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.
","abstract_html":"<p>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.</p>","abstract_has_math":false,"creators":["Vita, Nicole Ann"],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Dissertation","degree_discipline":"Pharmaceutical Sciences","degree_department":null,"school":null,"contributors":["Richard E. Lee, PhD"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-12-01T08:00:00Z","date_published":"2022-12-01T08:00:00Z","updated_at":"2026-07-24T05:00:45Z","subjects":["Antibiotic Resistance","Computer Aided Drug Discovery","Drug Discovery","H. pylori","Structure Based Design","Virtual Screening","Analytical, Diagnostic and Therapeutic Techniques and Equipment","Bacterial Infections and Mycoses","Diseases","Investigative Techniques","Medical Biochemistry","Medical Biomathematics and Biometrics","Medical Pharmacology","Medical Sciences","Medicinal and Pharmaceutical Chemistry","Medicine and Health Sciences","Pharmaceutics and Drug Design","Pharmacy and Pharmaceutical Sciences"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://dc.uthsc.edu/dissertations/624","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Richard E. Lee, PhD"]},{"key":"dc:creator","label":"Author","values":["Vita, Nicole Ann"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2023-01-12T08:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Pharmaceutical Sciences"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Antibiotic Resistance","Computer Aided Drug Discovery","Drug Discovery","H. pylori","Structure Based Design","Virtual Screening","Analytical, Diagnostic and Therapeutic Techniques and Equipment","Bacterial Infections and Mycoses","Diseases","Investigative Techniques","Medical Biochemistry","Medical Biomathematics and Biometrics","Medical Pharmacology","Medical Sciences","Medicinal and Pharmaceutical Chemistry","Medicine and Health Sciences","Pharmaceutics and Drug Design","Pharmacy and Pharmaceutical Sciences"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://dc.uthsc.edu/dissertations/624"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["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.
"]},{"key":"dc:title","label":"Title","values":["Computer-Aided Drug Discovery for Helicobacter pylori"]}]}],"canonical_facts":{"dc:contributor":["Richard E. Lee, PhD"],"dc:creator":["Vita, Nicole Ann"],"dc:date.available":["2023-01-12T08:00:00Z"],"dc:description.abstract":["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.
"],"dc:identifier":["https://dc.uthsc.edu/dissertations/624"],"dc:subject":["Antibiotic Resistance","Computer Aided Drug Discovery","Drug Discovery","H. pylori","Structure Based Design","Virtual Screening","Analytical, Diagnostic and Therapeutic Techniques and Equipment","Bacterial Infections and Mycoses","Diseases","Investigative Techniques","Medical Biochemistry","Medical Biomathematics and Biometrics","Medical Pharmacology","Medical Sciences","Medicinal and Pharmaceutical Chemistry","Medicine and Health Sciences","Pharmaceutics and Drug Design","Pharmacy and Pharmaceutical Sciences"],"dc:title":["Computer-Aided Drug Discovery for Helicobacter pylori"],"thesis:degree_discipline":["Pharmaceutical Sciences"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-24T05:00:45Z"}