Zhang Shuqiao, Mo Zhuomao, Zhang Shijun, Li Xinyu
Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 611137, China.
Department of Traditional Chinese Medicine, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong 510080, China.
Evid Based Complement Alternat Med. 2021 Feb 22;2021:8947304. doi: 10.1155/2021/8947304. eCollection 2021.
To investigate the potential active ingredients and underlying mechanisms of (AA) on the treatment of hepatocellular carcinoma (HCC) based on network pharmacology.
In the present study, we used a network pharmacological method to predict its underlying complex mechanism of treating HCC. First, we obtained relative compounds of AA based on the traditional Chinese medicine systems pharmacology (TCMSP) database and collected potential targets of these compounds by target fishing. Then, we built HCC-related targets target by the oncogenomic database of hepatocellular carcinoma (OncoDB.HCC) and biopharmacological network (PharmDB-K) database. Based on the matching results between AA potential targets and HCC targets, we built a protein-protein interaction (PPI) network to analyze the interactions among these targets and screen the hub targets by topology. Furthermore, the function annotation and signaling pathways of key targets were performed by Gene Oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis using DAVID tools. Finally, the binding capacity between active ingredients and key targets was validated by molecular docking.
A total of 19 main active ingredients of AA were screened as target prediction; then, 25 HCC-related common targets were seeked out via multiple HCC databases. The areas of nodes and corresponding degree values of EGFR, ESR1, CCND1, MYC, EGF, and PTGS2 were larger and could be easily found in the PPI network. Furthermore, GO and KEGG enrichment analysis showed that these key targets were significantly involved in multiple biological processes and pathways which participated in tumor cell proliferation, apoptosis, angiogenesis, tumor invasion, and metastasis to accomplish the anti-HCC activity. The molecular docking analysis showed that quercetin could stably bind to the active pocket of EGFR protein 4RJ5 via LibDock.
The anticancer effects of AA on HCC were predicted to be associated with regulating tumor cell proliferation, apoptosis, angiogenesis, tumor invasion, and metastasis via various pathways such as the EGFR signaling pathway, ESR1 signaling pathway, and CCND1 signaling pathway. It is suggested that AA might be developed as a broad-spectrum antitumor drug based on its characteristics of multicomponent, multipath, and multitarget.
基于网络药理学探讨[具体药物名称未给出](AA)治疗肝细胞癌(HCC)的潜在活性成分及潜在机制。
在本研究中,我们采用网络药理学方法预测其治疗HCC的潜在复杂机制。首先,基于中药系统药理学(TCMSP)数据库获取AA的相关化合物,并通过靶点筛选收集这些化合物的潜在靶点。然后,通过肝细胞癌肿瘤基因组数据库(OncoDB.HCC)和生物药理学网络(PharmDB-K)数据库构建HCC相关靶点。基于AA潜在靶点与HCC靶点的匹配结果,构建蛋白质-蛋白质相互作用(PPI)网络以分析这些靶点之间的相互作用,并通过拓扑结构筛选枢纽靶点。此外,使用DAVID工具通过基因本体论(GO)和京都基因与基因组百科全书(KEGG)富集分析对关键靶点进行功能注释和信号通路分析。最后,通过分子对接验证活性成分与关键靶点之间的结合能力。
共筛选出19种AA的主要活性成分用于靶点预测;然后,通过多个HCC数据库找出25个与HCC相关的共同靶点。在PPI网络中,表皮生长因子受体(EGFR)、雌激素受体1(ESR1)、细胞周期蛋白D1(CCND1)、原癌基因Myc(MYC)、表皮生长因子(EGF)和前列腺素内过氧化物合酶2(PTGS2)的节点面积和相应度值较大,且易于发现。此外,GO和KEGG富集分析表明,这些关键靶点显著参与多个生物学过程和信号通路,这些过程和通路参与肿瘤细胞增殖、凋亡、血管生成、肿瘤侵袭和转移,从而实现抗HCC活性。分子对接分析表明,槲皮素可通过LibDock稳定结合到EGFR蛋白4RJ5的活性口袋。
预测AA对HCC的抗癌作用与通过表皮生长因子受体(EGFR)信号通路、雌激素受体1(ESR1)信号通路和细胞周期蛋白D1(CCND1)信号通路等多种途径调节肿瘤细胞增殖、凋亡、血管生成、肿瘤侵袭和转移有关。基于其多成分、多途径和多靶点的特点,提示AA可能被开发为一种广谱抗肿瘤药物。