Multiscale QM/MM Molecular Dynamics Study on the First Steps of Guanine Damage by Free Hydroxyl Radicals in Solution
Bibliographic record
Abstract
Understanding the damage of DNA bases from hydrogen abstraction by free OH radicals is of particular importance to understanding the indirect effect of ionizing radiation. Previous studies address the problem with truncated DNA bases as ab initio quantum simulations required to study such electronic-spin-dependent processes are computationally expensive. Here, for the first time, we employ a multiscale and hybrid quantum mechanical-molecular mechanical simulation to study the interaction of OH radicals with a guanine-deoxyribose-phosphate DNA molecular unit in the presence of water, where all of the water molecules and the deoxyribose-phosphate fragment are treated with the simplistic classical molecular mechanical scheme. Our result illustrates that the presence of water strongly alters the hydrogen-abstraction reaction as the hydrogen bonding of OH radicals with water restricts the relative orientation of the OH radicals with respect to the DNA base (here, guanine). This results in an angular anisotropy in the chemical pathway and a lower efficiency in the hydrogen-abstraction mechanisms than previously anticipated for identical systems in vacuum. The method can easily be extended to single- and double-stranded DNA without any appreciable computational cost as these molecular units can be treated in the classical subsystem, as has been demonstrated here.
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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) | 0.000 | 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".