MétaCan
Menu
Back to cohort
Record W6996886319

Targeting antibiotic resistance through a versatile pantetheine scaffold: pantetheine derivatives as AAC(6')-Ii resistance inhibitors and novel pantothenamide antibacterial agents

2013· dissertation· en· W6996886319 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2013
Typedissertation
Languageen
FieldNeuroscience
TopicNeurological diseases and metabolism
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchMcGill University
KeywordsAminoglycosideEnzymeMoietyAntibioticsLipid IIMechanism of actionAntibiotic resistanceAntibacterial agent
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.025
GPT teacher head0.260
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueeScholarship@McGill (McGill)Same topicNeurological diseases and metabolismFrench-language works237,207