文献类型：期刊文献

英文题名：NADPHnet: a novel strategy to predict compounds for regulation of NADPH metabolism via network-based methods

作者：Pan, Fei[1];Wang, Cheng-nuo[1];Yu, Zhuo-hang[1];Wu, Zeng-rui[1];Wang, Ze[1];Lou, Shang[1];Li, Wei-hua[1];Liu, Gui-xia[1];Li, Ting[1];Zhao, Yu-zheng[1];Tang, Yun[1]

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

年份：2024

卷号：45

期号：10

起止页码：2199

外文期刊名：ACTA PHARMACOLOGICA SINICA

收录：;WOS:【SCI-EXPANDED(收录号:WOS:001252118500003)】；

基金：This work was supported by the National Key Research and Development Program of China (Grant 2019YFA0904800), the National Natural Science Foundation of China (Grant U23A20530, 82173746 and 82104066), and the Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism (Shanghai Municipal Education Commission).

语种：英文

外文关键词：NADPH metabolism; network-based inference; natural product; computational prediction

摘要：Identification of compounds to modulate NADPH metabolism is crucial for understanding complex diseases and developing effective therapies. However, the complex nature of NADPH metabolism poses challenges in achieving this goal. In this study, we proposed a novel strategy named NADPHnet to predict key proteins and drug-target interactions related to NADPH metabolism via network-based methods. Different from traditional approaches only focusing on one single protein, NADPHnet could screen compounds to modulate NADPH metabolism from a comprehensive view. Specifically, NADPHnet identified key proteins involved in regulation of NADPH metabolism using network-based methods, and characterized the impact of natural products on NADPH metabolism using a combined score, NADPH-Score. NADPHnet demonstrated a broader applicability domain and improved accuracy in the external validation set. This approach was further employed along with molecular docking to identify 27 compounds from a natural product library, 6 of which exhibited concentration-dependent changes of cellular NADPH level within 100 mu M, with Oxyberberine showing promising effects even at 10 mu M. Mechanistic and pathological analyses of Oxyberberine suggest potential novel mechanisms to affect diabetes and cancer. Overall, NADPHnet offers a promising method for prediction of NADPH metabolism modulation and advances drug discovery for complex diseases.