Date Approved

6-18-2019

Embargo Period

8-2-2019

Document Type

Thesis

Degree Name

M.S. Bioinformatics

Department

Molecular and Cellular Biosciences

College

College of Science & Mathematics

First Advisor

Wu, Chun

Second Advisor

Carone, Benjamin

Third Advisor

Keck, Thomas

Subject(s)

Computational biochemistry; Drug development

Disciplines

Bioinformatics | Pharmacy and Pharmaceutical Sciences

Abstract

The drug discovery process is an extremely long and expensive process that modern computational methods help to alleviate. Through the use of computational methods, we provide information and insight into the activation methods of class B GPCRs so that future drugs can be developed to have less side effects. The first study focuses on the corticotropin releasing factor receptor, which is a good drug target for anxiety and depression. A mechanism of activation was theorized which focuses less on molecular switches (as has been the focus of several papers) and more on large scale conformation at the intracellular region of the receptor and the C-terminal helix. We also developed a homology model for the complete receptor, which previously did not exist. The second study focused on the glucagon-like-peptide receptor which is a good drug target for treating type 2 diabetes. Here we explored the difference between full agonist activation and biased agonist activation. A distinctive conformational change of the C-terminal helix in the biased system was linked to allowing G protein docking, while blocking arrestin proteins from docking. Our findings elucidate details on GPCR activation which can be used to develop more efficient drugs on these receptors and provides insight into developing more specific drugs on other class B GPCRs.

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