Light-induced modulation of DNA recognition by the Rad4/XPC damage sensor protein
Bibliographic record
Abstract
Biomolecular structural changes upon binding/unbinding are key to their functions. However, characterization of such dynamical processes is difficult as it requires ways to rapidly and specifically trigger the assembly/disassembly as well as ways to monitor the resulting changes over time. Recently, various chemical strategies have been developed to use light to trigger changes in oligonucleotide structures, and thereby their activities. Here we report that photocleavable DNA can be used to modulate the DNA binding of the Rad4/XPC DNA repair complex using light. Rad4/XPC specifically recognizes diverse helix-destabilizing/distorting lesions including bulky organic adduct lesions and functions as a key initiator for the eukaryotic nucleotide excision repair (NER) pathway. We show that the 6-nitropiperonyloxymethyl (NPOM)-modified DNA is recognized by the Rad4 protein as a specific substrate and that the specific binding can be abolished by light-induced cleavage of the NPOM group from DNA in a dose-dependent manner. Fluorescence lifetime-based analyses of the DNA conformations suggest that free NPOM-DNA retains B-DNA-like conformations despite its bulky NPOM adduct, but Rad4-binding causes it to be heterogeneously distorted. Subsequent extensive conformational searches and molecular dynamics simulations demonstrate that NPOM in DNA can be housed in the major groove of the DNA, with stacking interactions among the nucleotide pairs remaining largely unperturbed and thus retaining overall B-DNA conformation. Our work suggests that photoactivable DNA may be used as a DNA lesion surrogate to study DNA repair mechanisms such as nucleotide excision repair.
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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 | 0.000 |
| 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".