Structural Insight into the Discrimination between 8-Oxoguanine Glycosidic Conformers by DNA Repair Enzymes: A Molecular Dynamics Study of Human Oxoguanine Glycosylase 1 and Formamidopyrimidine-DNA Glycosylase
Bibliographic record
Abstract
hOgg1 and FPG are the primary DNA repair enzymes responsible for removing the major guanine (G) oxidative product, namely, 7,8-dihydro-8-oxoguanine (OG), in humans and bacteria, respectively. While natural G adopts the anti conformation and forms a Watson-Crick pair with cytosine (C), OG can also adopt the syn conformation and form a Hoogsteen pair with adenine (A). hOgg1 removes OG paired with C but is inactive toward the OG:A pair. In contrast, FPG removes OG from OG:C pairs and also exhibits appreciable (although diminished) activity toward OG:A pairs. As a first step toward understanding this difference in activity, we have employed molecular dynamics simulations to examine how the anti and syn conformers of OG are accommodated in the hOgg1 and FPG active sites. When anti-OG is bound, hOgg1 active site residues are properly aligned to initiate catalytic base departure, while geometrical parameters required for the catalytic reaction are not conserved for syn-OG. On the other hand, the FPG catalytic residues are suitably aligned for both OG conformers, with anti-OG being more favorably bound. Thus, our data suggests that the differential ability of hOgg1 and FPG to accommodate the anti- and syn-OG glycosidic conformations is an important factor that contributes to the relative experimental excision rates. Nevertheless, the positions of the nucleophiles with respect to the lesion in the active sites suggest that the reactant complex is poised to initiate catalysis through a similar mechanism for both repair enzymes and supports a recently proposed mechanism in which sugar-ring opening precedes nucleoside deglycosylation.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".