Independent mechanisms of stimulation of polynucleotide kinase/phosphatase by phosphorylated and non-phosphorylated XRCC1
Bibliographic record
Abstract
XRCC1 plays a central role in mammalian single-strand break repair. Although it has no enzymatic activity of its own, it stimulates the activities of polynucleotide kinase/phosphatase (PNKP), and this function is enhanced by protein kinase CK2 mediated phosphorylation of XRCC1. We have previously shown that non-phosphorylated XRCC1 stimulates the kinase activity of PNKP by increasing the turnover of PNKP. Here we extend our analysis of the XRCC1-PNKP interaction taking into account the phosphorylation of XRCC1. We demonstrate that phosphorylated and non-phosphorylated XRCC1 interact with different regions of PNKP. Phosphorylated XRCC1 binds with high affinity (K(d) = 3.5 nM and 1 : 1 stoichiometry) to the forkhead associated (FHA) domain, while non-phosphorylated XRCC1 binds to the catalytic domain of PNKP with lower affinity (K(d) = 43.0 nM and 1 : 1 stoichiometry). Under conditions of limited enzyme concentration both forms of XRCC1 enhance the activities of PNKP, but the effect is more pronounced with phosphorylated XRCC1, particularly for the kinase activity of PNKP. The stimulatory effect of phosphorylated XRCC1 on PNKP can be totally inhibited by the presence of excess FHA domain polypeptide, but non-phosphorylated XRCC1 is not susceptible to competition by the FHA domain. Thus, XRCC1 can stimulate PNKP by two independent mechanisms.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".