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The Multivariate Regression Statistics Strategy to Investigate Content-Effect Correlation of Multiple Components in Traditional Chinese Medicine Based on a Partial Least Squares Method

by 1, 2, 1 and 1,*
1
State Key Laboratory of Natural Medicines, Key Lab of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, 24 Tong Jia Xiang, Nanjing, Jiangsu, 210009, China
2
China National Center for biotechnology Development, Beijing 100039, China
*
Author to whom correspondence should be addressed.
Molecules 2018, 23(3), 545; https://doi.org/10.3390/molecules23030545
Received: 4 February 2018 / Revised: 25 February 2018 / Accepted: 28 February 2018 / Published: 1 March 2018
Amultivariate regression statisticstrategy was developed to clarify multi-components content-effect correlation ofpanaxginseng saponins extract and predict the pharmacological effect by components content. In example 1, firstly, we compared pharmacological effects between panax ginseng saponins extract and individual saponin combinations. Secondly, we examined the anti-platelet aggregation effect in seven different saponin combinations of ginsenoside Rb1, Rg1, Rh, Rd, Ra3 and notoginsenoside R1. Finally, the correlation between anti-platelet aggregation and the content of multiple components was analyzed by a partial least squares algorithm. In example 2, firstly, 18 common peaks were identified in ten different batches of panax ginseng saponins extracts from different origins. Then, we investigated the anti-myocardial ischemia reperfusion injury effects of the ten different panax ginseng saponins extracts. Finally, the correlation between the fingerprints and the cardioprotective effects was analyzed by a partial least squares algorithm. Both in example 1 and 2, the relationship between the components content and pharmacological effect was modeled well by the partial least squares regression equations. Importantly, the predicted effect curve was close to the observed data of dot marked on the partial least squares regression model. This study has given evidences that themulti-component content is a promising information for predicting the pharmacological effects of traditional Chinese medicine. View Full-Text
Keywords: panax ginseng saponins; partial least squares regression; fingerprints panax ginseng saponins; partial least squares regression; fingerprints
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MDPI and ACS Style

Peng, Y.; Li, S.-n.; Pei, X.; Hao, K. The Multivariate Regression Statistics Strategy to Investigate Content-Effect Correlation of Multiple Components in Traditional Chinese Medicine Based on a Partial Least Squares Method. Molecules 2018, 23, 545. https://doi.org/10.3390/molecules23030545

AMA Style

Peng Y, Li S-n, Pei X, Hao K. The Multivariate Regression Statistics Strategy to Investigate Content-Effect Correlation of Multiple Components in Traditional Chinese Medicine Based on a Partial Least Squares Method. Molecules. 2018; 23(3):545. https://doi.org/10.3390/molecules23030545

Chicago/Turabian Style

Peng, Ying, Su-ning Li, Xuexue Pei, and Kun Hao. 2018. "The Multivariate Regression Statistics Strategy to Investigate Content-Effect Correlation of Multiple Components in Traditional Chinese Medicine Based on a Partial Least Squares Method" Molecules 23, no. 3: 545. https://doi.org/10.3390/molecules23030545

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