Intramolecular interaction energies in model alanine and glycine tetrapeptides. Evaluation of anisotropy, polarization, and correlation effects. A parallel <i>ab initio</i> HF/MP2, DFT, and polarizable molecular mechanics study
Bibliographic record
Abstract
An extension of the SIBFA polarizable molecular mechanics procedure to flexible oligopeptides is reported. The procedure is evaluated by computing the relative conformational energies, deltaE(conf), of the alanine tetrapeptide in 10 representative conformations, which were originally derived by Beachy et al. (J Am Chem Soc 1997, 119, 5908) to benchmark molecular mechanics procedures with respect to ab initio computations. In the present study, a particular emphasis is on the separable nature of the components of the energy and the particular impact of the polarization energy component on deltaE(conf). We perform comparisons with respect to single-point HF, DFT, LMP2, and MP2 computations done at the SIBFA-derived energy minima. Such comparisons are made first for the 10 conformers derived from phi/psi torsional angle energy-minimization (the rigid rotor approach), and, in a second step, after allowing additional relaxation of the C(alpha) centered valence angles. In both series of energy-minimization, the SIBFA deltaE(conf) compared best with the LMP2 results using the 6-311G** basis set, the rms being 1.3 kcal/mol. In the absence of the polarization component, the rms is 3.5 kcal/mol. In both series of minimizations, the magnitudes of deltaE(conf), computed as differences with respect to the most stable conformer taken as energy zero, decrease along the series: HF > DFT > LMP2 > SIBFA > MP2, indicative of increasing stabilization of the most highly folded conformers.
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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 | 0.000 |
| 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 | 0.000 | 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".