Suppr超能文献

基于机器学习方法的抗氧化剂鉴定研究进展。

Recent Advances on Antioxidant Identification Based on Machine Learning Methods.

机构信息

School of Basic Medical Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu 611730, China.

School of Sciences, North China University of Science and Technology, Tangshan 063000, China.

出版信息

Curr Drug Metab. 2020;21(10):804-809. doi: 10.2174/1389200221666200719001449.

Abstract

Antioxidants are molecules that can prevent damages to cells caused by free radicals. Recent studies also demonstrated that antioxidants play roles in preventing diseases. However, the number of known molecules with antioxidant activity is very small. Therefore, it is necessary to identify antioxidants from various resources. In the past several years, a series of computational methods have been proposed to identify antioxidants. In this review, we briefly summarized recent advances in computationally identifying antioxidants. The challenges and future perspectives for identifying antioxidants were also discussed. We hope this review will provide insights into researches on antioxidant identification.

摘要

抗氧化剂是一种能够预防自由基对细胞造成损伤的分子。最近的研究还表明,抗氧化剂在预防疾病方面也发挥着作用。然而,具有抗氧化活性的已知分子的数量非常少。因此,有必要从各种资源中识别抗氧化剂。在过去的几年中,已经提出了一系列计算方法来识别抗氧化剂。在这篇综述中,我们简要总结了最近在计算识别抗氧化剂方面的进展。还讨论了识别抗氧化剂所面临的挑战和未来展望。我们希望这篇综述能为抗氧化剂鉴定的研究提供一些思路。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验