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 leastsquares,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。
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.
出处
《分析化学》
SCIE
EI
CAS
CSCD
北大核心
2012年第10期1488-1493,共6页
Chinese Journal of Analytical Chemistry
基金
国家自然科学基金青年基金资助项目(No.81102900)
关键词
姜黄
挥发油
气相色谱-质谱联用
正交投影偏最小二乘法
组效关系
Curcuma
Volatile oil
Gas chromatography-mass spectrometry
Orthogonal partial least squares
Composition-activity relationship
