Cheng Zhang, Ye Fangdie, Xu Chenyang, Liang Yingchun, Zhang Zheyu, Chen Xinan, Dai Xiyu, Ou Yuxi, Mou Zezhong, Li Weijian, Chen Yiling, Zhou Quan, Zou Lujia, Mao Shanhua, Jiang Haowen
Department of Urology, Huashan Hospital, Fudan University, Shanghai, China.
Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai, China.
Front Pharmacol. 2022 Jul 14;13:932039. doi: 10.3389/fphar.2022.932039. eCollection 2022.
Our goal was to explore the bioactive constituents of Longsheyangquan (LSYQ) Decoction and elucidate its mechanisms on the treatment of bladder cancer (BCa). A total of 38 compounds were selected based on their pharmacokinetic properties in three large traditional Chinese medicine (TCM) databases. 654 putative targets of LSYQ Decoction were predicted using a structure-based, reverse-docking algorithm online, of which 343 overlapped with BCa-related protein-coding genes. The protein-protein interaction (PPI) network was constructed to perform module analysis for further Gene Ontology (GO) annotations and Kyoto Encyclopedia Genes and Genomes (KEGG) pathway enrichment analysis, which identified and as hub targets. The TCM-compound-target network and compound-target-pathway network together revealed that quercetin, diosmetin, enhydrin and luteolin were the main components of LSYQ Decoction. Finally, molecular docking showed the affinity between the key compounds and the hub target proteins to verify the accuracy of drug target prediction in the first place. The present study deciphered the core components and targets of LSYQ Decoction on the treatment of BCa in a comprehensive systemic pharmacological manner.
我们的目标是探索龙蛇羊泉汤（LSYQ）的生物活性成分，并阐明其治疗膀胱癌（BCa）的机制。基于三种大型中药（TCM）数据库中的药代动力学特性，共筛选出38种化合物。使用基于结构的在线反向对接算法预测了LSYQ汤的654个潜在靶点，其中343个与BCa相关的蛋白质编码基因重叠。构建蛋白质-蛋白质相互作用（PPI）网络进行模块分析，以进一步进行基因本体（GO）注释和京都基因与基因组百科全书（KEGG）通路富集分析，确定 和 为核心靶点。中药-化合物-靶点网络和化合物-靶点-通路网络共同表明，槲皮素、香叶木素、水仙苷和木犀草素是LSYQ汤的主要成分。最后，分子对接显示关键化合物与核心靶点蛋白之间的亲和力，首先验证了药物靶点预测的准确性。本研究以全面系统的药理学方式解读了LSYQ汤治疗BCa的核心成分和靶点。
