Direct Interaction between Uracil-DNA Glycosylase and a Proliferating Cell Nuclear Antigen Homolog in the CrenarchaeonPyrobaculum aerophilum
Bibliographic record
Abstract
Proliferating cell nuclear antigen (PCNA) acts as a sliding clamp on duplex DNA. Its homologs, present in Eukarya and Archaea, are part of protein complexes that are indispensable for DNA replication and DNA repair. In Eukarya, PCNA is known to interact with more than a dozen different proteins, including a human major nuclear uracil-DNA glycosylase (hUNG2) involved in immediate postreplicative repair. In Archaea, only three classes of PCNA-binding proteins have been reported previously: replication factor C (the PCNA clamp loader), family B DNA polymerase, and flap endonuclease. In this study, we report a direct interaction between a uracil-DNA glycosylase (Pa-UDGa) and a PCNA homolog (Pa-PCNA1), both from the hyperthermophilic crenarchaeon Pyrobaculum aerophilum (T(opt) = 100 degrees C). We demonstrate that the Pa-UDGa-Pa-PCNA1 complex is thermostable, and two hydrophobic amino acid residues on Pa-UDGa (Phe(191) and Leu(192)) are shown to be crucial for this interaction. It is interesting to note that although Pa-UDGa has homologs throughout the Archaea and bacteria, it does not share significant sequence similarity with hUNG2. Nevertheless, our results raise the possibility that Pa-UDGa may be a functional analog of hUNG2 for PCNA-dependent postreplicative removal of misincorporated uracil.
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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".