目的:运用网络药理学的方法,阐释米糠活性成分抗肿瘤的潜在靶点和分子机制。方法:查阅及检索TCMSP、BATMAN-TCM、PubMed、CNKI、TTD、GeneCard、OMIM等数据库,筛选米糠活性成分及肿瘤相关的靶点,建立核心靶点数据集。然后使用DAVID数据库进行GO和KEGG信号通路富集分析。结果:最终得到12个米糠活性成分,有5个靶点可能在抗肿瘤过程中发挥了重要作用,富集得到4条信号通路。结果表明,癌症信号通路、Hippo信号通路与米糠抗肿瘤作用密切相关。结论:网络药理学为米糠物质基础和分子机制的研究奠定了理论基础,也为米糠资源的开发利用及深入研究提供了参考依据。 Objective: To investigate the potential target and molecular mechanism of active components of rice bran against tumor using the method of network pharmacology. Methods: The active components of rice bran and tumor-related targets were screened and target data sets were established by searching and retrieving databases such as TCMSP, BATMAN-TCM, PubMed, CNKI, TTD, GeneCard, OMIM, etc. Then enrichment analysis of GO and KEGG signal pathways was performed using DAVID database. Results: Twelve active components of rice bran were obtained. Evaluation and screening of five targets play an important role in the anti-tumor process. Four signal pathways were selected to participate in the anti-tumor effect. The results of network analysis showed that the anti-tumor mechanism of rice bran may be related to the regulation of transcription disorder in cancer signaling pathway and Hippo signaling pathway. Conclusion: Network pharmacology laid a foundation for finding the active components and action mechanism of rice bran, and provided a new idea and theoretical basis for the development and utilization of rice bran resources.
目的:运用网络药理学的方法,阐释米糠活性成分抗肿瘤的潜在靶点和分子机制。方法:查阅及检索TCMSP、BATMAN-TCM、PubMed、CNKI、TTD、GeneCard、OMIM等数据库,筛选米糠活性成分及肿瘤相关的靶点,建立核心靶点数据集。然后使用DAVID数据库进行GO和KEGG信号通路富集分析。结果:最终得到12个米糠活性成分,有5个靶点可能在抗肿瘤过程中发挥了重要作用,富集得到4条信号通路。结果表明,癌症信号通路、Hippo信号通路与米糠抗肿瘤作用密切相关。结论:网络药理学为米糠物质基础和分子机制的研究奠定了理论基础,也为米糠资源的开发利用及深入研究提供了参考依据。
米糠,活性成分,抗肿瘤,网络药理学,作用机制
Yuqing Liang1,2, Yubao Chen1, Haixia Ran1, Jia Qiu1, Guangping Liang1,2*
1Zunyi Medical and Pharmaceutical College, Zunyi Guizhou
2Collaborative Innovation Center for Sustainable Utilization of Wild Medicinal Plant Resources in Guizhou Province, Zunyi Guizhou
Received: Oct. 31st, 2020; accepted: Nov. 11th, 2020; published: Nov. 18th, 2020
Objective: To investigate the potential target and molecular mechanism of active components of rice bran against tumor using the method of network pharmacology. Methods: The active components of rice bran and tumor-related targets were screened and target data sets were established by searching and retrieving databases such as TCMSP, BATMAN-TCM, PubMed, CNKI, TTD, GeneCard, OMIM, etc. Then enrichment analysis of GO and KEGG signal pathways was performed using DAVID database. Results: Twelve active components of rice bran were obtained. Evaluation and screening of five targets play an important role in the anti-tumor process. Four signal pathways were selected to participate in the anti-tumor effect. The results of network analysis showed that the anti-tumor mechanism of rice bran may be related to the regulation of transcription disorder in cancer signaling pathway and Hippo signaling pathway. Conclusion: Network pharmacology laid a foundation for finding the active components and action mechanism of rice bran, and provided a new idea and theoretical basis for the development and utilization of rice bran resources.
Keywords:Rice Bran, Active Components, Antineoplastic Agents, Network Pharmacology, Mechanism of Action
Copyright © 2020 by author(s) and Hans Publishers Inc.
This work is licensed under the Creative Commons Attribution International License (CC BY 4.0).
http://creativecommons.org/licenses/by/4.0/
当前肿瘤已经成为危害人类健康最严重的疾病之一,预计到2020年左右全球因肿瘤导致死亡的人数将达到2000多万,同时肿瘤发病率在我国也逐年上升 [
查阅及检索CNKI、PubMed和TCMSP (http://tcmspw.com/tcmsp.php)数据库,构建米糠活性成分数据集。依据相似性分析,通过BATMAN-TCM (http://bionet.ncpsb.org/batman-tcm/)数据库、TTD (http://bidd.nus.edu.sg/group/cjttd/)和TCMSP数据库,建立米糠活性成分的作用靶点,然后通过GeneCard (https://www.genecards.org/)和OMIM (http://www.omim.org/)数据库,构建肿瘤相关的靶点数据集。
PPI (http://www.genome.jp/kegg/)网络分析,将米糠的活性成分、作用靶点和交互蛋白对应的靶点绘制“成分-靶点-疾病”网络图,然后使用Cytoscape 3.7.0进行可视化分析,得到节点的拓扑参数值(Degree, Closeness centrality, Betweenness centrality),以3个拓扑参数值均大于所有节点中位数值为筛选标准,筛选米糠抗肿瘤的核心靶点。STRING (https://string-db.org/)数据库进行蛋白互作网络分析。
利用DAVID (https://david.ncifcrf.gov/)数据库进行GO和KEGG通路富集分析。
利用KEGG数据库的KEGG Mapper功能在与肿瘤相关的作用通路上标注核心靶点,阐释米糠多靶点、多途径协同抗肿瘤的分子机制。
最终得到了12个米糠的活性成分,结果见表1。筛选出693个靶点,并构建了米糠抗肿瘤的交互网络,用不同形状和颜色可视化,结果见图1。黄色表示药物与疾病共同作用的靶点,也是米糠抗肿瘤的重要靶点;红色表示米糠的活性成分;蓝色表示活性成分的作用靶点;紫色表示交互蛋白。
NO | 成分 | 靶标数目 |
---|---|---|
1 | 阿魏酸(Ferulic Acid) | 8 |
2 | γ-谷维素(gamma-Oryzanol) | 6 |
3 | 维生素E (VITAMIN E) | 21 |
4 | 甾醇(Sterol) | 11 |
5 | 油酸(Oleic Acid) | 8 |
6 | 亚油酸(Linoleic Acid) | 13 |
7 | 植酸(Fytic Acid) | 4 |
8 | 花色苷(Flavylium) | 5 |
9 | γ-氨基丁酸(gamma-Aminobutyric acid) | 46 |
11 | β-谷甾醇(beta-Sitosterol) | 10 |
12 | 维生素C (Vitamin C) | 12 |
13 | 棕榈酸(Palmitic Acid) | 34 |
表1. 米糠活性成分及靶标
图1. 米糠抗肿瘤作用的“成分–靶点–疾病”交互网络
网络拓扑参数分析,得到节点的拓扑参数(Degree、Betweenness centrality和Closeness centrality)中位数分别为:6.5、0.0470和0.1480。通过筛选后,最终得到5个核心靶点,结果见表2,蛋白与蛋白的相互作用网络见图2。结果显示,这些蛋白彼此相互关联且彼此相互调节。
Uniprot ID | Protein names | Gene names | Closeness Centrality | Degree | Betweeness Centrality |
---|---|---|---|---|---|
O15392 | Baculoviral IAP repeat-containing protein 5 | BIRC5 | 0.15 | 8 | 0.05 |
P35222 | Catenin beta-1 | CTNNB1 | 0.16 | 22 | 0.13 |
P09874 | Poly [ADP-ribose] polymerase 1 | PARP1 | 0.19 | 11 | 0.18 |
P07900 | Heat shock protein HSP 90-alpha | HSP90AA1 | 0.23 | 26 | 0.52 |
P62136 | Serine/threonine-protein phosphatase PP1-alpha catalytic subunit | PPP1CA | 0.17 | 9 | 0.054 |
表2. 米糠活性成分治疗肿瘤的直接作用靶点相关拓扑参数
图2. 米糠治疗肿瘤的蛋白互作关系图
GO富集分析,共得到24条生物过程,其中P值 ≤ 0.05的生物过程共有17条,结果见表3。结果表明,这些靶点与蛋白糖基化、β-连环蛋白复合物、离子通道、蛋白激酶等多种生物过程的调控相关,且这些生物过程与肿瘤的发生、发展密切相关。反映了肿瘤发病涉及体内多个生物过程的异常,同时表明米糠可能是通过调节这些生物过程发挥抗肿瘤效应的。
Category | Term | Count | Count (%) | P-Value | |
---|---|---|---|---|---|
GOTERM_BP_DIRECT | beta-catenin destruction complex disassembly | 2 | 40 | 0.0052 | |
GOTERM_BP_DIRECT | neuron migration | 2 | 40 | 0.025 | |
GOTERM_BP_DIRECT | protein sumoylation | 2 | 40 | 0.028 | |
GOTERM_BP_DIRECT | G2/M transition of mitotic cell cycle | 2 | 40 | 0.032 | |
GOTERM_BP_DIRECT | response to drug | 2 | 40 | 0.07 | |
GOTERM_BP_DIRECT | cell division | 2 | 40 | 0.081 | |
GOTERM_CC_DIRECT | nucleus | 5 | 100 | 0.00054 | |
GOTERM_CC_DIRECT | cytosol | 5 | 100 | 0.0078 | |
GOTERM_CC_DIRECT | cytoplasm | 4 | 80 | 0.021 | |
GOTERM_CC_DIRECT | protein complex | 4 | 80 | 0.074 | |
GOTERM_CC_DIRECT | membrane | 3 | 60 | 0.003 | |
GOTERM_CC_DIRECT | nuclear chromosome, telomeric region | 3 | 60 | 0.074 | |
GOTERM_CC_DIRECT | cell-cell junction | 2 | 40 | 0.028 | |
GOTERM_CC_DIRECT | basolateral plasma membrane | 2 | 40 | 0.037 | |
GOTERM_CC_DIRECT | transcription factor complex | 2 | 40 | 0.039 | |
GOTERM_MF_DIRECT | protein binding | 5 | 100 | 0.073 | |
GOTERM_MF_DIRECT | enzyme binding | 3 | 60 | 0.0023 | |
GOTERM_MF_DIRECT | identical protein binding | 3 | 60 | 0.011 | |
GOTERM_MF_DIRECT | estrogen receptor binding | 2 | 40 | 0.0087 | |
GOTERM_MF_DIRECT | protein phosphatase binding | 2 | 40 | 0.015 | |
GOTERM_MF_DIRECT | histone deacetylase binding | 2 | 40 | 0.024 | |
GOTERM_MF_DIRECT | ion channel binding | 2 | 40 | 0.027 | |
GOTERM_MF_DIRECT | transcription factor binding | 2 | 40 | 0.066 | |
GOTERM_MF_DIRECT | protein kinase binding | 2 | 40 | 0.086 | |
表3. 米糠抗肿瘤作用的GO生物学功能富集分析结果
KEGG富集分析得到4条主要信号通路,结果表4。其中Hippo signaling pathway和Pathways in cancer通路均显示出具有直接或间接参与抗肿瘤作用,此结果与肿瘤发病机制紧密相关。图3为米糠活性成分对Hippo signaling pathway信号通路靶点标注图。
Category | Term | Count | Count(%) | P-Value |
---|---|---|---|---|
KEGG_PATHWAY | Hippo signaling pathway | 3 | 60 | 0.0028 |
KEGG_PATHWAY | Pathways in cancer | 3 | 60 | 0.018 |
KEGG_PATHWAY | Colorectal cancer | 2 | 40 | 0.035 |
KEGG_PATHWAY | Prostate cancer | 2 | 40 | 0.05 |
表4. 米糠抗肿瘤作用的KEGG通路富集分析结果
图3. 米糠活性成分在肿瘤相关通路中的作用靶点标注图
米糠是稻谷加工过程中的主要副产品,我国产量巨大,多数都作为动物饲料,其营养价值、药用价值、资源优势没有得到充分的发挥。国内外研究显示,米糠是一种具有广泛开发潜力的高附加值资源。随着科学技术的不断发展,对米糠中活性成分的研究也不断深入到医药领域。朱丽丹等 [
本研究利用网络药理学的方法对米糠活性成分抗肿瘤的靶点和信号通路进行了分析,并构建了“成分–靶点–疾病”交互网络图,发现了4条主要信号通路,其中Hippo信号通路是一条抑制细胞生长的信号通路。在哺乳动物中,Hippo信号通路上游的膜蛋白受体感受到胞外环境的生长抑制信号后,经过一系列激酶的磷酸化反应,最终作用于下游效应因子YAP和TAZ,继而与细胞骨架蛋白相互作用,被滞留在胞质内,无法进入细胞核进行转录激活功能,从而实现对器官大小和体积的调控,因此Hippo信号通路抗肿瘤可能是通过抑制肿瘤细胞的生长发挥作用。本研究旨在为米糠资源的开发利用及深入研究提供参考,为实现米糠的高附加值奠定基础。
贵州省职业教育质量提升工程计划(黔教办职成函[
梁玉清,陈玉宝,冉海霞,邱 佳,梁光平. 米糠活性成分抗肿瘤的网络药理学研究Prediction of Active Components from Rice Bran Based on Network Pharmacology[J]. 药物资讯, 2020, 09(06): 218-224. https://doi.org/10.12677/PI.2020.96032