Global incorporation of meta-fluorotyrosine or meta-fluorophenylalanine into 1,2-catechol dioxygenase modulates the binding affinities of substrates
Bibliographic record
Abstract
Introduction Previous studies have shown how replacing canonical residues with isosteric amino acid analogs in enzymes can predictably alter biocatalytic activities by introducing variations in the first and second shell residues relative to the binding pocket. In this study, we explore the global integration of amino acid analogs into 1,2-catechol dioxygenase from Rhodococcus opacus (Rho 1,2-CTD), an industrial enzyme containing non-heme iron that is vital for phenol ring degradation. Methods We replaced tyrosine residues in the first shell of the binding pocket, phenylalanine residues in the second shell, and methionine residues near the binding pocket with m-fluorotyrosine (m-FY), m-fluorophenylalanine (m-FF), and Nle, respectively, using auxotrophic Escherichia coli strains. Results The expression, purification, and incorporation of m-FY and m-FF into the Rho 1,2-CTD was successful, but the Nle-insertion did not work. The structural characterization of the resulting m-FF- and m-FY-containing variants provided a mechanistic framework and plausible explanation for the results of the kinetic analyses of the native enzyme and fluorinated variants. Discussion Our findings demonstrate the impact of fluorination on the activity of 1,2-catechol dioxygenase, revealing its influence on residues near the substrate (first shell) as well as those distant from the binding pocket (second shell). This provides a robust foundation for future engineering activity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".