Zhuang Yanshuang, Qin Kunming, Yang Bing, Liu Xiao, Cai Baochang, Cai Hao
Engineering Center of State Ministry of Education for Chinese Medicine Processing, Nanjing University of Chinese Medicine Nanjing 210023 China
Nanjing Haichang Chinese Medicine Group Co., Ltd. Nanjing 210061 China
RSC Adv. 2018 Feb 27;8(16):8870-8877. doi: 10.1039/c8ra00186c. eCollection 2018 Feb 23.
(XF), a famous traditional Chinese medicine (TCM), has been widely used in the treatment of rhinitis and other diseases. However, the targets of the main XF components found in the blood after oral administration of XF extract are still unclear. In the current study, a feasible systems pharmacology method was developed to predict these targets. In accordance with our previous research, XF components were selected including cleomiscosin A, myristic acid, succinic acid, xanthosine, sitostenone, emodin, apigenin, and chrysophanol. Three components, namely emodin, apigenin, and chrysophanol, failed to be detected with target proteins, thus the other five components, namely cleomiscosin A, myristic acid, succinic acid, xanthosine and sitostenone, were eventually chosen for further systematic analysis. Ninety-nine target proteins and fifty-two pathways were found after a series of analyses. The frequency of some target proteins was much higher than that of others; high frequencies were obtained for P15086, P07360, P07195, MAOM_HUMAN (P23368), P35558, P35520, ACE_HUMAN (P12821), C1S_HUMAN (P09871), PH4H_HUMAN (P00439), FPPS_HUMAN (P14324), P50613, P12724, IMPA1_HUMAN (P29218), HXK1_HUMAN (P19367), P14061, and MCR_HUMAN (P08235). The frequency of eight pathways was also high, including Generic Transcription Pathway, RNA Polymerase II Transcription, Metabolism, Metabolism of steroids, Gene expression (Transcription), Cellular responses to stress, Platelet activation, signaling and aggregation, Signaling by Receptor Tyrosine Kinases, and Cellular Senescence. This study identified a common pathway - the Metabolism pathway - for all five XF components. We successfully developed a network pharmacology method to predict the potential targets of the main XF components absorbed in serum after oral administration of XF extract.
辛夷（XF）是一种著名的传统中药，已被广泛用于治疗鼻炎和其他疾病。然而，口服XF提取物后血液中主要XF成分的作用靶点仍不清楚。在本研究中，开发了一种可行的系统药理学方法来预测这些靶点。根据我们之前的研究，选择了包括金腰子素A、肉豆蔻酸、琥珀酸、黄嘌呤核苷、麦角甾烯酮、大黄素、芹菜素和大黄酚在内的XF成分。其中大黄素、芹菜素和大黄酚这三种成分未检测到与之相互作用的靶蛋白，因此最终选择其余五种成分，即金腰子素A、肉豆蔻酸、琥珀酸、黄嘌呤核苷和麦角甾烯酮进行进一步的系统分析。经过一系列分析，发现了99个靶蛋白和52条通路。一些靶蛋白出现的频率远高于其他蛋白；P15086、P07360、P07195、MAOM_HUMAN（P23368）、P35558、P35520、ACE_HUMAN（P12821）、C1S_HUMAN（P09871）、PH4H_HUMAN（P00439）、FPPS_HUMAN（P14324）、P50613、P12724、IMPA1_HUMAN（P29218）、HXK1_HUMAN（P19367）、P14061和MCR_HUMAN（P08235）出现的频率较高。八条通路的频率也较高，包括通用转录途径、RNA聚合酶II转录、代谢、类固醇代谢、基因表达（转录）、细胞应激反应、血小板激活、信号传导和聚集、受体酪氨酸激酶信号传导以及细胞衰老。本研究确定了所有五种XF成分的一条共同通路——代谢通路。我们成功开发了一种网络药理学方法，以预测口服XF提取物后血清中吸收的主要XF成分的潜在靶点。
