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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Cellular and Computational Evaluation of the Structural Pharmacology of Delta Opioid Receptors

Yazan J Meqbil (14210360) 05 December 2022 (has links)
<p>G-protein coupled receptors (GPCRs) are membrane proteins that constitute ~30% of the FDA-approved drug targets. Opioid receptors are a subtype of GPCRs with four different receptor types: delta, kappa, mu, and nociception opioid receptors. Opioids such as morphine have been used for thousands of years and are deemed the most effective method for treating pain. However, opioids can have detrimental effects if used illicitly or over an extended period of time. Intriguingly, most of the clinically used opioids act on the mu opioid receptor (µOR). Hence, efforts in recent decades have focused on other opioid receptors to treat pain and other disorders. The delta opioid receptor (δOR) is one of four opioid receptors expressed in the central and peripheral nervous system. The δOR has attracted much attention as a potential target for a multitude of diseases and disorders including substance and alcohol use disorders, ischemia, migraine, and neurodegenerative diseases. However, to date, no δOR agonists, or drugs that act directly at the δOR, have been successful as clinical candidates. Nonetheless, the therapeutic potential of the δOR necessitates the targeting its pharmacologically. In this dissertation, I highlight peptide-based modulation as well as the identification of novel agonists at the δOR. I report research findings in the context of biased agonism at δOR, which is a hypothesized cellular signaling mechanism with potential therapeutic benefits. The focus on this work is the molecular determinants of biased agonism, which were investigated using a combination of cellular and computational approaches.  </p>

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