DOI

https://doi.org/10.25772/V3QD-DP65

Defense Date

2015

Document Type

Dissertation

Degree Name

Doctor of Philosophy

Department

Microbiology & Immunology

First Advisor

Dr. Ping Xu

Second Advisor

Dr. W. Mike Holmes

Third Advisor

Dr. Glen E. Kellogg

Fourth Advisor

Dr. Todd Kitten

Fifth Advisor

Dr. Yan Zhang

Abstract

The human body is colonized by more than 100 trillion microbes which make up an essential part of the body and plays a significant role in health. We now know the over use and misuse of broad-spectrum antibiotics can disrupt this microbiome contributing to the onset of disease and runs the risk of promoting antibiotic resistance. With antibiotic research still on the decline, new strategies are greatly needed to combat emerging pathogens while maintaining a healthy microbiome. We therefore set out to present a novel species-selective antimicrobial drug discovery strategy.

Disruption of the homeostasis within the oral cavity can trigger the onset of one of the most common bacterial infections, periodontal disease. Even though the oral cavity is one of the most diverse sites on the human body, the Gram-negative colonizer, Porphyromonas gingivalis has long been considered a key player in the initiation of periodontitis, suggesting the potential for novel narrow-spectrum therapeutics. By targeting key pathogens, it may be possible to treat periodontitis while allowing for the recolonization of the beneficial, healthy flora. Therefore, we set out to use P. gingivalis and periodontal disease as a model for pathogen-specific antimicrobial drug discovery.

In this study we present a unique approach to predict essential gene targets selective for the periodontal pathogen within the oral environment. Using our knowledge of metabolic networks and essential genes we identified a “druggable” essential target, meso-diaminopimelate dehydrogenase, which is found in a limited number of species. This enzyme, meso-diaminopimelate dehydrogenase from P. gingivalis, was first expressed and purified, then characterized for enzymatic inhibitor screening studies. We then applied a computer-based drug discovery method, combining pharmacophore models, high-throughput virtual screening and molecular docking. Utilizing the ZINC database we virtually screened over 9 million small-molecules to identify several potential target-specific inhibitors. Finally, we used target-based and whole-cell based biochemical screening to assess in vitro activity. We conclude that the establishment of this target and screening strategy provides a framework for the future development of new antimicrobials and drug discovery.

Rights

© The Author

Is Part Of

VCU University Archives

Is Part Of

VCU Theses and Dissertations

Date of Submission

10-29-2015

Included in

Bacteriology Commons

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