Rewiring DNA repair with PARP-based chemical inducers of proximity
Bibliographic record
Abstract
Abstract Chemical inducers of proximity (CIPs) can elicit durable—and often neomorphic—biological effects through the formation of a ternary complex, even at low equilibrium occupancy of their targets. This “event-driven” pharmacology is exemplified by CIPs that promote targeted protein degradation, but other applications remain underexplored. We developed a generalizable strategy to discover event-driven CIPs by tracking the cellular effects of heterobifunctional small molecules alongside quantitative measures of intracellular target engagement. Using this approach, we discovered PCIP-1, which inhibits DNA repair by recruiting BET proteins to PARP2. Unlike conventional PARP inhibitors, PCIP-1 activity is observed at low equilibrium occupancy of PARP1/2 and without inhibition of PARP-catalyzed PARylation, yet it retains synthetic lethality in cancer cells with homologous recombination deficiencies. PARP1 knockout, which confers resistance to conventional PARP drugs, increases sensitivity to PCIP-1, offering a potential new mechanism to overcome clinical resistance. Through these studies, we demonstrate that DNA repair can be rewired by CIPs and introduce a new form of event-driven pharmacology.
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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 | 0.001 |
| 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".