Identification of the Catalytic Residues of AroA (<i>Enol</i>pyruvylshikimate 3-Phosphate Synthase) Using Partitioning Analysis
Bibliographic record
Abstract
AroA (EPSP synthase) catalyzes carboxyvinyl transfer through addition of shikimate 3-phosphate (S3P) to phosphoenolpyruvate (PEP) to form a tetrahedral intermediate (THI), followed by phosphate elimination to give enolpyruvylshikimate 3-phosphate (EPSP). A novel approach, partitioning analysis, was used to elucidate the roles of catalytic residues in each step of the reaction. Partitioning analysis involved trapping and purifying [1-(14)C]THI, degrading it with AroA, and quantitating the products. Wild-type AroA gave a partitioning factor, f(PEP) = 0.25 +/- 0.02 at pH 7.5, where f(PEP) = [[1-(14)C]PEP]/([[1-(14)C]PEP] + [[1-(14)C]EPSP]). Eighteen mutations were made to 14 amino acids to discover which residues preferentially catalyzed either the addition or the elimination step. Mutating a residue catalyzing one step (e.g., addition) should change f(PEP) to favor the opposite step (e.g., elimination). No mutants caused large changes in f(PEP), with experimental values from 0.07 to 0.41. This implied that there are no side chains that catalyze only addition or elimination, which further implied that the same residues are general acid/base catalysts in both forward and reverse THI breakdown. Only Lys22 (protonating S3P hydroxyl or phosphate) and Glu341 (deprotonating C3 of PEP) are correctly situated in the active site. In the overall reaction, Lys22 would act as a general base during addition, while Glu341 would act as a general acid. Almost half of the mutations (eight of 18) caused a >1000-fold decrease in specific activity, demonstrating that a large number of residues are important for transition state stabilization, "ensemble catalysis", in contrast to some enzymes where a single amino acid can be responsible for up to 10(8)-fold catalytic enhancement.
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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".