The DNA Damage-Sensing NER Repair Factor XPC-RAD23B Does Not Recognize Bulky DNA Lesions with a Missing Nucleotide Opposite the Lesion
Bibliographic record
Abstract
Abstract The Nucleotide Excision Repair (NER) mechanism removes a wide spectrum of structurally different lesions that critically depend on the binding of the DNA damage sensing NER factor XPC-RAD23B (XPC) to the lesions. The bulky mutagenic benzo[ a ]pyrene diol epoxide metabolite-derived cis - and trans -B[ a ]P-dG lesions (G*) adopt base-displaced intercalative ( cis ) or minor groove ( trans) conformations in fully paired DNA duplexes with the canonical C opposite G* (G*:C duplexes). While XPC has a high affinity for binding to these DNA lesions in fully complementary double-stranded DNA, we show here that deleting only the C in the complementary strand opposite the lesion G* embedded in 50-mer duplexes, fully abrogates XPC binding. Accurate values of XPC dissociation constants ( K D ) were determined by employing an excess of unmodified DNA as a competitor; this approach eliminated the binding and accumulation of multiple XPC molecules to the same DNA duplexes, a phenomenon that prevented the accurate estimation of XPC binding affinities in previous studies. Surprisingly, a detailed comparison of XPC dissociation constants K D of unmodified and lesion-containing G*:Del complexes, showed that the K D values were ∼ 2.5 – 3.6 times greater in the case of G*:Del than in the unmodified G:Del and fully base-paired G:C duplexes. The origins of this unexpected XPC lesion avoidance effect is attributed to the intercalation of the bulky, planar B[ a ]P aromatic ring system between adjacent DNA bases that thermodynamically stabilize the G*:Del duplexes. The strong lesion-base stacking interactions associated with the absence of the partner base, prevent the DNA structural distortions needed for the binding of the BHD2 and BHD3 β–hairpins of XPC to the deletion duplexes, thus accounting for the loss of XPC binding and the known NER-resistance of G*:Del duplexes.
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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 | 0.001 |
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".