Alteration of Amino Acid Profiling Influenced by the Active Ingredients of DanHong Injection After Prescription Optimization
Authors Guo Z, Zhu Y, Xu W, Luo K, Xiao H, Wang Z
Received 21 June 2019
Accepted for publication 12 November 2019
Published 21 November 2019 Volume 2019:13 Pages 3939—3947
Checked for plagiarism Yes
Review by Single-blind
Peer reviewers approved by Dr Junhua Mai
Peer reviewer comments 2
Editor who approved publication: Dr Qiongyu Guo
Zhili Guo,1 Yan Zhu,2 Wenjuan Xu,3 Kaitao Luo,1 Hongbin Xiao,4 Zhong Wang3
1Chinese Medicine Department, Jiaxing Hospital of Traditional Chinese Medicine, Jiaxing University, Jiaxing, Zhejiang, 314000, People’s Republic of China; 2Chinese Medicine Department, Beijing Electric Power Hospital, Capital Medical University, Beijing 10073, People’s Republic of China; 3Chinese Medicine Pharmacology, Institute of Basic Research in Clinical Medicine. China Academy of Chinese Medical Sciences, Beijing 100700, People’s Republic of China; 4Beijing University of Chinese Medicine, Chinese Medicine Institute, Beijing 100029, People’s Republic of China
Correspondence: Kaitao Luo; Zhong Wang Tel +86057382079269; +861064014411-3308
Email firstname.lastname@example.org; email@example.com
Introduction: The aim of this work was to optimize the formulation composition of DanHong injection and to study the disturbance of microscopic components of cerebral ischemia in amino acid metabolites and metabolic pathways. The subtle relationship among these three substances and the influence of metabolic pathways were also studied.
Methods: In this study, the central composite design (CCD) matrix and response surface methodology (RSM) were used to design the experiments and to evaluate the interactive effects of three substances. Targeted metabolomics was used to detect the amino acid variation in CCD sets.
Results: Response surfaces were generated, and the formulation was optimized by superimposing the contour plots. It was found that the optimum values of the responses could be obtained at an SAB concentration (x1) of 8–9 mg/kg, a TSN concentration (x2) of 14–16 mg/kg, and an HSYA yellow A concentration (x3) of 6 mg/kg. Statistical analysis showed that the three independent variables had significant effects (p < 0.05) on the responses. A total of 22 experimental runs were performed, and the kinetic data were analyzed using a second-order polynomial. Model algorithm calculation indicated that glutamic acid, serine, leucine, glycine, and valine had a very close correlation with the active ingredients. Methionine, aspartic acid, asparagine, glutamic acid, and valine were important for distinguishing different groups, and they were identified as potential biomarkers. Cluster analysis and pathway analysis indicated that the valine, leucine, and isoleucine degradation (VLI degradation) pathway was the major metabolic pathway. Arginine and proline metabolites were most frequently detected, and they were closely associated with other networks according to the network analysis results. VLI degradation pathway and arginine and proline metabolism pathway had a significant influence on cerebral ischemia.
Discussion: The integration of CCD and metabolomics may be an effective strategy for optimizing the formulation composition and identifying the mechanism of action of traditional chinese medicine.
Keywords: amino acid metabolomics, central composite design, metabolic pathways, cerebral ischemia, DanHong injection, HPLC-FLD test, traditional Chinese medicine
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