Pharmacy and Pharmaceutical Sciences Commons^™

Computer-Aided Drug Design Of Bakuchiol-Inspired Lxrα Modulators Against Acute Lymphoblastic Leukemia, Dillon P. Cao

LSU Master's Theses

Acute lymphoblastic leukemia (ALL) is the most common type of cancer in children, accounting for approximately 25% of pediatric malignancies. Although glucocorticoids are commonly used to treat ALL, prolonged use can lead to steroid resistance, rendering the drug regimen ineffective. Therefore, alternative treatment avenues are needed for high- risk pediatric patients that do not respond well to traditional regimens.

Liver X Receptor α (LXRα) is presented as a potential alternative drug target for pediatric patients that exhibit suboptimal response to glucocorticoids. Limitations of the current LXRα modulators such as indiscriminate isoform selectivity between LXRα and LXRβ and consequent adverse effects …

Computer-Aided Drug Discovery For Helicobacter Pylori, Nicole Ann Vita

Theses and Dissertations (ETD)

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 …

Scalable Feature Selection And Extraction With Applications In Kinase Polypharmacology, Derek Jones

Theses and Dissertations--Computer Science

In order to reduce the time associated with and the costs of drug discovery, machine learning is being used to automate much of the work in this process. However the size and complex nature of molecular data makes the application of machine learning especially challenging. Much work must go into the process of engineering features that are then used to train machine learning models, costing considerable amounts of time and requiring the knowledge of domain experts to be most effective. The purpose of this work is to demonstrate data driven approaches to perform the feature selection and extraction steps in …

Biophysical And Biochemical Screening Approaches For Antimicrobial Drug Discovery Targeting S. Aureus Clpp, Aman Preet Singh

Theses and Dissertations (ETD)

The discovery of antibacterial drugs has been among most significant achievements of mankind in saving millions of lives across the planet from infectious diseases. With rise in resistance to almost all existing chemotypes, the design of next generation novel antibiotics has become much more challenging and difficult. The early 21st century witnessed the advancement of multiple novel chemotypes during golden age of antibiotics however the pace of antibiotic drug discovery has slowed down tremendously, contributing to life threatening antimicrobial discovery void since 1980’s. Therefore the need to develop novel antibiotics with unique mechanism of action to leverage against multi drug …