyltransferases, among which notable poly(ADP-ribose) polymerase (PARP) enzymes are intimately involved in the maintenance of genome integrity. The role of ADP-ribose modifications during DNA damage repair is of significant interest for the proper development of PARP inhibitors targeted toward the treatment of diseases caused by genomic instability. More specifically, inhibitors promoting PARP persistence on DNA lesions, termed PARP "trapping," is considered a desirable characteristic. In this review, we discuss key classes of proteins involved in ADP-ribose signaling (writers, readers, and erasers) with a focus on those involved in the maintenance of genome integrity. An overview of factors that modulate PARP1 and PARP2 persistence at sites of DNA lesions is also discussed. Finally, we clarify aspects of the PARP trapping model in light of recent studies that characterize the kinetics of PARP1 and PARP2 recruitment at sites of lesions. These findings suggest that PARP trapping could be considered as the continuous recruitment of PARP molecules to sites of lesions, rather than the physical stalling of molecules. Recent studies and novel research tools have elevated the level of understanding of ADP-ribosylation, marking a coming-of-age for this interesting modification.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".