文献类型：期刊文献

英文题名：wSDTNBI: a novel network-based inference method for virtual screening

作者：Wu, Zengrui[1];Ma, Hui[1];Liu, Zehui[1];Zheng, Lulu[1];Yu, Zhuohang[1];Cao, Shuying[1];Fang, Wenqing[1];Wu, Lili[1];Li, Weihua[1];Liu, Guixia[1];Huang, Jin[1];Tang, Yun[1]

机构：[1]East China Univ Sci & Technol, Shanghai Frontiers Sci Ctr Optogenet Tech Cell Me, Sch Pharm, 130 Meilong Rd, Shanghai 200237, Peoples R China

年份：2022

卷号：13

期号：4

起止页码：1060

外文期刊名：CHEMICAL SCIENCE

收录：;EI(收录号：20220511564324);WOS:【SCI-EXPANDED(收录号:WOS:000741015600001)】；

基金：We thank Dr Junhao Li (Uppsala University, Sweden) and Dr Hongbin Yang (University of Cambridge, United Kingdom) for helpful discussions. This work was supported by the National Key Research and Development Program of China (Grants 2016YFA0502304 and 2019YFA0904800), the National Natural Science Foundation of China (Grants 81872800, 81773775, 81973362, 82173746 and 82104066), the Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism (Shanghai Municipal Education Commission, Grant 2021 Sci & Tech 03-28), the Shanghai Post-doctoral Excellence Program (Grant 2018199), the Shanghai Sailing Program (Grant 19YF1412700), the China Postdoctoral Science Foundation (Grant 2019M661413), and the 111 Project (Grant BP0719034).

语种：英文

外文关键词：Carboxylic acids - Crystal structure - Tensors

摘要：In recent years, the rapid development of network-based methods for the prediction of drug-target interactions (DTIs) provides an opportunity for the emergence of a new type of virtual screening (VS), namely, network-based VS. Herein, we reported a novel network-based inference method named wSDTNBI. Compared with previous network-based methods that use unweighted DTI networks, wSDTNBI uses weighted DTI networks whose edge weights are correlated with binding affinities. A two-pronged approach based on weighted DTI and drug-substructure association networks was employed to calculate prediction scores. To show the practical value of wSDTNBI, we performed network-based VS on retinoid-related orphan receptor gamma t (ROR gamma t), and purchased 72 compounds for experimental validation. Seven of the purchased compounds were confirmed to be novel ROR gamma t inverse agonists by in vitro experiments, including ursonic acid and oleanonic acid with IC50 values of 10 nM and 0.28 mu M, respectively. Moreover, the direct contact between ursonic acid and ROR gamma t was confirmed using the X-ray crystal structure, and in vivo experiments demonstrated that ursonic acid and oleanonic acid have therapeutic effects on multiple sclerosis. These results indicate that wSDTNBI might be a powerful tool for network-based VS in drug discovery.