Targeting antibiotic resistance through a versatile pantetheine scaffold: pantetheine derivatives as AAC(6')-Ii resistance inhibitors and novel pantothenamide antibacterial agents
Bibliographic record
Abstract
Aminoglycosides are broad-spectrum antibiotics used in the treatment of serious infections. With the rapid emergence and spread of antibiotic resistance, their therapeutic use is becoming increasingly threatened. The most common mechanism of aminoglycoside resistance is the expression of aminoglycoside-modifying enzymes (AMEs). Aminoglycoside 6'-N-acetyltransferase-Ii (AAC(6')-Ii) is a chromosomally-encoded enzyme in Enterococcus faecium, which transfers an acetyl group from AcCoA to the 6'-NH2 of aminoglycosides. Many inhibitors of this enzyme have been reported by the Auclair group. Initially, bisubstrate inhibitors containing aminoglycoside and CoA moieties were generated, which were nanomolar inhibitors of AAC(6')-Ii, and served as useful structural and mechanistic probes. However, the presence of negatively charged phosphate groups precluded their membrane permeation and thus a second generation of truncated bisubstrate inhibitors was subsequently reported. It was demonstrated that the diphosphate group could effectively be mimicked by an acetoacetate moiety to afford a "lead" compound which was shown to be the first inhibitor active in cells, albeit at reduced activity over the bisubstrates. The work presented in this thesis encompasses a multi-faceted approach to targeting aminoglycoside resistance through 1) the inhibition of AAC(6')-Ii; and 2) the development of a novel class of antibacterial agents. A medicinal chemistry approach was used to improve the potency of the "lead" compound inhibitor through the insertion of alternative diphosphate mimics such as a squarate ester or an acetylsulfamate. As described in Chapter 2, we hoped this would improve upon the stability of the acetoacetate group, while maintaining key hydrogen-bonding interactions to the enzyme. The synthesis of these molecules however, proved more challenging than expected, and efforts were instead focused on the work described in subsequent chapters. In Chapter 3, a rigidification strategy was employed to improve the affinity of the lead molecule for AAC(6')-Ii by reducing the entropic cost of binding. Rigidified, triazole-containing derivatives were found to have a positive effect on the affinity of inhibitors for AAC(6')-Ii, and showed comparable in-cell activity to that of the lead. Next, Chapter 4 describes the use of a previously established prodrug strategy which capitalizes on the CoA biosynthetic pathway in order to extend aminoglycoside-pantetheine derivatives into potent bisubstrate inhibitors in cells. The effect of rigidification on the activity of the prodrugs was investigated. These compounds were not active in cells, which resulted from their poor in-cell extension. Finally, pantothenamide derivatives were synthesized and tested as reported in Chapter 5. Pantothenamides constitute a promising class of antibacterial agents, which has recently gained much attention. The molecules are extended by the CoA biosynthetic enzymes into inhibitors of downstream effector proteins. Chapter 5 reports the synthesis and biological activity of novel pantothenamides which were generated as part of a large-scale study. Although the molecules reported in this thesis were not the most active of the series, the results contribute to important SARs and provide a better understanding of the selectivity of PanK, the first, and rate-limiting step of CoA biosynthesis. Contributions and experimental methods comprise the final chapters of this thesis.
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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 | 0.001 |
| 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".