FANCD2-associated Nuclease 1, but Not Exonuclease 1 or Flap Endonuclease 1, Is Able to Unhook DNA Interstrand Cross-links in Vitro
Bibliographic record
Abstract
Cisplatin and its derivatives, nitrogen mustards and mitomycin C, are used widely in cancer chemotherapy. Their efficacy is linked primarily to their ability to generate DNA interstrand cross-links (ICLs), which effectively block the progression of transcription and replication machineries. Release of this block, referred to as unhooking, has been postulated to require endonucleases that incise one strand of the duplex on either side of the ICL. Here we investigated how the 5' flap nucleases FANCD2-associated nuclease 1 (FAN1), exonuclease 1 (EXO1), and flap endonuclease 1 (FEN1) process a substrate reminiscent of a replication fork arrested at an ICL. We now show that EXO1 and FEN1 cleaved the substrate at the boundary between the single-stranded 5' flap and the duplex, whereas FAN1 incised it three to four nucleotides in the double-stranded region. This affected the outcome of processing of a substrate containing a nitrogen mustard-like ICL two nucleotides in the duplex region because FAN1, unlike EXO1 and FEN1, incised the substrate predominantly beyond the ICL and, therefore, failed to release the 5' flap. We also show that FAN1 was able to degrade a linear ICL substrate. This ability of FAN1 to traverse ICLs in DNA could help to elucidate its biological function, which is currently unknown.
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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) | 0.000 | 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".