Regulation of FANCD2 and FANCI monoubiquitination by their interaction and by DNA
Bibliographic record
Abstract
FANCD2 and FANCI function together in the Fanconi anemia network of deoxyribonucleic acid (DNA) crosslink repair. These proteins form the dimeric ID2 complex that binds DNA and becomes monoubiquitinated upon exposure of cells to DNA crosslinking agents. The monoubiquitinated ID2 complex is thought to facilitate DNA repair via recruitment of specific nucleases, translesion DNA polymerases and the homologous recombination machinery. Using the ubiquitin conjugating enzyme (E2) UBE2T and ubiquitin ligase (E3) FANCL, monoubiquitination of human FANCD2 and FANCI was examined. The ID2 complex is a poor substrate for monoubiquitination, consistent with the published crystal structure showing the solvent inaccessibility of the target lysines. Importantly, FANCD2 monoubiquitination within the ID2 complex is strongly stimulated by duplex or branched DNA, but unstructured single-stranded DNA or chromatinized DNA is ineffective. Interaction of FANCL with the ID2 complex is indispensable for its E3 ligase efficacy. Interestingly, mutations in FANCI that impair its DNA binding activity compromise DNA-stimulated FANCD2 monoubiquitination. Moreover, we demonstrate that in the absence of FANCD2, DNA also stimulates FANCI monoubiquitination, but in a FANCL-independent manner. These results implicate the role of a proper DNA ligand in FANCD2 and FANCI monoubiquitination, and reveal regulatory mechanisms that are dependent on protein-protein and protein-DNA interactions.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".