Glycosidic Bond Cleavage in DNA Nucleosides: Effect of Nucleobase Damage and Activation on the Mechanism and Barrier
Bibliographic record
Abstract
Although DNA damage can have a variety of deleterious effects on cells (e.g., senescence, death, and rapid growth), the base excision repair (BER) pathway combats the effects by removing several types of damaged DNA. Since the first BER step involves cleavage of the bond between the damaged nucleobase and the DNA sugar-phosphate backbone, we have used density functional theory to compare the intrinsic stability of the glycosidic bond in a number of common DNA oxidation, deamination, and alkylation products to the corresponding natural nucleosides. Our calculations predict that the dissociative (SN1) and associative (SN2) pathways are nearly isoenergetic, with the dissociative pathway only slightly favored on the Gibbs reaction surface for all canonical and damaged nucleosides, which suggests that DNA damage does not affect the inherently most favorable deglycosylation pathway. More importantly, with the exception of thymine glycol, all DNA lesions exhibit reduced glycosidic bond stability relative to the undamaged nucleosides. Furthermore, the trend in the magnitude of the deglycosylation barrier reduction directly correlates with the relative nucleobase acidity (at N9 for purines or N1 for pyrimidines), which thereby provides a computationally efficient, qualitative measure of the glycosidic bond stability in DNA damage. The effect of nucleobase activation (protonation) at different sites predicts that the positions leading to the largest reductions in the deglycosylation barrier are typically used by DNA glycosylases to facilitate base excision. Finally, deaza purine derivatives are found to have greater glycosidic bond stability than the canonical counterparts, which suggests that alterations to excision rates measured using these derivatives to probe DNA glycosylase function must be interpreted in reference to the inherent differences in the nucleoside reactivity. Combined with previous studies of the deglycosylation of DNA nucleosides, the current study provides a greater fundamental understanding about the reactivity of the glycosidic bond in damaged DNA, which has direct implications to the function of critical DNA repair enzymes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".