文献类型：期刊文献

英文题名：Investigation of Anti-Alzheimer?s Mechanisms of Sarsasapogenin Derivatives by Network-Based Combining Structure-Based Methods

作者：Zhou, Moran[1];Sun, Jiamin[1];Yu, Zhuohang[1];Wu, Zengrui[1];Li, Weihua[1];Liu, Guixia[1];Ma, Lei[1];Wang, Rui[1];Tang, Yun[1]

机构：[1]East China Univ Sci & Technol, Shanghai Frontiers Sci Ctr Optogenet Tech Cell Met, Sch Pharm, Shanghai 200237, Peoples R China

年份：2023

卷号：63

期号：9

起止页码：2881

外文期刊名：JOURNAL OF CHEMICAL INFORMATION AND MODELING

收录：;EI(收录号：20231914060865);WOS:【SCI-EXPANDED(收录号:WOS:000981977100001)】；

基金：? ACKNOWLEDGMENTS This work was supported by the National Natural Science Foundation of China (Grants 82173746 and 82104066) , Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism (Shanghai Municipal Education Commis- sion, grant 2021 Sci & Tech 03-28) , and the 111 Project (Grant BP0719034) .

语种：英文

外文关键词：Association reactions - Atomic absorption spectrometry - Forecasting - Tensors

摘要：Alzheimer's disease (AD), a neurodegenerative disease with no cure, affects millions of people worldwide and has become one of the biggest healthcare challenges. Some investigated compounds play anti-AD roles at the cellular or the animal level, but their molecular mechanisms remain unclear. In this study, we designed a strategy combining network-based and structure-based methods together to identify targets for anti-AD sarsasapogenin derivatives (AAs). First, we collected drug-target interactions (DTIs) data from public databases, constructed a global DTI network, and generated drug-substructure associations. After network construction, network-based models were built for DTI prediction. The best bSDTNBI-FCFP_4 model was further used to predict DTIs for AAs. Second, a structure-based molecular docking method was employed for rescreening the prediction results to obtain more credible target proteins. Finally, in vitro experiments were conducted for validation of the predicted targets, and Nrf2 showed significant evidence as the target of anti-AD compound AA13. Moreover, we analyzed the potential mechanisms of AA13 for the treatment of AD. Generally, our combined strategy could be applied to other novel drugs or compounds and become a useful tool in identification of new targets and elucidation of disease mechanisms. Our model was deployed on our NetInfer web server (http:// lmmd.ecust.edu.cn/netinfer/).