Date of Award
1-1-2024
Document Type
Dissertation
Degree Name
Ph.D. in Pharmaceutical Sciences
First Advisor
Robert J. Doerksen
Second Advisor
Robert J. Doerksen
Third Advisor
David A. Colby
Relational Format
dissertation/thesis
Abstract
Infectious diseases are the leading cause of disability-adjusted life years worldwide. Glycans initiate host–pathogen interactions in two particular infectious diseases, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and urinary tract infections (UTIs). In this work, recent advances of computational tools in drug design are utilized to target these glycanspecific host–pathogen interactions for the potential prevention of SARS-CoV-2 or UTIs.
SARS-CoV-2 viral entry into the host cell is mediated by the viral S-protein. Carbohydrate molecules bind to the receptor-binding domain (RBD) of the S-protein which interacts with angiotensin-converting enzyme 2 and leads to host cell invasion. Here we report computational studies to investigate the binding of marine glycans to the wild-type, Alpha and Delta variants of RBDs. In research by our collaborators, the glycans exhibited anti-SARS-CoV-2 activities, mediated through competitive inhibition. We investigated the static and dynamic behavior of the protein–glycan interactions using molecular docking, molecular dynamics simulations and binding free energy calculations. Five potential glycan binding sites on the RBD were studied. Statistical analyses of the stability of RBD–glycan complexes differentiated pseudo vs. real binding sites. Our results provide significant insights into the importance of extensive molecular dynamics simulations to move beyond the limitations of molecular docking alone.
Approximately 50% of women are affected by UTIs during their lifetimes. The most common agent causing UTIs is uropathogenic Escherichia coli (UPEC). UPEC uses the protein FmlH that specifically bind to galactosaminosides attached to glycoproteins in host cells, aiding colonization of host tissue surfaces. The traditional treatment using antibiotics has led to the rise of UPEC antibiotic-resistant strains. An alternative therapeutic approach includes an anti-adhesion strategy using competitive FmlH-binding inhibitors to discourage initial bacterial attachment. Here we have used modeling techniques to identify novel glycomimetics that are predicted to bind strongly to and inhibit FmlH. We designed a novel hybrid fragment-based virtual screening workflow. We generated a database containing ~190K fragments which could be utilized to identify new glycomimetics that can be subjected to further biological activity studies. Following this, we have used scaffold hopping and machine learning models to obtain novel FmlH-binding glycomimetics with improved pharmacokinetic properties.
Recommended Citation
Samanta, Priyanka, "Molecular Modeling of Inhibitors of Severe Acute Respiratory Syndrome Coronavirus 2 and Urinary Tract Infections" (2024). Electronic Theses and Dissertations. 2870.
https://egrove.olemiss.edu/etd/2870