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Current Medicinal Chemistry

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ISSN (Print): 0929-8673
ISSN (Online): 1875-533X

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Review Article

The Structure-property Relationships of GPCR-targeted Drugs Approved between 2011 and 2021

Author(s): Kihang Choi*

Volume 30, Issue 31, 2023

Published on: 19 December, 2022

Page: [3527 - 3549] Pages: 23

DOI: 10.2174/1573399819666221102113217

Price: $65

Open Access Journals Promotions 2
Abstract

Background: G-protein-coupled receptors (GPCRs) are the largest family of membrane receptors and the most intensively studied drug targets. Given the physiological importance of signal transduction by GPCRs and the recent progress in the structure determination of membrane proteins, the development of GPCR antagonists and agonists is expected to continue to be a major area of medicinal chemistry research.

Methods: The structure-property relationship illustrates how the modification of the chemical structure influences the absorption, distribution, metabolism, excretion, and other related properties of drug compounds. Understanding the structure-property relationships of clinically approved GPCR-targeted drugs and their analogues could provide useful information on the lead-to-candidate optimization strategies.

Results: Among more than 50 GPCR antagonists and agonists approved in the last decade, the structure-property relationships of 17 drugs are compiled from medicinal chemistry literature, in which detailed pharmacokinetic and toxicological properties are disclosed not only for the final drug candidate but also for key analogues generated during the lead optimization campaign.

Conclusion: The structure-property relationships hereby summarized demonstrate how in vitro and in vivo properties of the membrane protein-targeted ligands could be effectively optimized, in many cases, without requiring a significant change in the molecular size. This information is expected to provide valuable insights to expedite new GPCR-targeted drug development.

Keywords: Structure-property relationship, GPCR antagonist, GPCR agonist, lead optimization, candidate selection, drug discovery.

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