| 夏枯草抗乳腺癌成分-靶点-通路的网络药理学研究 |
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| 作者姓名： | 李亚梅 彭壮 徐佳 张智敏 林丽美 夏伯候 廖端芳 |
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| 作者单位： | 湖南中医药大学, 湘产大宗药材品质评价湖南省重点实验室, 湖南 长沙 410208;湖南中医药大学, 湖湘中药资源保护与利用协同创新中心, 湖南 长沙 410208,湖南中医药大学, 湘产大宗药材品质评价湖南省重点实验室, 湖南 长沙 410208,湖南中医药大学, 湘产大宗药材品质评价湖南省重点实验室, 湖南 长沙 410208,湖南中医药大学, 湘产大宗药材品质评价湖南省重点实验室, 湖南 长沙 410208;湖南中医药大学, 湖湘中药资源保护与利用协同创新中心, 湖南 长沙 410208,湖南中医药大学, 湘产大宗药材品质评价湖南省重点实验室, 湖南 长沙 410208;湖南中医药大学, 湖湘中药资源保护与利用协同创新中心, 湖南 长沙 410208,湖南中医药大学, 湘产大宗药材品质评价湖南省重点实验室, 湖南 长沙 410208;湖南中医药大学, 湖湘中药资源保护与利用协同创新中心, 湖南 长沙 410208,湖南中医药大学, 湘产大宗药材品质评价湖南省重点实验室, 湖南 长沙 410208;湖南中医药大学, 湖湘中药资源保护与利用协同创新中心, 湖南 长沙 410208 |
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| 基金项目： | 湖南省自然科学基金（2017JJ4045, 2019JJ50443, 2019JJ50449）；长沙市科技计划项目（KQ1602023, KQ1701073, KQ1801041, KQ1801045）；湖南中医药大学中药学一流学科。 |
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| 摘 要： | 目的 应用网络药理学方法预测夏枯草抗乳腺癌的作用靶点及相关信号通路，挖掘其抗乳腺癌的作用机制。方法 在TCMSP和TCMID数据库中检索并筛选出夏枯草的潜在活性成分，在TCMSP数据库中查询活性成分作用靶点并采用Cytoscape 3.7.1软件构建活性成分-靶点网络图；在HPO和DisGeNET数据库中检索乳腺癌相关基因；将活性成分作用靶点和乳腺癌相关基因进行比对，得到重复项（即活性抗乳腺癌的可能靶点）；利用String平台构建潜蛋白互作网络（PPI）；使用Cytoscape 3.7.1软件构建夏枯草潜在活性成分-靶点-乳腺癌网络，并根据度值、介数和紧密度筛选出关键靶点；应用Metascape数据库分析关键靶点的KEGG信号通路并进行GO生物过程富集。结果 夏枯草中有19种活性成分，作用于253个靶点；夏枯草有17种成分可作用于乳腺癌相关的29个靶点，其中有7个关键靶点，7种主要活性成分，9条相关信号通路。结论 夏枯草可通过雌激素受体、细胞特异性周期蛋白、表皮生长因子受体等靶点及相关通路，发挥抗乳腺癌作用。
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| 关 键 词： | 夏枯草 乳腺癌 网络药理学 活性成分 |
| 收稿时间： | 2019/4/19 0:00:00 |
Network Pharmacology Study on Anti-Breast Cancer of Ingredients-Targets-Pathways of Prunella Vulgaris L. |
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| Authors: | LI Yamei PENG Zhuang XU Ji ZHANG Zhimin LIN Limei XIA Bohou and LIAO Duanfang |
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| Affiliation: | Hunan University of Chinese Medicine, Key Laboratory for Quality Evaluation of Bulk Herbs of Hunan Province, Changsha, Hunan 410208, China;Collaborative Innovation Center of Resource for Protection and Utilization of Chinese Materia Medica of Hunan Province, Changsha, Hunan 410208, China,Hunan University of Chinese Medicine, Key Laboratory for Quality Evaluation of Bulk Herbs of Hunan Province, Changsha, Hunan 410208, China,Hunan University of Chinese Medicine, Key Laboratory for Quality Evaluation of Bulk Herbs of Hunan Province, Changsha, Hunan 410208, China,Hunan University of Chinese Medicine, Key Laboratory for Quality Evaluation of Bulk Herbs of Hunan Province, Changsha, Hunan 410208, China;Collaborative Innovation Center of Resource for Protection and Utilization of Chinese Materia Medica of Hunan Province, Changsha, Hunan 410208, China,Hunan University of Chinese Medicine, Key Laboratory for Quality Evaluation of Bulk Herbs of Hunan Province, Changsha, Hunan 410208, China;Collaborative Innovation Center of Resource for Protection and Utilization of Chinese Materia Medica of Hunan Province, Changsha, Hunan 410208, China,Hunan University of Chinese Medicine, Key Laboratory for Quality Evaluation of Bulk Herbs of Hunan Province, Changsha, Hunan 410208, China;Collaborative Innovation Center of Resource for Protection and Utilization of Chinese Materia Medica of Hunan Province, Changsha, Hunan 410208, China and Hunan University of Chinese Medicine, Key Laboratory for Quality Evaluation of Bulk Herbs of Hunan Province, Changsha, Hunan 410208, China;Collaborative Innovation Center of Resource for Protection and Utilization of Chinese Materia Medica of Hunan Province, Changsha, Hunan 410208, China |
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| Abstract: | Objective To predict the anti-breast cancer target and related signaling pathways, and explore the anti-breast cancer mechanism of Prunella Vulgaris L. by network pharmacology. Methods The potential active ingredients of Prunella vulgaris L. were searched and screened in the TCMSP and TCMID databases. The targets of potential active ingredients were searched in the TCMSP database, and Cytoscape 3.7.1 software was used to construct active ingredients-target network map. The breast cancer related genes were searched in the HPO and DisGe NET databases. Comparing the target of active ingredients of breast cancer-related genes to get duplicates (i.e. possible targets of active anti-breast cancer). The potential protein interaction network (PPI) was constructed by using the String platform. The cytoscape 3.7.1 software was used to construct a potential active component-target-breast cancer network of Prunella vulgaris L., and screen out the key targets based on the median of degree, betweenness and closeness. Metascape database was applied to analyze KEGG signaling pathways of key targets and perform GO biological processes enrichment. Results There were 19 active components in Prunella vulgaris L., which acted on 253 targets, and it had 17 components that acted on 29 targets associated with breast cancer, 7 key targets, 7 main active ingredients, and 9 related signaling pathways. Conclusion Prunella vulgaris L. can play the anti-breast effect through estrogen receptor, G1/S-specific cyclin-D1, epidermal growth factor receptor and some correlation signaling pathway. |
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| Keywords: | Prunella vulgaris L breast cancer network pharmacology active ingredients |
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