Metal binding and inhibition of Class II fructose 1,6‐bisphosphate aldolase
Bibliographic record
Abstract
Fructose 1,6-bisphosphate (FBP) aldolase (E.C. 4.1.2.13) catalyzes the reversible aldol condensation of dihydroxyacetonephosphate and glyceraldehyde 3-phosphate in the Calvin cycle, glycolysis and gluconeogenesis. The FBP aldolases are divided in two groups depending on the reaction mechanism: Class I aldolases form a Schiff-base intermediate with the substrate and Class II aldolases instead use a divalent metal to stabilize the carbanion intermediate. Since the Class II aldolase is not present in animals or plants, it has been suggested that it could be a viable drug target. Derivatives of the metal binding agent 2,6-pyridinedicarboxylic acid were synthesized and tested against the Class II FBP aldolases from Mycobacterium tuberculosis, Pseudomonas aeruginosa, Bacillus cereus and Magnaporthe grisea. Molecular modeling of the derivatives in the enzymes’ active site was also used to design a new generation of inhibitors. The derivatives were found to behave as specific mixed inhibitors of the aldol cleavage reaction. The metal binding affinity of the inhibitor compounds and Class II FBP aldolases were determined, and compared with the inhibition constants obtained to estimate the compounds’ affinity for the enzymes’ active site. This work was supported by grants from the Natural Sciences and Engineering Research Council of Canada. G.L. is the recipient of an Ontario Graduate Scholarship.
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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".