Recent discoveries in GPCR signaling have elucidated multiple critical roles of beta-arrestins which are scaffolding proteins that regulate GPCR internalization and signaling. Beta-arrestins are promising to clinical targets, because mice with a knockout of a single beta-arrestin have no overt phenotype, while dual knockout of beta-arrestin1 and beta-arrestin2 is lethal. Also, bladder cancer cells express elevated levels of beta-arrestin2 and one of its activators, the thromboxane-beta GPCR. This increase correlates with a poor clinical prognosis and suggests beta-arrestin2 as a bladder cancer target. Although GPCRs are a major clinical target, to date there are no small molecule regulators for beta-arrestins. Using high performance docking on the NICS Kraken supercomputer, we have conducted virtual screening of a 1.4 million compound library and identified ~250 potential beta-arrestin2 inhibitors. We then created and validated a high throughput and high-content screen targeting GPCR/ B-arrestin2 interactions and tested 61 predicted inhibitory compounds, 15 of which decreased receptor internalization by >40%, validating our discovery strategy. We will complete the screening of all the predicted inhibitors and carry out lead optimization to increase their potency and selectivity for beta-arrestin2. The resulting first selective inhibitors of betaarrestin2 will be used to determine their effect and selectivity on downstream GPCR signaling events in model cell systems. We will also test our beta-arrestin2 inhibitor for anticancer activity using cell based and animal models of bladder cancer. The success of this study will warrant the development of beta-arrestin2 inhibitors as therapeutic agents for bladder cancer and other diseases associated with aberrant betaarrestin- mediated signal transduction.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Exploratory Grants (P20)
Project #
5P20GM109091-04
Application #
9274310
Study Section
Special Emphasis Panel (ZGM1)
Project Start
Project End
Budget Start
2017-05-01
Budget End
2018-04-30
Support Year
4
Fiscal Year
2017
Total Cost
Indirect Cost
Name
University of South Carolina at Columbia
Department
Type
DUNS #
041387846
City
Columbia
State
SC
Country
United States
Zip Code
29208
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