Quantum capping potentials with point charges: A simple QM/MM approach for the calculation of large-molecule NMR shielding tensors
Bibliographic record
Abstract
A simple quantum-mechanics/molecular-mechanics (QM/MM) approach for calculating NMR shielding tensors (sigma) is presented. The method involves capping the QM region with quantum capping potentials (QCPs) and representing the MM region with point charges. Test calculations on simple systems without MM charges show that calculated sigma values improve relative to the full QM results with increasing distance between the capped bond and chromophore. Calculations on the histidine amino acid and cytosine monophosphate (CMP) nucleic acid show that the use of QCPs with point charges result in mean errors in the isotropic component of sigma that are less than 1.6 ppm. The results also reveal that, contrary to previous work, the explicit effect of point charges on sigma through coupling with gauge factors, as in the gauge including atomic orbital approach, is minimal for the CMP molecule. The present QM/MM approach for calculating sigma is easy to apply and requires no code modification.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".