Kang Sun1, Chaonan Su1, Wenjing Li1, Zhao Gong1, Chunjie Sha1, Rongxia Liu2. 1. School of Pharmacy, Key Laboratory of Molecular Pharmacology and Drug Evaluation (Yantai University), Ministry of Education, Collaborative Innovation Center of Advanced Drug Delivery System and Biotech Drugs in Universities of Shandong, Yantai University, Yantai 264005, China. 2. School of Pharmacy, Key Laboratory of Molecular Pharmacology and Drug Evaluation (Yantai University), Ministry of Education, Collaborative Innovation Center of Advanced Drug Delivery System and Biotech Drugs in Universities of Shandong, Yantai University, Yantai 264005, China. Electronic address: liurongxia@ytu.edu.cn.
Abstract
BACKGROUND: Quality control, key for the clinical application of traditional Chinese medicines (TCMs), should be connected to the authentication and efficacy of TCMs. The heartwood of Dalbergia odorifera has been widely used to treat inflammation-related diseases. However, in the Chinese pharmacopeia, only the total volatile oil, which does not sufficiently reflect the clinical efficacy, is used as a quality control indicator. PURPOSE: Establishing a "phytochemical-specificity-effectiveness-Q-marker" analytical strategy to improve the quality control of D. odorifera. METHODS: Combined with biosynthetic pathway analysis, phytochemical compositions identified by UHPLC-Q-Orbitrap HRMS were used to build substantial phytochemical groups and further discover specific Q-markers. Then, lipopolysaccharide-stimulated RAW 264.7 cells were used to screen effective anti-inflammatory ingredients. Finally, a UHPLC-HRMS method was developed and validated to quantify the selected Q-markers in D. odorifera samples. RESULTS: Along the constructed biosynthetic pathways, 93 phytochemical components were identified in D. odorifera, including 7 chalcones, 13 flavanones, 21 isoflavones, 21 isoflavanones, 3 flavonols, 19 neoflavones, etc. Among them, 31 compounds representing these 6 categories were further evaluated for their anti-inflammatory activities. It revealed that the extract of D. odorifera and nine flavonoids in the noncytotoxic range could alleviated lipopolysaccharide-stimulated inflammation in RAW 264.7 cells by decreasing the production of proinflammatory mediators such as nitric oxide and interleukin-6. Notably, neoflavones, as species-specific components, exhibited superior anti-inflammatory activities among the representative compounds. Finally, 12 Q-markers (butin, liquiritigenin, eriodictyol, melanettin, naringenin, butein, genistein, 4'-hydroxy-4-methoxydalbergione, isoliquiritigenin, 2,4-dihydroxy-5-methoxybenzophenone, medicarpin, and pinocembrin), which reflect specificity and effectiveness, were successfully quantified in 10 batches of samples from different origins. The origins and consistency of D. odorifera could be efficiently discriminated by hierarchical cluster analysis (HCA). CONCLUSION: The analysis strategy that combines phytochemical analysis with anti-inflammatory screening clarified the therapeutic material basis and discovered Q-markers, which possibly offers a more comprehensive quality assessment of D. odorifera.
BACKGROUND: Quality control, key for the clinical application of traditional Chinese medicines (TCMs), should be connected to the authentication and efficacy of TCMs. The heartwood of Dalbergia odorifera has been widely used to treat inflammation-related diseases. However, in the Chinese pharmacopeia, only the total volatile oil, which does not sufficiently reflect the clinical efficacy, is used as a quality control indicator. PURPOSE: Establishing a "phytochemical-specificity-effectiveness-Q-marker" analytical strategy to improve the quality control of D. odorifera. METHODS: Combined with biosynthetic pathway analysis, phytochemical compositions identified by UHPLC-Q-Orbitrap HRMS were used to build substantial phytochemical groups and further discover specific Q-markers. Then, lipopolysaccharide-stimulated RAW 264.7 cells were used to screen effective anti-inflammatory ingredients. Finally, a UHPLC-HRMS method was developed and validated to quantify the selected Q-markers in D. odorifera samples. RESULTS: Along the constructed biosynthetic pathways, 93 phytochemical components were identified in D. odorifera, including 7 chalcones, 13 flavanones, 21 isoflavones, 21 isoflavanones, 3 flavonols, 19 neoflavones, etc. Among them, 31 compounds representing these 6 categories were further evaluated for their anti-inflammatory activities. It revealed that the extract of D. odorifera and nine flavonoids in the noncytotoxic range could alleviated lipopolysaccharide-stimulated inflammation in RAW 264.7 cells by decreasing the production of proinflammatory mediators such as nitric oxide and interleukin-6. Notably, neoflavones, as species-specific components, exhibited superior anti-inflammatory activities among the representative compounds. Finally, 12 Q-markers (butin, liquiritigenin, eriodictyol, melanettin, naringenin, butein, genistein, 4'-hydroxy-4-methoxydalbergione, isoliquiritigenin, 2,4-dihydroxy-5-methoxybenzophenone, medicarpin, and pinocembrin), which reflect specificity and effectiveness, were successfully quantified in 10 batches of samples from different origins. The origins and consistency of D. odorifera could be efficiently discriminated by hierarchical cluster analysis (HCA). CONCLUSION: The analysis strategy that combines phytochemical analysis with anti-inflammatory screening clarified the therapeutic material basis and discovered Q-markers, which possibly offers a more comprehensive quality assessment of D. odorifera.