Conformational Analysis of Oligoarabinofuranosides: Overcoming Torsional Barriers with Umbrella Sampling
Bibliographic record
Abstract
In this report, the conformations of a series of mono- and oligoarabinofuranosides were probed through the use of umbrella sampling simulations with the AMBER force field and the GLYCAM carbohydrate parameter set. The rotamer population distribution about the exocyclic C4-C5 bonds and the puckering distributions of the rings obtained from these umbrella sampling simulations were found to be in excellent agreement with those obtained from conventional long MD simulations for small monosaccharide fragments. For larger systems, the conventional MD approach becomes impractical, and we propose the use of umbrella sampling to circumvent poor sampling of certain conformations. The same umbrella sampling simulations were used to calculate the distributions about the vicinal protons and ensemble-averaged vicinal proton-proton coupling constants ((3)JH,H). The distributions about the vicinal protons of a monomer, methyl-α-l-arabinofuranoside (1), were found to be very similar to those obtained from direct umbrella sampling simulations about the vicinal protons. We calculated (3)JH,H based on DFT-based Karplus-like relationships for l-arabinofuranosides. The (3)JH,H values were found to be very similar to those obtained with the conventional MD simulations. For 1, the (3)JH,H values obtained with the DFT-based Karplus equations agree very well with experimental results; the agreement is, however, not as good for the larger oligomers. An approach to determine the experimental rotamer populations from the simulations is also discussed.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".