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<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>

<p>Drug discovery and development has experienced a tremendous growth in the recent</p> <p>years, and methods to accelerate the process are necessary as the demand for effective drugs</p> <p>to treat a wide range of diseases continue to increase. Nevertheless, the majority of conventional</p> <p>techniques are labor-intensive or have relatively low yields. As a result, academia</p> <p>and the pharmaceutical industry are continuously seeking for rapid and efficient methods to</p> <p>accelerate the drug discovery pipeline. Therefore, in order to expedite the drug discovery</p> <p>process, recent developments in physical and artificial intelligence models have been utilized</p> <p>extensively. However, the overarching problem is how to use these cutting-edge advancements</p> <p>in artificial intelligence to enhance drug discovery? Therefore, this dissertation work</p> <p>focused on developing and applying artificial intelligence and physical models to accelerate</p> <p>the drug discovery pipeline at different stages. As the first study reported in the dissertation,</p> <p>the potential to apply graph neural network-based machine learning architectures</p> <p>with the assistance of molecular modeling features to identify plausible drug leads out of</p> <p>structurally similar chemical databases is assessed. Then, the capability of applying molecular</p> <p>modeling methods including molecular docking and molecular dynamics simulations to</p> <p>identify prospective targets and biological pathways for small molecular drugs is discussed</p> <p>and evaluated in the following chapter. Further, the capability of applying state-of-the-art</p> <p>deep learning architectures such as multi-layer perceptron and recurrent neural networks</p> <p>to optimize the formulation development stage has been assessed. Moreover, this dissertation</p> <p>has contributed to assist functionality identification of unknown compounds using</p> <p>simple machine learning based computational frameworks. The developed omics data analysis</p> <p>pipeline is then discussed in order to comprehend the effects of a particular treatment</p> <p>on the proteome and lipidome levels of cells. In conclusion, the potential for developing and</p> <p>utilizing various artificial intelligence-based approaches to accelerate the drug discovery and</p> <p>development process is explored in this research. Thus, these collaborative studies intend</p> <p>to contribute to ongoing acceleration efforts and advancements in the drug discovery and</p> <p>development field.</p>

<p dir="ltr">The BRG1/BRM-associated factor (BAF) complexes, also called SWI/SNF, are multi-subunit chromatin remodelers that regulate chromatin compaction in an ATP-dependent manner. In the past decade, BAF complexes have been under the spotlight in cancer research, especially after proteomic analyses revealed the genes encoding the subunits are amongst the most frequently mutated genes in cancer. The present dissertation focuses on prostate cancer (PCa), a disease in which the role of the BAF subunits is increasingly being explored but is yet to be defined as a potential therapeutic target. According to the GLOBOCAN report, PCa is the second most frequent cancer in males worldwide. Since most of the variants of PCa rely on the androgen receptor (AR) axis, surgical or chemical castration and androgen deprivation therapy (ADT) are the main treatment strategies for PCa patients. Even though these therapeutic approaches prolong survival, reduce tumor burden, and relieve symptoms, PCa patients eventually relapse and develop castration resistant PCa (CRPC). At present, the mechanisms underlying ADT resistance are not fully understood, current efforts focus on finding new targets for PCa treatment.</p><p dir="ltr">In the projects included in this dissertation we explored the function of the PBAF complex, a BAF subtype, in a variety of models of PCa and its potential as a therapeutic target by inhibiting or depleting its different subunits. To do so we (i) developed the first inhibitors for BRD7 (a subunit unique to PBAF) and (ii) established cell-based assays in multiple PCa cell lines to study BRD7 and other PBAF unique subunits.</p><p dir="ltr">Bromodomain-containing proteins are readers of acetylated lysine and play important roles in cancer. Bromodomain-containing protein 7 (BRD7) has been implicated in multiple malignancies; however, there are no selective chemical probes to study its function in disease. Using crystal structures of BRD7 and BRD9 bromodomains (BDs) bound to BRD9-selective ligands, we identified a binding pocket exclusive to BRD7. We synthesized a series of ligands designed to occupy this binding region and identified two inhibitors with increased selectivity towards BRD7, 1-78 and 2-77, which bind with submicromolar affinity to the BRD7 BD. Our binding mode analyses indicate that these ligands occupy a uniquely accessible binding cleft in BRD7 and maintain key interactions with the asparagine and tyrosine residues critical for acetylated lysine binding. Finally, we validated the utility and selectivity of the compounds in cell-based models of prostate cancer.</p><p dir="ltr">There are three BAF complexes that have been biochemically characterized up to date: canonical BAF (cBAF), polybromo-associated BAF (PBAF) and GLTSCR1/like-containing BAF (GBAF or ncBAF). All BAF complexes are characterized by containing an ATPase and accessory subunits that may be shared between them or unique to each subtype. PBAF, the BAF subtype of interest of this dissertation, contains four unique subunits: BRD7, PBRM1, ARID2 and BAF45A. We showed that knocking down BRD7 and ARID2 leads to reduction of cell viability in PCa cells with ligand-dependent and independent AR signaling, while knocking down PBRM1 leads to reduction in viability of cells with only ligand-dependent AR signaling. We also performed a chromatin immunoprecipitation assay with BAF45A and observed that it does not colocalize with AR binding sites, indicating that the mechanism by which PBAF regulates AR signaling is indirect. This observation was further supported by the fact that knocking down BRD7 prevents expression of genes related to adaptive processes, but not AR target genes, in response to androgen treatment. Further mechanistic studies will aid in understanding the function of PBAF in PCa. However, overall, our results indicate that PBAF is a promising therapeutic target in PCa models expressing AR, including CRPC systems.</p>

<p>This dissertation describes the effects of a <i>de novo</i> mutation of CaMKII found in children with learning disabilities and describes its effect on catalytic activity. We develop a malachite green assay for the measurement of CaMKII activation and use it for high-throughput chemical screening to identify CaMKII inhibitors and enhancers. We also propose a new mechanism of regulation of CaMKII activity by ADP.</p><p><br></p>