Molecular Modeling of the Major DNA Adduct Formed from Food Mutagen Ochratoxin A in <i>Nar</i>I Two-Base Deletion Duplexes: Impact of Sequence Context and Adduct Ionization on Conformational Preference and Mutagenicity
Bibliographic record
Abstract
Exposure to ochratoxin A (OTA), a possible human carcinogen, leads to many different DNA mutations. As a first step toward understanding the structural basis of OTA-induced mutagenicity, the present work uses a robust computational approach and a slipped mutagenic intermediate model previously studied for C 8 -dG aromatic amine adducts to analyze the conformational features of postreplication two-base deletion DNA duplexes containing OT-dG, the major OTA lesion at the C 8 position of guanine. Specifically, a total of 960 ns of molecular dynamics simulations (excluding trial simulations) were carried out on four OT-dG ionization states in three sequence contexts within oligomers containing the Nar I recognition sequence, a known hotspot for deletion mutations induced by related adducts formed from known carcinogens. Our results indicate that the structural properties and relative stability of the competing “major groove” and “stacked” conformations of OTA adducted two-base deletion duplexes depend on both the OTA ionization state and the sequence context, mainly due to conformation-dependent deviations in discrete local (hydrogen-bonding and stacking) interactions at the lesion site, as well as DNA bending. When the structural characteristics of the OT-dG adducted two-base deletion duplexes are compared to those associated with previously studied C 8 -dG adducts, a greater understanding of the effects of the nucleobase–carcinogen linkage, and size of the carcinogenic moiety on the conformational preferences of damaged DNA is obtained. Most importantly, our work predicts key structural features for OT-dG-adducted deletion DNA duplexes, which in turn allow us to develop hypotheses regarding OT-dG replication outcomes. Thus, our computational results are valuable for the design and interpretation of future biochemical studies on the potentially carcinogenic OT-dG lesion.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".