Molecular Dynamics Study of One-Base Deletion Duplexes Containing the Major DNA Adduct Formed by Ochratoxin A: Effects of Sequence Context and Adduct Ionization State on Lesion Site Structure and Mutagenicity
Bibliographic record
Abstract
Ochratoxin A (OTA) is a ubiquitous food toxin associated with chronic nephropathy in humans and renal carcinogenicity in rodents. The mutational spectra of cells exposed to OTA reveal that one-base deletions comprise the largest percentage (73%) of the total mutations that occur upon OTA exposure. To contribute toward understanding the prevalence of OTA-induced one-base deletion mutations, the present work uses molecular dynamics (MD) simulations to analyze the conformational preferences of one-base deletion duplexes containing OT-G, the major OTA adduct ( add ition prod uct ) at the C 8 -site of guanine. Specifically, the influence of OT-G in four possible ionization states and three sequence contexts (G 1, G 2 and G 3 in the Nar I (5′–G 1 G 2 CG 3 CC–3′), a prokaryotic mutational hotspot sequence) on the structure of the adducted DNA is investigated. Our data reveal that the damaged helices are stable in two (B-type (B) and stacked (S)) conformations that are structurally similar to those adopted by common N-linked C 8 -guanine lesions. However, the adduct ionization state and sequence context affect the degree of helical distortion and the B/S conformational heterogeneity, which will impact the lesion repair and replication outcomes. This finding correlates with the experimentally reported tissue-specific mutagenicity of OTA exposure. Furthermore, regardless of the adduct conformation, ionization state, or sequence context, more stable lesion-site interactions and lack of disruption of the flanking base pairs in the one-base deletion duplexes compared to the corresponding two-base deletion helices rationalize the greater abundance of OTA induced one-base deletions. Overall, our work provides valuable structural insights that help explain the experimentally observed mutagenicity associated with OTA.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".