id7b00214_si_001.pdf (203.28 kB)
Optimization of CoaD Inhibitors against Gram-Negative Organisms through Targeted Metabolomics
journal contribution
posted on 2017-12-15, 00:00 authored by Christopher
M. Rath, Bret M. Benton, Javier de Vicente, Joseph E. Drumm, Mei Geng, Cindy Li, Robert J. Moreau, Xiaoyu Shen, Colin K. Skepper, Micah Steffek, Kenneth Takeoka, Lisha Wang, Jun-Rong Wei, Wenjian Xu, Qiong Zhang, Brian Y. FengDrug-resistant Gram-negative bacteria
are of increasing concern worldwide. Novel antibiotics are needed,
but their development is complicated by the requirement to simultaneously
optimize molecules for target affinity and cellular potency, which
can result in divergent structure–activity relationships (SARs).
These challenges were exemplified during our attempts to optimize
inhibitors of the bacterial enzyme CoaD originally identified through
a biochemical screen. To facilitate lead optimization, we developed
mass spectroscopy assays based on the hypothesis that levels of CoA
metabolites would reflect the cellular enzymatic activity of CoaD.
Using these methods, we were able to monitor the effects of cellular
enzyme inhibition at compound concentrations up to 100-fold below
the minimum inhibitory concentration (MIC), a common metric of growth
inhibition. Furthermore, we generated a panel of efflux pump mutants
to dissect the susceptibility of a representative CoaD inhibitor to
efflux. These approaches allowed for a nuanced understanding of the
permeability and efflux liabilities of the series and helped guide
optimization efforts to achieve measurable MICs against wild-type E. coli.
History
Usage metrics
Categories
Keywords
enzyme CoaDMICgrowth inhibitionrepresentative CoaD inhibitorNovel antibioticsnuanced understandingenzyme inhibitionwild-type E . coliguide optimization effortscompound concentrationsSARmass spectroscopy assaysTargeted Metabolomics Drug-resistantCoaD Inhibitorstarget affinityefflux liabilities. coliCoA metabolitesGram-Negative Organisms
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC