Analysis of bacterial cell-wall synthesis to combat antibiotic resistance
Bibliographic record
Abstract
The peptidoglycan biosynthetic pathway is one of the most important processes in the bacterial cell to be exploited as a target for the design of antimicrobial drugs to combat infection and pathogenesis. This pathway, unique to bacteria, utilizes over twenty enzymes, likely in concert, with reactions that proceed from the cytoplasm, across the membrane and into the periplasmic space culminating in the production of the mesh-like structure composed of polymerized glycan and cross-linked peptide components that form the major structural component of the essential bacterial protective barrier known as the cell wall. Work in our group has aimed at understanding the structural and kinetic properties of several of these enzymes including the glycosyltransferase/transpeptidase activity of a family of enzymes known historically as the penicillin binding proteins (PBPs). As the name implies, these enzymes are also the target of beta-lactam antibiotics, and molecular modifications to transpeptidase variants have been shown to be linked to increased antibiotic resistance in superbugs such as Methicillin Resistant Staphlococcal aureus (MRSA). In parallel, highly disseminated plasmid-encoded beta-lactamase enzymes, with structural and mechanistic ties to the transpeptidases, have also arisen in many of the clinically important bacterial pathogens, leading to further widespread beta-lactam antibiotic resistance. The molecular details of these critical enzymatic reactions in bacterial viability and drug resistance will be presented.
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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 | 0.001 |
| 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 | 0.001 |
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".