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 ...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 revolutionized the field of GPCR ligand discovery and has provided valuable tools for accelerating the identification 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 summarized,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 formats 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 AI in GPCR research were deliberated.In conclusion,continued advancements in AI techniques coupled with interdisciplina ry collaborations will offer great potential for improving the efficiency of GPCR ligand discovery.展开更多
Pharmaceutical analysis is a discipline based on chemical, physical, biological, and information technologies. At present, biotechnological analysis is a short branch in pharmaceutical analysis;however, bioanalysis is...Pharmaceutical analysis is a discipline based on chemical, physical, biological, and information technologies. At present, biotechnological analysis is a short branch in pharmaceutical analysis;however, bioanalysis is the basis and an important part of medicine. Biotechnological approaches can provide information on biological activity and even clinical efficacy and safety, which are important characteristics of drug quality. Because of their advantages in reflecting the overall biological effects or functions of drugs and providing visual and intuitive results, some biotechnological analysis methods have been gradually applied to pharmaceutical analysis from raw material to manufacturing and final product analysis,including DNA super-barcoding, DNA-based rapid detection, multiplex ligation-dependent probe amplification, hyperspectral imaging combined with artificial intelligence, 3D biologically printed organoids,omics-based artificial intelligence, microfluidic chips, organ-on-a-chip, signal transduction pathwayrelated reporter gene assays, and the zebrafish thrombosis model. The applications of these emerging biotechniques in pharmaceutical analysis have been discussed in this review.展开更多
基金Natural Science Foundation of Sichuan(2023NSFSC0683)Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine(ZYYCXTD-D202209).
文摘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 revolutionized the field of GPCR ligand discovery and has provided valuable tools for accelerating the identification 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 summarized,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 formats 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 AI in GPCR research were deliberated.In conclusion,continued advancements in AI techniques coupled with interdisciplina ry collaborations will offer great potential for improving the efficiency of GPCR ligand discovery.
基金supported by the National Key R&D Program of China(No.2019YFC1711100,China)the National Natural Science Foundation of China(No.U1812403-1,China).
文摘Pharmaceutical analysis is a discipline based on chemical, physical, biological, and information technologies. At present, biotechnological analysis is a short branch in pharmaceutical analysis;however, bioanalysis is the basis and an important part of medicine. Biotechnological approaches can provide information on biological activity and even clinical efficacy and safety, which are important characteristics of drug quality. Because of their advantages in reflecting the overall biological effects or functions of drugs and providing visual and intuitive results, some biotechnological analysis methods have been gradually applied to pharmaceutical analysis from raw material to manufacturing and final product analysis,including DNA super-barcoding, DNA-based rapid detection, multiplex ligation-dependent probe amplification, hyperspectral imaging combined with artificial intelligence, 3D biologically printed organoids,omics-based artificial intelligence, microfluidic chips, organ-on-a-chip, signal transduction pathwayrelated reporter gene assays, and the zebrafish thrombosis model. The applications of these emerging biotechniques in pharmaceutical analysis have been discussed in this review.
