变构作用揭秘：利用人工智能和机器学习进行药物研发
Allostery Illuminated: Harnessing AI and Machine Learning for Drug Discovery.
作者信息
Blanco Maria-Jesus, Buskes Melissa J, Govindaraj Rajiv G, Ipsaro Jonathan J, Prescott-Roy Joann E, Padyana Anil K
机构信息
Atavistik Bio, 101 Cambridgepark Drive, Cambridge, Massachusetts 02140, United States.
出版信息
ACS Med Chem Lett. 2024 Aug 30;15(9):1449-1455. doi: 10.1021/acsmedchemlett.4c00260. eCollection 2024 Sep 12.
Abstract
In the past several years there has been rapid adoption of artificial intelligence (AI) and machine learning (ML) tools for drug discovery. In this Microperspective, we comment on recent AI/ML applications to the discovery of allosteric modulators, focusing on breakthroughs with AlphaFold, structure-based drug discovery (SBDD), and medicinal chemistry applications. We discuss how these technologies are facilitating drug discovery and the remaining challenges to identify allosteric binding sites and ligands.
摘要
在过去几年中，人工智能（AI）和机器学习（ML）工具已迅速应用于药物发现领域。在这篇微观视角文章中，我们对人工智能/机器学习在变构调节剂发现中的最新应用进行评论，重点关注AlphaFold、基于结构的药物发现（SBDD）和药物化学应用方面的突破。我们讨论了这些技术如何推动药物发现，以及在识别变构结合位点和配体方面仍然存在的挑战。
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