Conformational Preference of Fused Carbohydrate-Templated Proline Analogues—A Computational Study
Bibliographic record
Abstract
The structure of fused C-glucosylproline hybrid (GlcProH) has been studied in detail computationally. A systematic molecular mechanics/Monte Carlo search has been performed in order to cover the entire conformational space of GlcProH. This has been followed by density-functional (DFT B3LYP) calculations in the gas phase and in aqueous solution, using the polarizable continuum model (PCM). In the gas phase, a large excess of the cis conformation with respect to the prolyl amide bond is found. This is reversed in aqueous solution where the calculations show 80% trans conformers, which is in accordance with experimental data. Thus, the PCM model is capable of accurately predicting cis-trans ratios. The free energy of solvation is not correlated with the dipole moment. Hence, a model (such as PCM) is required that takes into account the complete charge distribution. The reversal of the cis-trans ratio between gas phase and solution also emphasizes the effects of different free energies of solvation for the distinct conformers. Nevertheless, the energy difference between the cis and trans conformers is very small in solution (0.18 kcal/mol). Intramolecular hydrogen bonding is found to stabilize the cis conformers exclusively, which is a result of the rigid geometry of the fused rings. This can be contrasted to related more flexible molecules that show hydrogen bonding for both cis and trans isomers. The hydrogen bonding is at least partially responsible for the preferential stabilization of the cis conformers in the gas phase and a very small cis-trans energy difference in solution.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".