Data mining, ab initio, and molecular mechanics study on conformation of phenylalanine and its interaction with neighboring backbone amide groups in proteins
Bibliographic record
Abstract
Abstract Data mining results for 1029 X‐ray protein structures demonstrate that there are, on average, more than nine phenylalanine residues in a typical protein structure. Moreover, the conformations of these phenylalanine residues are not arbitrary but fall into four regular types. These four phenylalanine conformational types can be related to the interaction between the phenylalanine's phenyl group and its neighboring backbone amide groups. They are designated as “Aphe,” “Cphe,” “ACphe,” and “NACphe,” respectively, depending on the presence and absence of such phenyl–amide interactions. It is shown that 96.2% of the phenylalanine residues occurring in proteins fall into the first three types, which involve one or two types of these interactions. The side chain and associated backbone fragment of each phenylalanine type have characteristic conformational regularities. The interaction potential energy surfaces of these interactions were exhaustively and systematically evaluated by means of the validated CHARMm force field. We show that this force field produces interaction energies comparable to BSSE‐corrected values calculated using MP2/6‐311G(2d,2p) and MP2/6‐31+G(2d,p). The phenyl–amide interactions occurring in proteins have configurations corresponding to a stabilization energy of up to 11 kJ/mol in vacuum. None occur that would correspond to a phenyl–amide repulsion. We conclude that the phenyl–amide interaction is one of the factors responsible for the conformational regularity of the phenyalanine in proteins and that it is of significance due to its strength and common occurrence. © 2002 Wiley Periodicals, Inc. Int J Quantum Chem, 2002
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".