Effect of Size and Shape of Nitrogen-Containing Aromatics on Conformational Preferences of DNA Containing Damaged Guanine
Bibliographic record
Abstract
The present work investigates the effects of the size and shape of the nitrogen-containing aromatic (NCA) skeleton on the structure of DNA damaged through adduct formation at C 8 of 2′-deoxyguanosine (dG), a common DNA lesion associated with chemical carcinogenesis. Specifically, density functional theory (DFT) calculations (B3LYP-D3) and molecular dynamics (MD) simulations (AMBER) are performed on seven model adducts with systematic expansion of the NCA moiety. DFT calculations reveal that the NCA moiety shape affects the structure at the nucleobase–carcinogen linkage. Approximately 4.5 μs of MD simulations on damaged oligonucleotides adopting three established conformational themes (namely, B, W, and S) illustrate that the structure and lesion-site stabilization strongly depend on the NCA moiety shape and size, which provides insight into the repair propensity of C 8 -dG adducted DNA. Our results add bulky moiety shape to the growing list of previously established effects on the conformational and repair outcomes of damaged DNA (i.e., size, ionization state, substitution, linker type, and DNA sequence). Furthermore, this work illustrates the utility of a systematic set of model DNA lesions for understanding the structure–activity relationship for DNA damaged by carcinogens of different sizes and shapes, which should be used in future studies of the cellular processing of damaged DNA.
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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) | 0.002 | 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".