Glycosidic Bond Cleavage in Deoxynucleotides: Effects of Solvent and the DNA Phosphate Backbone in the Computational Model
Bibliographic record
Abstract
Density functional theory (B3LYP) was employed to examine the hydrolysis of the canonical 2'-deoxynucleotides in varied environments (gas phase or water) using different computational models for the sugar residue (methyl or phosphate group at C5') and nucleophile (water activated through full or partial proton abstraction). Regardless of the degree of nucleophile activation, our results show that key geometrical parameters along the reaction pathway are notably altered upon direct inclusion of solvent effects in the optimization routine, which leads to significant changes in the reaction energetics and better agreement with experiment. Therefore, despite the wide use of gas-phase calculations in the literature, small model computational work, as well as large-scale enzyme models, that strive to understand nucleotide deglycosylation must adequately describe the environment. Alternatively, although inclusion of the phosphate group at C5' also affects the geometries of important stationary points, the effects cancel to yield unchanged deglycosylation barriers, and therefore smaller computational models can be used to estimate the energy associated with nucleotide deglycosylation, with the 5' phosphate group included if full (geometric) details of the reaction are desired. Hydrogen-bonding interactions with the nucleobase can significantly reduce the barrier to deglycosylation, which supports suggestions that discrete hydrogen-bonding interactions with active-site amino acid residues can play a significant role in enzyme-catalyzed nucleobase excision. Taken together with previous studies, the present work provides vital clues about the components that must be included in future studies of the deglycosylation of isolated noncanonical nucleotides, as well as the corresponding enzyme-catalyzed reactions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".