Date of Award
Doctor of Philosophy (PhD)
Richard E. Lee, PhD
Marcus Fischer, PhD; Kirk E. Hevener, PhD; Bernd Meibohm, PhD; Fatima Rivas, PhD
Antibiotic Resistance, Computer Aided Drug Discovery, Drug Discovery, H. pylori, Structure Based Design, Virtual Screening
Helicobacter pylori is a high-priority drug-resistant pathogen and is currently the only bacteria considered to be a class I carcinogen and there is a critical need to identify novel chemical matter to treat H. pylori infections. Hp is responsible for greater than 60% of gastric cancer related deaths and 89% of all gastric cancer morbidities. In a previous study, our lab identified novel Hp thienopyrmidine inhibitors that target respiratory complex I, an essential enzyme in respiration. Respiratory complex I is a large asymmetric multidomain and membrane bound enzyme and due to these innate features, it is not practical for biophysical or biochemical enzyme screening making it an ideal candidate for computer-aided drug discovery. To employ structure-based design we developed a homology model of the NuoD and NuoB subunits of respiratory complex I. The homology model was used to build a docking grid based on the sites of mutation from the generated resistant mutants, a previously found H. pylori complex I inhibitor, and known quinone binding. The docking grid was validated using a library of known actives and DUD-E generated decoys through enrichment. The validated model provided an AU-ROC of 0.92 and was used to determine a threshold for selecting molecules for biological evaluation. After previous success using our docking protocol, we screened the St. Jude Chemical Library comprising of approximately 600,000 compounds, which were then filtered for optimal drug-like properties, resulting in 74 Hp active compounds. With continued success of the virtual screening protocol, a set of 4.2 million compounds with molecular weight up to 400 g/mol and logP 4 from the ZINC20 in-stock screening library was docked. These hits will be used for continued development of our diverse chemical library and for hit-to-lead optimization to find novel and narrow-spectrum Hp inhibitors.
Vita, Nicole Ann (https://orcid.org/0000-0003-4985-6662), "Computer-Aided Drug Discovery for Helicobacter pylori" (2022). Theses and Dissertations (ETD). Paper 624. http://dx.doi.org/10.21007/etd.cghs.2022.0611.
Bacterial Infections and Mycoses Commons, Investigative Techniques Commons, Medical Biochemistry Commons, Medical Biomathematics and Biometrics Commons, Medical Pharmacology Commons, Medicinal and Pharmaceutical Chemistry Commons, Pharmaceutics and Drug Design Commons