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综合二维前列腺细胞膜色谱系统与网络药理学联用,从大黄和大黄根茎中表征膜结合活性成分及其靶标。

Combination of comprehensive two-dimensional prostate cancer cell membrane chromatographic system and network pharmacology for characterizing membrane binding active components from Radix et Rhizoma Rhei and their targets.

机构信息

School of Pharmacy, Second Military Medical University, No. 325 Guohe Road, Shanghai, 200433, PR China.

Department of Pharmacy, 210th Hospital of the Chinese People's Liberation Army, Dalian, 116021, PR China; Postdoctoral Research Workstation, 210th Hospital of the Chinese People's Liberation Army, Dalian, 110615, PR China.

出版信息

J Chromatogr A. 2018 Aug 24;1564:145-154. doi: 10.1016/j.chroma.2018.06.015. Epub 2018 Jun 6.

DOI:10.1016/j.chroma.2018.06.015
PMID:29895409
Abstract

Prostate cancer (PCa) is a common and fatal cancer for men and effective treatment options are still not enough for patients. Radix et Rhizoma Rhei had been applied to treat PCa long-termly and effectively when combined with surgical treatment and chemotherapy. However, its active components and target proteins are still not quite clear. As membrane receptors play a vital role in PCa, in this study, a novel strategy that combines comprehensive 2D 3-aminopropyltriethoxysilane-decorated prostate cancer cell (DU145) membrane chromatographic (CMC) system with network pharmacology approach was developed to characterize membrane binding active components proteins from Radix et Rhizoma Rhei and their targets. Thirteen active components were screened out by CMC system, among which emodin and rhapontigrnin with good membrane binding behaviors were validated to show ideal inhibitory effects on DU145 cells by cell viability and cell apoptosis assays. Five membrane proteins were predicted as the potential targets by the a specific network pharmacology approach, among which mast/stem cell growth factor receptor Kit (KIT) was identified as the most possible target by network data mining. Surface plasmon resonance analysis verified that the dissociation constant (K) of rhapontigrnin and emodin with KIT was 6.06 × 10 M and 8.82 × 10 M, respectively. Our results showed that the combination of comprehensive 2D CMC system and network pharmacology based target identification could not only rapidly identify the membrane binding components but also find the potential membrane protein targets with high confidence, which could broaden the range of application scope of CMC, especially for the screening of active compounds from complex chemical samples using primary pathologic cell lines.

摘要

前列腺癌(PCa)是男性常见的致命癌症,有效的治疗选择仍然不足。大黄和大黄根在与手术治疗和化疗结合使用时,已被长期有效地用于治疗 PCa。然而,其活性成分和靶蛋白仍不清楚。由于膜受体在 PCa 中起着至关重要的作用,在这项研究中,开发了一种将综合 2D 3-氨丙基三乙氧基硅烷修饰的前列腺癌细胞(DU145)膜色谱(CMC)系统与网络药理学方法相结合的新策略,以鉴定大黄和大黄根中的膜结合活性成分蛋白及其靶蛋白。通过 CMC 系统筛选出 13 种活性成分,其中大黄素和虎杖苷具有良好的膜结合行为,通过细胞活力和细胞凋亡实验验证对 DU145 细胞具有理想的抑制作用。通过特定的网络药理学方法预测到 5 种膜蛋白作为潜在的靶标,其中通过网络数据挖掘鉴定出 mast/stem cell growth factor receptor Kit (KIT) 作为最可能的靶标。表面等离子体共振分析验证了 rhapontigrnin 和大黄素与 KIT 的解离常数(K)分别为 6.06×10 M 和 8.82×10 M。我们的结果表明,综合 2D CMC 系统与基于网络药理学的靶标识别相结合,不仅可以快速鉴定膜结合成分,还可以找到具有高置信度的潜在膜蛋白靶标,这可以拓宽 CMC 的应用范围,特别是用于筛选初级病理细胞系中复杂化学样品中的活性化合物。

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