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运用综合虚拟筛选技术鉴定食品来源的亲电查尔酮作为Nrf2激活剂

Identification of Food-Derived Electrophilic Chalcones as Nrf2 Activators Using Comprehensive Virtual Screening Techniques.

作者信息

Bai Bingyu, Tu Piaohan, Weng Jiayi, Zhang Yan, Lin Quan, Muskat Mitchell N, Wang Jie, Tang Xue, Cheng Xiangrong

机构信息

School of Food Science and Technology, Jiangnan University, Wuxi 214122, China.

State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China.

出版信息

Antioxidants (Basel). 2025 Apr 30;14(5):546. doi: 10.3390/antiox14050546.

DOI:10.3390/antiox14050546
PMID:40427428
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12108417/
Abstract

Electrophilic compounds are bioactive components commonly found in foods that are capable of covalently modifying nucleophilic sites on biologically functional macromolecules. These compounds may elicit positive bioactivity or negative biotoxicity, posing significant challenges in terms of time and resource expenditure in the de novo characterization of their biological activity. In this study, we developed a database of 332 food-derived electrophilic compounds and used a semi-supervised k-nearest neighbors (KNN) machine learning model to predict their bioactivity. Molecular docking analysis identified the three chalcone compounds with the highest potential positive activity-4-hydroxyderricin (4HD), isoliquiritigenin (ISO), and butein. Furthermore, in cell experiments, treatment with 4HD, ISO, and butein significantly reduced reactive oxygen species (ROS) levels. An RT-qPCR analysis demonstrated that these chalcones significantly upregulated the mRNA expression of and its downstream antioxidant genes, including , , , , and . ISO's cytoprotective and antioxidant effects were abolished following these findings, which highlight that 4HD, ISO, and butein are effective Nrf2 activators and suggest that comprehensive virtual technology is a promising strategy for identifying functional bioactive compounds.

摘要

亲电化合物是常见于食物中的生物活性成分,能够共价修饰生物功能大分子上的亲核位点。这些化合物可能引发积极的生物活性或负面的生物毒性,在从头表征其生物活性方面,在时间和资源消耗上带来了重大挑战。在本研究中,我们开发了一个包含332种食物来源亲电化合物的数据库,并使用半监督k近邻(KNN)机器学习模型来预测它们的生物活性。分子对接分析确定了三种具有最高潜在正活性的查尔酮化合物——4-羟基德里辛(4HD)、异甘草素(ISO)和紫铆因。此外,在细胞实验中,用4HD、ISO和紫铆因处理显著降低了活性氧(ROS)水平。逆转录定量聚合酶链反应(RT-qPCR)分析表明,这些查尔酮显著上调了 及其下游抗氧化基因的mRNA表达,包括 、 、 、 和 。这些发现后,ISO的细胞保护和抗氧化作用被消除,这突出表明4HD、ISO和紫铆因是有效的核因子E2相关因子2(Nrf2)激活剂,并表明综合虚拟技术是识别功能性生物活性化合物的一种有前途的策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1599/12108417/93487ed0e601/antioxidants-14-00546-g008.jpg
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