Structural insights into the role of DNA-PK as a master regulator in NHEJ
Bibliographic record
Abstract
is the largest serine/threonine protein kinase of the phosphatidyl inositol 3-kinase-like protein kinase (PIKK) family and is the most highly expressed PIKK in human cells. With its DNA-binding partner Ku70/80, DNA-PKcs is required for regulated and efficient repair of ionizing radiation-induced DNA double-strand breaks via the non-homologous end joining (NHEJ) pathway. Loss of DNA-PKcs or other NHEJ factors leads to radiation sensitivity and unrepaired DNA double-strand breaks (DSBs), as well as defects in V(D)J recombination and immune defects. In this review, we highlight the contributions of the late Dr. Carl W. Anderson to the discovery and early characterization of DNA-PK. We furthermore build upon his foundational work to provide recent insights into the structure of NHEJ synaptic complexes, an evolutionarily conserved and functionally important YRPD motif, and the role of DNA-PKcs and its phosphorylation in NHEJ. The combined results identify DNA-PKcs as a master regulator that is activated by its detection of two double-strand DNA ends for a cascade of phosphorylation events that provide specificity and efficiency in assembling the synaptic complex for NHEJ.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".