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Direct Selection of DNA-Encoded Libraries for Biased Agonists of GPCRs on Live Cells
[Image: see text] G protein-coupled receptors (GPCRs) are the largest superfamily of human membrane target proteins for approved drugs. GPCR ligands can have a complex array of pharmacological activities. Among these activities, biased agonists have potential to serve as both chemical probes to unde...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10131204/ https://www.ncbi.nlm.nih.gov/pubmed/37124302 http://dx.doi.org/10.1021/jacsau.2c00674 |
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author | Cai, Bo El Daibani, Amal Bai, Yuntian Che, Tao Krusemark, Casey J. |
author_facet | Cai, Bo El Daibani, Amal Bai, Yuntian Che, Tao Krusemark, Casey J. |
author_sort | Cai, Bo |
collection | PubMed |
description | [Image: see text] G protein-coupled receptors (GPCRs) are the largest superfamily of human membrane target proteins for approved drugs. GPCR ligands can have a complex array of pharmacological activities. Among these activities, biased agonists have potential to serve as both chemical probes to understand specific aspects of receptor signaling and therapeutic leads with more specific, desired activity. Challenges exist, however, in the development of new biased activators due, in part, to the low throughput of traditional screening approaches. DNA-encoded chemical libraries (DELs) dramatically improve the throughput of drug discovery by allowing a collective selection, rather than discrete screening, of large compound libraries. The use of DELs has been largely limited to affinity-based selections against purified protein targets, which identify binders only. Herein, we report a split protein complementation approach that allows direct identification of DNA-linked molecules that induce the dimerization of two proteins. We used this selection with a DEL against opioid receptor GPCRs on living cells for the identification of small molecules that possess the specific function of activation of either β-arrestin or G protein signaling pathways. This approach was applied to δ-, μ-, and κ-opioid receptors and enabled the discovery of compound [66,66], a selective, G-protein-biased agonist of the κ-opioid receptor (EC(50) = 100 nM, E(max) = 82%, G(i) bias factor = 6.6). This approach should be generally applicable for the direct selection of chemical inducers of dimerization from DELs and expand the utility of DELs to enrich molecules with a specific and desired biochemical function. |
format | Online Article Text |
id | pubmed-10131204 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-101312042023-04-27 Direct Selection of DNA-Encoded Libraries for Biased Agonists of GPCRs on Live Cells Cai, Bo El Daibani, Amal Bai, Yuntian Che, Tao Krusemark, Casey J. JACS Au [Image: see text] G protein-coupled receptors (GPCRs) are the largest superfamily of human membrane target proteins for approved drugs. GPCR ligands can have a complex array of pharmacological activities. Among these activities, biased agonists have potential to serve as both chemical probes to understand specific aspects of receptor signaling and therapeutic leads with more specific, desired activity. Challenges exist, however, in the development of new biased activators due, in part, to the low throughput of traditional screening approaches. DNA-encoded chemical libraries (DELs) dramatically improve the throughput of drug discovery by allowing a collective selection, rather than discrete screening, of large compound libraries. The use of DELs has been largely limited to affinity-based selections against purified protein targets, which identify binders only. Herein, we report a split protein complementation approach that allows direct identification of DNA-linked molecules that induce the dimerization of two proteins. We used this selection with a DEL against opioid receptor GPCRs on living cells for the identification of small molecules that possess the specific function of activation of either β-arrestin or G protein signaling pathways. This approach was applied to δ-, μ-, and κ-opioid receptors and enabled the discovery of compound [66,66], a selective, G-protein-biased agonist of the κ-opioid receptor (EC(50) = 100 nM, E(max) = 82%, G(i) bias factor = 6.6). This approach should be generally applicable for the direct selection of chemical inducers of dimerization from DELs and expand the utility of DELs to enrich molecules with a specific and desired biochemical function. American Chemical Society 2023-03-22 /pmc/articles/PMC10131204/ /pubmed/37124302 http://dx.doi.org/10.1021/jacsau.2c00674 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Cai, Bo El Daibani, Amal Bai, Yuntian Che, Tao Krusemark, Casey J. Direct Selection of DNA-Encoded Libraries for Biased Agonists of GPCRs on Live Cells |
title | Direct Selection
of DNA-Encoded Libraries for Biased
Agonists of GPCRs on Live Cells |
title_full | Direct Selection
of DNA-Encoded Libraries for Biased
Agonists of GPCRs on Live Cells |
title_fullStr | Direct Selection
of DNA-Encoded Libraries for Biased
Agonists of GPCRs on Live Cells |
title_full_unstemmed | Direct Selection
of DNA-Encoded Libraries for Biased
Agonists of GPCRs on Live Cells |
title_short | Direct Selection
of DNA-Encoded Libraries for Biased
Agonists of GPCRs on Live Cells |
title_sort | direct selection
of dna-encoded libraries for biased
agonists of gpcrs on live cells |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10131204/ https://www.ncbi.nlm.nih.gov/pubmed/37124302 http://dx.doi.org/10.1021/jacsau.2c00674 |
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