首页|The Application of Artificial Intelligence Accelerates G Protein-Coupled Receptor Ligand Discovery

The Application of Artificial Intelligence Accelerates G Protein-Coupled Receptor Ligand Discovery

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G protein-coupled receptors(GPCRs)are crucial players in various physiological processes,making them attractive candidates for drug discovery.However,traditional approaches to GPCR ligand discovery are time-consuming and resource-intensive.The emergence of artificial intelligence(AI)methods has revo-lutionized the field of GPCR ligand discovery and has provided valuable tools for accelerating the identi-fication and optimization of GPCR ligands.In this study,we provide guidelines for effectively utilizing AI methods for GPCR ligand discovery,including data collation and representation,model selection,and specific applications.First,the online resources that are instrumental in GPCR ligand discovery were sum-marized,including databases and repositories that contain valuable GPCR-related information and ligand data.Next,GPCR and ligand representation schemes that can convert data into computer-readable for-mats were introduced.Subsequently,the key applications of AI methods in the different stages of GPCR drug discovery were discussed,ranging from GPCR function prediction to ligand design and agonist identification.Furthermore,an AI-driven multi-omics integration strategy for GPCR ligand discovery that combines information from various omics disciplines was proposed.Finally,the challenges and future directions of the application of Al in GPCR research were deliberated.In conclusion,continued advance-ments in AI techniques coupled with interdisciplinary collaborations will offer great potential for improv-ing the efficiency of GPCR ligand discovery.

G protein-coupled receptorLigandArtificial intelligenceMulti-omicsDrug discovery

Wei Chen、Chi Song、Liang Leng、Sanyin Zhang、Shilin Chen

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State Key Laboratory of Southwestern Chinese Medicine Resources,Innovative Institute of Chinese Medicine and Pharmacy,Chengdu University of Traditional Chinese Medicine,Chengdu 611137,China

Institute of Herbgenomics,Chengdu University of Traditional Chinese Medicine,Chengdu 611137,China

Natural Science Foundation of SichuanInnovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine

2023NSFSC0683ZYYCXTD-D-202209

2024

10.1016/j.eng.2023.09.011

工程(英文)

工程(英文)

CSTPCDEI
ISSN：2095-8099
年,卷(期)：2024.32(1)
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