Clustering of Aromatic Amino Acid Residues around Methionine in Proteins
Bibliographic record
Abstract
Short-range, non-covalent interactions between amino acid residues determine protein structures and contribute to protein functions in diverse ways. The interactions of the thioether of methionine with the aromatic rings of tyrosine, tryptophan, and/or phenylalanine has long been discussed and such interactions are favorable on the order of 1–3 kcal mol−1. Here, we carry out a new bioinformatics survey of known protein structures where we assay the propensity of three aromatic residues to localize around the [-CH2-S-CH3] of methionine. We term these groups “3-bridge clusters”. A dataset consisting of 33,819 proteins with less than 90% sequence identity was analyzed and such clusters were found in 4093 structures (or 12% of the non-redundant dataset). All sub-classes of enzymes were represented. A 3D coordinate analysis shows that most aromatic groups localize near the CH2 and CH3 of methionine. Quantum chemical calculations support that the 3-bridge clusters involve a network of interactions that involve the Met-S, Met-CH2, Met-CH3, and the π systems of nearby aromatic amino acid residues. Selected examples of proposed functions of 3-bridge clusters are discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".