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Selective Signal Capture from Multidimensional GPCR Outputs with Biased Agonists: Progress Towards Novel Drug Development

Kim, Donghwa and Tokmakova, Alina and Woo, Jung-A A. and An, Steven S. and Goddard, William A., III and Liggett, Stephen B. (2022) Selective Signal Capture from Multidimensional GPCR Outputs with Biased Agonists: Progress Towards Novel Drug Development. Molecular Diagnosis & Therapy, 26 (4). pp. 383-396. ISSN 1177-1062. PMCID PMC9276727. doi:10.1007/s40291-022-00592-4. https://resolver.caltech.edu/CaltechAUTHORS:20220523-164626000

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Abstract

G protein coupled receptors (GPCRs) are a superfamily of transmembrane-spanning receptors that are activated by multiple endogenous ligands and are the most common target for agonist or antagonist therapeutics across a broad spectrum of diseases. Initial characterization within the superfamily suggested that a receptor activated a single intracellular pathway, depending on the G protein to which it coupled. However, it has become apparent that a given receptor can activate multiple different pathways, some being therapeutically desirable, while others are neutral or promote deleterious signaling. The activation of pathways that limit effectiveness of a primary pathway or promote unwanted signals has led to abandonment of some GPCRs as drug targets. However, it is now recognized that the conformation of the receptor in its ligand-bound state can be altered by the structure of the agonist or antagonist to achieve pathway selectivity, a property termed biased signaling. Biased ligands could dramatically expand the number of novel drugs acting at GPCRs for new indications. However, the field struggles with the complexity and uncertainty of these structure-functions relationships. In this review we define the theoretical underpinnings of the biased effect, discuss the methods for measuring bias, and the pitfalls that can lead to incorrect assignments of bias. Using the recent elucidation of a β2-adrenergic receptor agonist that is biased in favor of Gs coupling over β-arrestin binding, we provide an example of how large libraries of compounds that are impartial to preconceived notions of agonist binding can be utilized to discover pathway-specific agonists. In this case, an agonist that lacks tachyphylaxis for the treatment of obstructive lung diseases was uncovered, with a structure that was distinctly different from other agonists. We show how biased characteristics were ascertained analytically, and how molecular modeling and simulations provide a structural basis for a restricted signaling repertoire.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1007/s40291-022-00592-4DOIArticle
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9276727/PubMed CentralArticle
ORCID:
AuthorORCID
Kim, Donghwa0000-0002-8994-8513
Tokmakova, Alina0000-0001-5280-7621
Woo, Jung-A A.0000-0002-9194-1361
An, Steven S.0000-0003-4723-1888
Goddard, William A., III0000-0003-0097-5716
Liggett, Stephen B.0000-0002-0128-3669
Additional Information:© The Author(s) 2022. This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/. Accepted 13 April 2022. Published 20 May 2022. We thank Lauren K. Lujan and Hannah R. Strzelinski and our other collaborators for data generation for the original papers and Himeshkumar N. Patel for assistance in manuscript preparation. Funding: National institutes of Health Grants, National Heart, Lung, and Blood Institute, HL45967, HL114471 and HL15532. Open Access and related publication costs were provided by University of South Florida internal funds. The authors declare no conflicts of interest. Availability of data and material: Not applicable. Ethics approval: Not applicable. Consent: Not applicable. Author contributions. DK, AT, JAW, SSA, WAG, and SBL conceived of the contents and wrote this review. Data availability statement: Not applicable
Funders:
Funding AgencyGrant Number
NIHHL45967
NIHHL114471
NIHHL15532
University of South FloridaUNSPECIFIED
Other Numbering System:
Other Numbering System NameOther Numbering System ID
WAG1522
Issue or Number:4
PubMed Central ID:PMC9276727
DOI:10.1007/s40291-022-00592-4
Record Number:CaltechAUTHORS:20220523-164626000
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20220523-164626000
Official Citation:Kim, D., Tokmakova, A., Woo, JA.A. et al. Selective Signal Capture from Multidimensional GPCR Outputs with Biased Agonists: Progress Towards Novel Drug Development. Mol Diagn Ther 26, 383–396 (2022). https://doi.org/10.1007/s40291-022-00592-4
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:114876
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:23 May 2022 22:24
Last Modified:14 Aug 2022 23:57

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