Modeling the Dissociative Hydrolysis of the Natural DNA Nucleosides
Bibliographic record
Abstract
Two-dimensional PCM-B3LYP/6-31+G(d) potential energy surfaces for the hydrolysis of the four natural 2'-deoxyribonucleosides (2'-deoxyadenosine, 2'-deoxyguanosine, 2'-deoxycytidine, and thymidine) are characterized using a model that includes both implicit (bulk) solvent effects and (three or four) explicit water molecules in the optimization routine. For the first time, the experimentally predicted dissociative (S(N)1) mechanism is found to be favored over the synchronous (S(N)2) pathway for all nucleosides studied. Due to the success of our model in stabilizing the charge-separated intermediates along the S(N)1 pathway, it is proposed that the new model presented here is the smallest system capable of generating the experimentally predicted oxacarbenium cation intermediate. We therefore stress that dissociative mechanisms should be studied with methodologies that account for the (bulk) environment in the optimization routine, where these effects are often only included as a correction to the energy in the current literature. In addition to accounting for charge stabilization through implicit solvation, nucleophile activation and leaving group stabilization should also be explicitly introduced into the model to further stabilize the system. Our work also emphasizes the importance of studying the Gibbs surface, which in some cases provides a better description of chemically important regions of the reaction surface or changes the calculated trend in the magnitude of dissociative barriers. In addition, it is proposed that the methodology presented in this study can be used to calculate uncatalyzed deglycosylation barriers for a range of DNA nucleosides, which when compared to the corresponding enzyme-catalyzed reactions, will allow the prediction of the rate enhancement (barrier reduction) due to the enzyme.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".