Year of Award

2022

Document Type

Dissertation

Degree Type

Doctor of Philosophy (PhD)

Degree Name

Biochemistry & Biophysics

Department or School/College

Department of Biomedical and Pharmaceutical Sciences

Committee Chair

Travis S. Hughes

Commitee Members

J. Stephen Lodmell, Bruce Bowler, Stephen Sprang, Jesse Hay

Keywords

Biased Agonism, fluorescence anisotropy, functional selectivity, nuclear receptor, PPARgamma, selective modulator

Abstract

Nuclear receptors are a class of ligand-activated transcription factors that affect gene expression. Pharmaceutical drugs that target nuclear receptors make up (13%) of all therapeutics prescribed in the United States. Unlike signaling pathways, nuclear receptors have a wide variety of binding partners that can bind upon activation of a nuclear receptor to upregulate gene transcription. These binding partner proteins, called “coregulators”, are diverse in function. However, the determinants of their binding to nuclear receptors, and how binding to certain coregulators over others occurs, is not known.

In this work, we examine how ligands create a preference for nuclear receptors to bind some coregulators over others, a concept previously established in G-protein coupled receptors (GPCRs) known as biased agonism. We define a method to measure bias of ligands, and for the first time to our knowledge, we define structural classes of coregulators that biased ligands can select for. Due to the largely shared coregulator binding surface of nuclear receptors, we expect these findings to be impactful for the field of nuclear receptor research and pharmaceutical drug design. Preclinical works have demonstrated that activation of specific pathways with biased ligands can expand their therapeutic utility and limit side effects. By defining an assay to measure bias and defining clear structural classes of coregulators that ligands can bias binding towards, we define a new method of nuclear receptor ligand design.

Available for download on Monday, January 20, 2025

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© Copyright 2022 Michelle Deanna Nemetchek