Many-Body Effects in Systems of Peptide Hydrogen-Bonded Networks and Their Contributions to Ligand Binding: A Comparison of the Performances of DFT and Polarizable Molecular Mechanics
Bibliographic record
Abstract
We compute the stabilization energies of the complexes formed between formate or water and a linear array of n = 2−5 N -methylformamide (NMF) molecules. We perform density functional theory (DFT), ab initio SCF and MP2, and SIBFA molecular mechanics computations. A very significant amount of cooperativity is found by DFT in the formate--(NMF) n complexes, amounting to −17 kcal/mol with n = 5. The SIBFA computations with fixed internal geometries for the monomers recover up to 80% of the DFT values. Single-point SCF/MP2 computations at the SIBFA-optimized geometries give binding energies and cooperativities very close to the SIBFA values. Solvation effects as represented by a continuum reaction field procedure are found to affect cooperativity to a modest extent. The implications for oligopeptides are 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".