The search for inhibitors of O-acetylpeptidoglycan esterase 1a (Ape1a) in Neisseria gonorrhoeae
Bibliographic record
Abstract
This thesis reports an investigation and discovery of an inhibitor of O-acetylpeptidoglycan esterase 1a (Ape1a). With the rise in rates of antibiotic resistant microbes it is becoming increasingly important to discover new targets related to the cell wall, cell membrane, or synthesis of nucleic acids and proteins. Ape1a, an esterase responsible for cleaving the acetyl group from MurNAc and allowing the activity of muramidases, presented as a potential target. Optimal storage conditions of the enzyme were determined and an assay that was amenable to high throughput screening (HTS) was developed. Ape1a was then screened against a selection from the Canadian Compound Collection in an effort to discover an inhibitor. Several compounds were determined to be false positives; however one compound, purpurin, showed true inhibition. MICs performed 'in vivo' on various Gram positive and Gram negative organisms corroborated the microtitre plate findings. These findings were further supported by results from testing performed on PO, Ape1a's natural substrate. Purpurin was found to be an effective inhibitor of 'B. cereus', an O-acetylated organism, at a relatively low concentration of 16 [mu]g/ml. These results supported the hypothesis that Ape1a is necessary for cell viability in organisms possessing Ape1a Thus, this compound serves as a potential target for drug development and may aid in the fight against drug resistant microbes.
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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".