人类饮食中富含天然多酚，来源广泛。大量的临床前研究已证明它们对各种恶性肿瘤具有显着的抗癌特性，使其成为药物开发的宝贵资源。然而，利用天然多酚开发抗癌疗法的传统实验方法既耗时又费力。最近，人工智能在药物发现方面取得了令人鼓舞的进展。将人工智能技术融入天然多酚的开发过程中可以大大缩短开发时间并提高效率。在这项研究中，我们回顾了天然多酚在抗癌治疗中的关键作用，并探索了人工智能技术辅助药物开发的潜力。具体来说，我们讨论了人工智能在药物结构预测、虚拟药物筛选、生物活性预测以及药物与靶蛋白相互作用等关键阶段的应用，凸显了彻底改变基于天然多酚的抗癌疗法发展的潜力。版权所有© 2024 作者。由爱思唯尔有限公司出版。保留所有权利。

Natural polyphenols, abundant in the human diet, are derived from a wide variety of sources. Numerous preclinical studies have demonstrated their significant anticancer properties against various malignancies, making them valuable resources for drug development. However, traditional experimental methods for developing anticancer therapies from natural polyphenols are time-consuming and labor-intensive. Recently, artificial intelligence has shown promising advancements in drug discovery. Integrating AI technologies into the development process for natural polyphenols can substantially reduce development time and enhance efficiency. In this study, we review the crucial roles of natural polyphenols in anticancer treatment and explore the potential of AI technologies to aid in drug development. Specifically, we discuss the application of AI in key stages such as drug structure prediction, virtual drug screening, prediction of biological activity, and drug-target protein interaction, highlighting the potential to revolutionize the development of natural polyphenol-based anticancer therapies.Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.