多酚
药物发现
抗癌药
药物开发
自然(考古学)
药品
生化工程
药理学
计算生物学
计算机科学
医学
生物信息学
生物
工程类
生物化学
抗氧化剂
古生物学
作者
Ying Zheng,Yifei Ma,Qunli Xiong,Kai Zhu,Ningna Weng,Qing Zhu
标识
DOI:10.1016/j.phrs.2024.107381
摘要
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.
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