基于组效关系的姜黄挥发油抗肿瘤活性成分辨识研究

引用本文: 蒋建兰, 丁洪涛, 苏鑫, 元英进. 基于组效关系的姜黄挥发油抗肿瘤活性成分辨识研究[J]. 分析化学, 2012, 40(10): 1488-1493. doi: 10.3724/SP.J.1096.2012.11387 shu

Citation: JIANG Jian-Lan, DING Hong-Tao, SU Xin, YUAN Ying-Jin. Identification of Anti-tumor Ingredients in Curcuma Volatile Oil Based on Composition-Activity Relationship[J]. Chinese Journal of Analytical Chemistry, 2012, 40(10): 1488-1493. doi: 10.3724/SP.J.1096.2012.11387 shu

基于组效关系的姜黄挥发油抗肿瘤活性成分辨识研究

通讯作者: 蒋建兰

基金项目:
本文系国家自然科学基金青年基金资助项目(No.81102900) (No.81102900)

摘要: 基于GC-MS分析,建立了姜黄挥发油的化学成分与其抑制人宫颈癌Hela细胞作用的组效关系模型,寻找与药效显著相关的活性成分。采用水蒸汽蒸馏法提取得到31批姜黄挥发油,提取率在1.63%-4.52%之间;采用GC-MS联用仪建立了31批姜黄挥发油的指纹图谱,确定了20个特征峰,以特征峰的相对峰面积(各峰面积与内标正十三烷的峰面积之比)来表征其相对含量;MTT法测定姜黄挥发油抑制人宫颈癌Hela细胞活性,以抑制率为评价指标;利用Simca-p11.5软件的正交投影偏最小二乘法(Orthogonal Partial least squares, OPLS) 和SPSS软件的双变量相关(bivariate)分析,研究特征峰与药效的相关性,根据S-载荷图、变异权重参数值(Variable importance in projection, VIP) 和皮尔逊(Pearson)相关系数来辨识显著活性成分。结果表明,11, 15, 7, 19, 3, 6, 12, 14, 9号等9个特征峰与姜黄挥发油抑制Hela细胞活性显著相关,除19号峰尚未定性外,11, 15, 7, 3, 6, 12, 14和9号峰对应的成分分别为芳姜黄酮、β-姜黄酮、姜烯、β-榄香烯、α-姜黄烯、α-姜黄酮、吉马酮和β-倍半水芹烯。

关键词:

English

Identification of Anti-tumor Ingredients in Curcuma Volatile Oil Based on Composition-Activity Relationship

1.
Key Laboratory of Systems Bioengineering, Ministry of Education; Tianjin Key Laboratory of Biological and Pharmaceutical Engineering; Department of Pharmaceutical Engineering, School of Chemical Engineering and Technology, Tianjin University; Tianjin 300072, China

Corresponding author: 蒋建兰

Received Date: 08 December 2011
Fund Project:
本文系国家自然科学基金青年基金资助项目(No.81102900)

Abstract: The Composition-activity relationship (CAR) model of curcuma volatile oil based on GC-MS analysis was established to recognize the active compounds. 31 batches of curcuma volatile oil were prepared using steam distillation with the extraction rate ranging from 1.63% to 4.52%, and quantitatively analyzed by GC-MS. Anti-tumor activity was investigated by MTT assays on Hela cell line. The orthogonal partial least squares (OPLS) and bivariate correlation analysis was respectively performed on SIMCA-P 11.5 and SPSS 18.0 software to construct the CAR model of curcuma volatile oil. The results showed that 9 peaks including Peaks 11, 15, 7, 19, 3, 6, 12, 14 and 9 were significantly related to anti-tumor activity according to scores plot, variable importance in projection (VIP) values in OPLS and Pearson correlation coefficient in bivariate correlation analysis; Peaks 11, 15, 7, 3, 6, 12, 14 and 9 were identified as ar-tumerone, β-tumerone, zingiberene, β-elemene, α-curcumene, α-tumerone, germacrone, β-sesquiphellandrene, respectively.

Key words:

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1.
沈阳化工大学材料科学与工程学院沈阳 110142

基于组效关系的姜黄挥发油抗肿瘤活性成分辨识研究

通讯作者: 蒋建兰

English

Identification of Anti-tumor Ingredients in Curcuma Volatile Oil Based on Composition-Activity Relationship

Corresponding author: 蒋建兰

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通讯作者: 陈斌, bchen63@163.com

中国化学会秘书处

基于组效关系的姜黄挥发油抗肿瘤活性成分辨识研究

通讯作者: 蒋建兰

English

Identification of Anti-tumor Ingredients in Curcuma Volatile Oil Based on Composition-Activity Relationship

Corresponding author: 蒋建兰

CCS Chemistry：嵌段共聚物自组装成 “三明治”二维有机材料，实现纳米级压力传感功能

CCS Chemistry：颜徐州、鲍哲南： 你的皮肤可能是一片SPMs

CCS Chemistry：工作高效不疲劳，只须让催化剂动起来

CCS Chemistry：静电组装导向聚合- 聚电解质纳米凝胶量化制备新策略

CCS Chemistry：金黄色葡萄球菌醛基脱氢酶是如何识别特异性底物的？

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通讯作者: 陈斌, bchen63@163.com

中国化学会秘书处

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