Peptide models XXVII. An exploratory ab initio study on the 21<sup>st</sup> amino acid side-chain conformations of <i>N</i>-formyl-L-selenocysteinamide (For-L-Sec-NH<sub>2</sub>) and <i> N</i>-acetyl-L-selenocysteine-<i>N</i>-methylamide (Ac-L-Sec-NHMe) in their γ<sub>L</sub> backbone conformation
Bibliographic record
Abstract
Selenocysteine is expected to have 9 × 9 = 81 conformations [3 × 3 = 9 backbone: ψ (g+,a,g-) × ϕ (g+,a,g-) and 3 × 3 = 9 side-chain: χ1 (g+,a,g-) × χ2 (g+,a,g-)]. In the present study, all the torsional modes of the side-chain (χ1: rotation about the Cα-Cβ and χ2: rotation about the Cβ-Se bonds) were investigated in the relaxed γL backbone [(ϕ,ψ); (g-,g+)] conformation. Seven out of the nine expected minima were found at the RHF/3-21G level of theory for N-formyl-L-selenocysteinamide (For-L-Sec-NH2) and N-acetyl-L-selenocysteine-N-methylamide (Ac-L-Sec-NHMe). The stabilization energy exerted by the -CH2-SeH side-chain has been compared with that of -CH2-SH and -CH2-OH. Relative energies of the various conformers were also obtained via single point calculations at the B3LYP/6-31G(d,p) level of theory. Topological analysis of the electron density has been performed by Bader's Atoms in Molecule (AIM) approach using the results. The structures were also optimized at the B3LYP/6-31+G(d,p) level of theory.Key words: selenocysteine side-chain conformations, ab initio MO study, Multidimensional Conformational Analysis (MDCA), Atoms in Molecules (AIM), Bader's electron density analysis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".