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人工智能在 G 蛋白偶联受体药物发现中的应用。

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

机构信息

Drug Discovery Biology Theme, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia.

Department of Information Technology, Faculty of Engineering and Technology, Vietnam National University, Cau Giay, Hanoi, Vietnam.

出版信息

Br J Pharmacol. 2024 Jul;181(14):2371-2384. doi: 10.1111/bph.16140. Epub 2023 May 26.

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.

摘要

人工智能在 G 蛋白偶联受体 (GPCR) 药物发现中的应用是一个快速发展的领域。人工智能可以在药物发现过程的多个阶段使用,从帮助我们理解 GPCR 的基本作用,到发现新的配体-GPCR 相互作用或预测临床反应。在这里,我们概述了人工智能背后的概念,包括机器学习和深度学习的子领域。我们总结了人工智能在 GPCR 药物发现不同阶段的应用。最后,我们反思了人工智能的优势和局限性,并分享了我们对进一步发展应用以辅助 GPCR 药物发现的激动人心的潜力的看法。除了使药物发现过程“更快、更智能、更便宜”之外,我们预计人工智能的应用将为 GPCR 药物发现创造令人兴奋的新机会。

相关文章

本文是治疗靶向 G 蛋白偶联受体:2021 年澳大利亚临床和实验药理学和毒理学学会虚拟年会热点主题特刊的一部分。要查看本节中的其他文章,请访问 http://onlinelibrary.wiley.com/doi/10.1111/bph.v181.14/issuetoc.

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