Regulation of PARP1/2 and the tankyrases: emerging parallels
Bibliographic record
Abstract
ADP-ribosylation is a prominent and versatile post-translational modification, which regulates a diverse set of cellular processes. Poly-ADP-ribose (PAR) is synthesised by the poly-ADP-ribosyltransferases PARP1, PARP2, tankyrase (TNKS), and tankyrase 2 (TNKS2), all of which are linked to human disease. PARP1/2 inhibitors have entered the clinic to target cancers with deficiencies in DNA damage repair. Conversely, tankyrase inhibitors have continued to face obstacles on their way to clinical use, largely owing to our limited knowledge of their molecular impacts on tankyrase and effector pathways, and linked concerns around their tolerability. Whilst detailed structure-function studies have revealed a comprehensive picture of PARP1/2 regulation, our mechanistic understanding of the tankyrases lags behind, and thereby our appreciation of the molecular consequences of tankyrase inhibition. Despite large differences in their architecture and cellular contexts, recent structure-function work has revealed striking parallels in the regulatory principles that govern these enzymes. This includes low basal activity, activation by intra- or inter-molecular assembly, negative feedback regulation by auto-PARylation, and allosteric communication. Here we compare these poly-ADP-ribosyltransferases and point towards emerging parallels and open questions, whose pursuit will inform future drug development efforts.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".