The Impact of Second Coordination Sphere Methionine-Aromatic Interactions in Copper Proteins
Bibliographic record
Abstract
The interplay between the primary and secondary coordination spheres in biological metal sites plays an essential role in controlling their properties. Some of the clearest examples of this are from copper sites in blue and purple copper proteins. Many such proteins contain methionine (Met) in the primary coordination sphere as a weakly bound ligand to Cu. While the effects of replacing the coordinated Met are understood, less so is the importance of its second-sphere interactions. In this combined informatics and experimental study, we first present a bioinformatics investigation of the second-sphere environments in biological Met-Cu motifs. The most common interaction is between the Met-CH 3 and the π-face of a phenylalanine (Phe) (81% of surveyed structures), tyrosine (Tyr) (11%), and tryptophan (Trp) (8%). In most cases, the Met-CH 3 also forms a contact with a π-face of one of a Cu-ligating histidine-imidazole. Such interactions are widely distributed in different Cu proteins. Second, to explore the impact of the second-sphere interactions of Met, a series of artificial Pseudomonas aeruginosa azurin proteins were produced where the native Phe15 was replaced with Tyr or Trp. The proteins were characterized using optical and magnetic resonance spectroscopies, X-ray diffraction, electrochemistry, and an investigation of the time-resolved electron-transfer kinetics of photosensitizer-modified proteins. The influence of the Cu-Met-Aro interaction on azurin’s physical properties is subtle, and the hallmarks of the azurin blue copper site are maintained. In the Phe15Trp variant, the mutation to Phe15 induces changes in Cu properties that are comparable to replacement of the weak Met ligand. The broader impacts of these widely distributed interactions are discussed.
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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) | 0.001 | 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".