Theoretical Investigations on the Conformation of the β-<scp>d</scp>-Arabinofuranoside Ring
Bibliographic record
Abstract
A method for the conformational analysis of furanose rings that involves the prediction of (3)JH,H that can be compared directly to experimental values is investigated. This method, which differs from the traditional PSEUROT approach for conformational studies of furanose rings, was previously applied to a number of α-d-arabinofuranosides and enabled the direct comparison of (3)JH,H values to those obtained from NMR spectroscopy. In this paper, the use of this approach to study the conformational preferences of oligosaccharides containing β-linked arabinofuranose residues is reported. Density functional theory (DFT) calculations were carried out to derive Karplus relationships that are specifically tailored for these ring systems. In addition, probability distributions obtained from GLYCAM/AMBER molecular dynamics simulations were employed to calculate (3)JH,H values from these Karplus relationships. However, unlike the results obtained with α-arabinofuranosides, the (3)JH,H values computed for β-arabinofuranosides agreed poorly with experimental values. This prompted the exploration of other methodologies including reevaluation and optimization of the initial MD protocol, use of various force field models, and recalculation of the DFT-derived coupling profiles using an optimized basis set. After extensive investigations, we established that the conformer distributions obtained from MD simulations with the GLYCAM force fields and the furanoside-specific CHARMM force field in combination with the DFT Karplus equations, determined using an augmented basis set (B3LYP/aug-cc-pVTZ-J), produced the best agreement compared to experimental (3)JH,H values. Using these protocols, there is relatively good agreement in (3)JH,H for all coupling pathways with the exception of (3)J2,3 and (3)J3,4, which are underestimated.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".