The application of artificial intelligence to accelerate G protein-coupled receptor drug discovery

Anh T.N. Nguyen, Diep T.N. Nguyen, Huan Yee Koh, Jason Toskov, William MacLean, Andrew Xu, Daokun Zhang, Geoffrey I. Webb, Lauren T. May, Michelle L. Halls

Research output: Journal PublicationReview articlepeer-review

11 Citations (Scopus)

Abstract

The application of artificial intelligence (AI) approaches to drug discovery for G protein-coupled receptors (GPCRs) is a rapidly expanding area. Artificial intelligence can be used at multiple stages during the drug discovery process, from aiding our understanding of the fundamental actions of GPCRs to the discovery of new ligand-GPCR interactions or the prediction of clinical responses. Here, we provide an overview of the concepts behind artificial intelligence, including the subfields of machine learning and deep learning. We summarise the published applications of artificial intelligence to different stages of the GPCR drug discovery process. Finally, we reflect on the benefits and limitations of artificial intelligence and share our vision for the exciting potential for further development of applications to aid GPCR drug discovery. In addition to making the drug discovery process “faster, smarter and cheaper,” we anticipate that the application of artificial intelligence will create exciting new opportunities for GPCR drug discovery. LINKED ARTICLES: This article is part of a themed issue Therapeutic Targeting of G Protein-Coupled Receptors: hot topics from the Australasian Society of Clinical and Experimental Pharmacologists and Toxicologists 2021 Virtual Annual Scientific Meeting. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v181.14/issuetoc.

Original languageEnglish
Pages (from-to)2371-2384
Number of pages14
JournalBritish Journal of Pharmacology
Volume181
Issue number14
DOIs
Publication statusPublished - Jul 2024
Externally publishedYes

Keywords

  • G protein-coupled receptor
  • artificial intelligence
  • deep learning
  • drug discovery
  • machine learning

ASJC Scopus subject areas

  • Pharmacology

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