Advisory Committee Chair
Advisory Committee Members
Date of Award
Degree Name by School
Doctor of Philosophy (PhD) Heersink School of Medicine
Deaths due to antibiotic-resistant bacteria are predicted to exceed 10 million per year by 2050, endangering our ability to conduct fundamental medical procedures such as immunosuppressive therapy or even basic surgery. Unfortunately, we are largely falling behind in the evolutionary arms race against common pathogens. Not only are we in sore need of new antibiotics, we also evidently need altogether new approaches to drug discovery itself, as our familiar avenues are increasingly failing to meet demands. In this dissertation, we describe a promising new source of antibacterials: copper-dependent inhibitors (CDIs), compounds that exert significant antibiotic activity only in the presence of physiological concentrations of copper ions. Herein, we explore the potential of CDIs as a novel class of antibiotics. Using Mycobacterium tuberculosis as a model organism, we characterized the activity of one CDI, disulfiram, finding that it primarily killed its target through copper poisoning. We speculated that it operated as a “Trojan Horse,” bypassing M. tuberculosis’ normal copper homeostatic machinery and destroying the cell from within. This contrasts with most traditional antibiotics, which generally exert a “one drug, one target” effect that can be easily countered with a single mutation in the target enzyme. Given that we could induce the striking antibacterial effects simply by modulating the media concentration of copper, rather than requiring directed synthesis efforts, we hypothesized that such activities may lie unseen within standard chemical libraries. To provide proof-of-principle for this hypothesis, we pioneered a unique combinatorial screen against Staphylococcus aureus to identify copper-dependent inhibitors in a small pilot assay, eventually developing a lead series, termed the NNSN compounds. Finally, we deployed this assay on an industrial high-throughput screening platform, resulting in hundreds of confirmed hit molecules. Subsequent cheminformatic analyses extracted ten unique hit clusters, all of which were unknown to possess antistaphylococcal activity. Thus, we have demonstrated that CDIs provide an encouraging new form of antibiotic discovery, readily uncovering new antibacterials in previously exhausted screening libraries.
Dalecki, Alex, "Cheminformatic Discovery And Characterization Of Copperdependent Bacterial Inhibitors" (2018). All ETDs from UAB. 1464.