Mycobacterial drug target deconvolution using computational, genetic, phenotypic and proteomic approaches

Kingdon, Alexander David Harry ORCID: 0000-0001-7074-6893 (2023). Mycobacterial drug target deconvolution using computational, genetic, phenotypic and proteomic approaches. University of Birmingham. Ph.D.

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Abstract

Mycobacterium tuberculosis has burdened humanity for centuries, remains one of the largest global killers, and causes over ten million tuberculosis infections yearly. Resistance to the current treatment regimen is growing and new treatment options are required. Work was undertaken to target the essential M. tuberculosis protein, AroB, and study the mechanism of action of a recently discovered antimycobacterial compound, vanoxerine (GBR12909). Several tools were developed to allow the rapid screening of potential inhibitors against the AroB protein, including biochemical, biophysical, and in vitro assays. Computational screening identified potential inhibitors of AroB, however, no compounds showed activity in vitro or in vivo against AroB or mycobacteria. In contrast, screening a drug repurposing library identified the antimycobacterial activity of vanoxerine, but no known target. Previous work suggested vanoxerine targeted AroB, however, this work has demonstrated it is not the target. Evidence provided herein highlights vanoxerine is a disruptor of the membrane electric potential, with downstream inhibition of efflux and membrane transport. A more potent analogue of vanoxerine was also developed, retaining its mechanism of action, but possessing lower activity against the known human target. Vanoxerine also targeted the pathogenic Enterococcus faecium, suggesting routes for future development against multiple pathogenic species. Overall, this work provides a strong foundation for future drug discovery studies targeting M. tuberculosis.

Type of Work:

Thesis (Doctorates > Ph.D.)

Award Type:

Doctorates > Ph.D.

Supervisor(s):