Atoms‐in‐molecules study of the genetically encoded amino acids. II. Computational study of molecular geometries
Bibliographic record
Abstract
The geometries of the 20 genetically encoded amino acids were optimized at the restricted Hartree-Fock level of theory using the 6-31+G* basis set. A detailed comparison showed the calculated geometries to be in excellent agreement with those determined by X-ray crystallography. The study demonstrated that the geometric parameters for the main-chain group and for the bonds and common functional groups of the side-chains exhibit a high degree of transferability among the members of this set of molecules. This geometric transferability is a necessary prerequisite for the corresponding transferability of their electron density distributions and hence of their bond and atomic properties. The transferability of the electron distributions will be demonstrated and exploited in the following paper of this series, which uses the topology of the electron density to define an atom within the quantum theory of atoms in molecules. Particular features of the geometries of the amino acids are discussed. It has been shown, for example, how the apparent anomaly of the Calpha-N bond length in a peptide being shorter than in the charged species Calpha-NH3+ is resolved when the charge separation is gauged by the differences in the charges of the Calpha and N atoms as opposed to the use of formal charges. A compilation of literature sources on experimental geometries covering each member of the 20 amino acids is presented. A set of rules for labeling the atoms and bonds, complementing the generally accepted IUPAC-IUB rules, is proposed to uniquely identify every atom and bond in the amino acids.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".