An ONIOM and MD Investigation of Possible Monofunctional Activity of Human 8-Oxoguanine–DNA Glycosylase (hOgg1)
Bibliographic record
Abstract
Since the formation of 8-oxoguanine (OG) is one of the most common DNA-damaging events, cells have evolved efficient repair processes to avoid the mutagenic effects associated with this lesion, including base excision repair (BER) initiated by hOgg1. In the present work, three distinct mechanisms for deglycosylation catalyzed by hOgg1 that represent monofunctional activity were characterized using a combination of molecular dynamics (MD) simulations on the full DNA-enzyme complex and ONIOM calculations on a truncated DNA-protein model. The initial lysine activation step common to all pathways involves proton transfer from (cationic) K249 to (anionic) C253 and subsequent active-site rearrangement to align key amino acids and/or water for the next reaction step. In the first mechanism, K249 initiates deglycosylation as the nucleophile and the resulting DNA-protein cross-link is hydrolyzed to generate an abasic site. In the remaining two mechanisms, an active-site water molecule is the nucleophile, which is activated by either K249 or D268. These latter mechanisms are supported by MD simulations that reveal an abundance of water in the active site that could function as the nucleophile. Our ONIOM model suggests that the most likely mechanism involves water nucleophile activation by K249, which allows the active-site aspartate (D268) to electrostatically stabilize the charge buildup on the sugar residue throughout the entire reaction pathway. This newly conjectured mechanism is consistent with the proposed activity of other monofunctional glycosylases. In addition to providing the first atomic level evidence for a monofunctional hOgg1 catalytic pathway, the mechanistic details revealed in the present work can be used to direct future large-scale reaction modeling on the entire DNA-protein complex, which can be coupled with experimental kinetic data to afford a reliable comparison of the potential mono- and bifunctional activity of this crucial enzyme.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".