Antitumor Active Constituents Identification In The Combination Of Turmeric And Licorice Extracts Based On The Composition-activity Relationship

Turmeric(Curcuma longa L.)and licorice(Glycyrrhiza)roots have a long history of use in traditional Chinese medicine(TCM).It has been reported that both of them have a variety of pharmacological activities.In this study,we investigated the relationship between chemical composition and the anti-tumor activity of the combination of turmeric and licorice extracts based on chemometrics.The composition-activity relationship(CAR)model was employed to determine potential lead active compounds in the combination of turmeric and licorice extracts,which provided an economical and efficient approach for drug discovery from herbal medicine.The main research works were as follows:1.The HPLC-UV was used to establish the fingerprint of 50 batches of turmeric extract.Using isoquercitrin as internal standard,we quantified 15 common peaks and found that the content differed considerably from each other and that the content of each constituent varied a lot from batch to batch.The UPLC-MS/MS was conducted to qualitatively analyze the fingerprint of turmeric.12 peaks were identified with reference to literature data based on their LC-MS/MS information among the 15 peaks,including curcuminoids and curcuma volatile oil.2.The HPLC-UV was used to establish the fingerprint of 50 batches of licorice extract.Using isoquercitrin as internal standard,we quantified 31 common peaks and found that the content differed considerably from each other and that the content of each constituent varied a lot from batch to batch.The UPLC-MS/MS was conducted to qualitatively analyze the fingerprint of licorice.29 peaks were identified with reference to literature data based on their LC-MS/MS information among the 31 peaks,including triterpenoid saponins,flavonoids,isoflavones and coumarin.3.The inhibitory effect of the combination of turmeric and licorice extracts on He La cells were measured by the MTT assay with the inhibition ratios ranging from 0.044 to 0.918.The results revealed that the combination extracts from different batches had evident diversity in anti-tumor activity against HeLa cells.4.The support vector regression(SVR)model was constructed with 46 chromatographic peaks from 50 batches of turmeric and licorice as input variables and inhibition ratios on HeLa cells as output variables.The particle swarm optimization(PSO)algorithm was explored to optimize the model parameters.The optimal model was obtained with SVR parameters of C,g and ? being equal to 10.4771,0.1469 and 0.001,respectively.In the optimal model,the mean square error(MSE)was as low as 0.0083 and the correlation coefficient(R)was as high as 0.9321.5.15 compounds possessing the high absolute mean impact value(MIV,>0.003)were identified to have significant cytotoxicity against He La cells using the optimal SVR model combined with MIV,which eight compounds were from turmeric.We chose these 15 compounds as input variables to reconstruct a MIV-PSO-SVR model.Compared with the original model,the new model still had a better prediction performance.