João P.L. Velloso , Aaron S. Kovacs , Douglas E.V. Pires , David B. Ascher
{"title":"AI-driven GPCR analysis, engineering, and targeting","authors":"João P.L. Velloso , Aaron S. Kovacs , Douglas E.V. Pires , David B. Ascher","doi":"10.1016/j.coph.2023.102427","DOIUrl":null,"url":null,"abstract":"<div><p>This article investigates the role of recent advances in Artificial Intelligence (AI) to revolutionise the study of G protein-coupled receptors (GPCRs). AI has been applied to many areas of GPCR research, including the application of machine learning (ML) in GPCR classification, prediction of GPCR activation levels, modelling GPCR 3D structures and interactions, understanding G-protein selectivity, aiding elucidation of GPCRs structures, and drug design. Despite progress, challenges in predicting GPCR structures and addressing the complex nature of GPCRs remain, providing avenues for future research and development.</p></div>","PeriodicalId":50603,"journal":{"name":"Current Opinion in Pharmacology","volume":"74 ","pages":"Article 102427"},"PeriodicalIF":4.0000,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Opinion in Pharmacology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1471489223000826","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 0
Abstract
This article investigates the role of recent advances in Artificial Intelligence (AI) to revolutionise the study of G protein-coupled receptors (GPCRs). AI has been applied to many areas of GPCR research, including the application of machine learning (ML) in GPCR classification, prediction of GPCR activation levels, modelling GPCR 3D structures and interactions, understanding G-protein selectivity, aiding elucidation of GPCRs structures, and drug design. Despite progress, challenges in predicting GPCR structures and addressing the complex nature of GPCRs remain, providing avenues for future research and development.
期刊介绍：
Current Opinion in Pharmacology (COPHAR) publishes authoritative, comprehensive, and systematic reviews. COPHAR helps specialists keep up to date with a clear and readable synthesis on current advances in pharmacology and drug discovery. Expert authors annotate the most interesting papers from the expanding volume of information published today, saving valuable time and giving the reader insight on areas of importance.
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