Establishment of High Performance Liquid Chromatographic Fingerprints and Identification of Chemical Constituents in Benchmark Samples of Lianpo Decoction

doi:10.19894/j.issn.1000-0518.230351

Chinese Journal of Applied Chemistry ›› 2024, Vol. 41 ›› Issue (6): 813-829.DOI: 10.19894/j.issn.1000-0518.230351

• Full Papers • Previous Articles Next Articles

Establishment of High Performance Liquid Chromatographic Fingerprints and Identification of Chemical Constituents in Benchmark Samples of Lianpo Decoction

Jie WANG, Shu-Hang WANG, Shao-Yan ZHOU, Xiao-Yun LIANG, Ke-Jin XU()

Changchun University of Traditional Chinese Medicine，Changchun 130117，China

Received:2023-11-07 Accepted:2024-02-01 Published:2024-06-01 Online:2024-07-09
Contact: Ke-Jin XU
About author:xukj@ccucm.edu.cn
Supported by:
Jilin Province Innovation Capacity Building Project(2021C002);Scientific Research Project of Jilin Provincial Department of Education(JJKH20241093KJ);Construction Project of Reserve Bank of Classical Famous Formulas for Prevention and Control of Major Epidemics （［2021］ No.11）

Abstract

Abstract:

High performance liquid chromatography （HPLC） technique was used to establish the fingerprints of the benchmark samples of Lianpo Decoction （LPD）. The experiment was performed on a Welch Ultimate^?XB-C18 （250 mm×4.6 mm， 5 μm） column with methanol -0.1% phosphoric acid solution as the mobile phase in a gradient elution with the detection wavelength of 254 nm， the column temperature of 30 ℃， the volume flow rate of 1.0 mL/min， and the injection volume of 10 μL. The quality of different batches of LPD was evaluated by similarity evaluation， cluster analysis （CA）， principal component analysis （PCA） and orthogonal partial least squares-discriminant analysis （OPLS-DA）. Ultra performance liquid chromatography-quadrupole-electrostatic field orbitrap high resolution mass spectrometry （UPLC-Q-Orbitrap HRMS） was applied to identify the chemical constituents in LPD. The results showed that the similarity between the fingerprints of the benchmark samples of 15 batches of LPD and the control fingerprints was higher than 0.9， and the methodological validation of the HPLC fingerprints of the benchmark samples of LPD was good. Twenty-three common peaks were identified， and eight components were recognized， which were geniposide at peak 3， epiberine at peak 7， coptis hydrochloride at peak 8， berberine hydrochloride at peak 11， palmatine hydrochloride at peak 12， genistein at peak 19， honokiol at peak 21， magnolol at peak 22， respectively. The 15 batches of benchmark samples were classified into three categories by two chemical pattern recognition methods， cluster analysis and principal component analysis， and the results corroborated each other. Principal components 1 to 4 were the main factors affecting their quality evaluation， and a total of 12 differential markers were identified by OPLS-DA. Ninety-one compounds were identified in LPD， which mainly included cyclic enol ether terpenes， organic acids， flavonoid glycosides， flavonoids and isoflavonoids， alkaloids， lignans and amino acids. The HPLC fingerprints of the baseline samples of LPD were simple， stable and reproducible， and combined with the mass spectrometry method， it can provide a reference for the subsequent formulation development and quality control studies.

Key words: Lianpo decoction, Cluster analysis, High performance liquid chromatography fingerprinting, UPLC-Q-Orbitrap HRMS, Principal component analysis, Orthogonal partial least squares-discriminant analysis

CLC Number:

O657

Jie WANG, Shu-Hang WANG, Shao-Yan ZHOU, Xiao-Yun LIANG, Ke-Jin XU. Establishment of High Performance Liquid Chromatographic Fingerprints and Identification of Chemical Constituents in Benchmark Samples of Lianpo Decoction[J]. Chinese Journal of Applied Chemistry, 2024, 41(6): 813-829.

Figures/Tables 13

References 42

1	王曦宇. 连朴饮加减联合四联疗法治疗幽门螺杆菌相关性胃炎脾胃湿热证的临床研究［J］. 中国医药指南， 2019， 17（1）： 153-154.
	WANG X Y. Clinical study on the treatment of Helicobacter pylori-associated gastritis with damp-heat syndrome of spleen and stomach by combination of Lian Pu Drink and quadruple therapy［J］. Guide Chin Med， 2019， 17（1）： 153-154.
2	何学梅. 王氏连朴饮加味治疗脾胃湿热型幽门螺杆菌相关慢性胃炎30例［J］. 浙江中医杂志， 2019， 54（12）： 892.
	HE X M. Treatment of Helicobacter pylori-associated chronic gastritis with damp-heat in spleen and stomach by adding flavor of Wang's Lianpu Drink in 30 cases［J］. Zhejiang J Tradit Chin Med， 2019， 54（12）： 892.
3	褚璨灿，师为人，陈云志，等. 连朴饮的临床应用与实验研究进展［J］. 中华中医药学刊， 2018， 36（10）： 2478-2480.
	CHU C C， SHI W R， CHEN Y Z， et al. Progress of clinical application and experimental research on Lianpuo drink［J］. Chin J Tradit Chin Med， 2018， 36（10）： 2478-2480.
4	王彩萍，张科防，苗慧霞，等. 幽门螺杆菌相关性胃炎脾胃湿热证连朴饮加减联合四联疗法治疗临床效果分析［J］. 临床医药文献电子杂志， 2019， 6（86）： 8-9.
	WANG C P， ZHANG K F， MIAO H X， et al. Clinical effect analysis of Helicobacter pylori-associated gastritis with damp-heat syndrome of spleen and stomach combined with Lianpu Drink and quadruple therapy［J］. Electronic J Clin Med Literature， 2019， 6（86）： 8-9.
5	孟金金. 黄连苦寒成分体内代谢过程对药性的影响研究［J］. 抗感染药学， 2017， 14（2）： 256-258.
	MENG J J. Studies on the effects of in vivo metabolic processes of bitter and cold components of Coptis chinensis on the medicinal properties of the drug［J］. Anti-Infection Pharm， 2017， 14（2）： 256-258.
6	杨红兵，杨晓琴，陈学昆，等. 厚朴不同部位的体外抑菌试验研究［J］. 湖北中医药大学学报， 2016， 18（1）： 40-43.
	YANG H B， YANG X Q， CHEN X K， et al. In vitro bacteriostatic test study on different parts of Huperzia serrata［J］. J Hubei Univ Chin Med， 2016， 18（1）： 40-43.
7	王志强，宓伟，刘现兵，等. 厚朴体外抑菌作用研究［J］. 时珍国医国药， 2007（11）： 2763.
	WANG Z Q， MI W， LIU X B， et al. In vitro bacteriostatic test study on different parts of Huperzia serrata.［J］. Lishizhen Med Mater Med Res， 2007（11）： 2763.
8	伍晓丽，陈义嘉，王钰，等. 黄连研究进展综述［J］. 安徽农学通报， 2023， 29（7）： 37-41.
	WU X L， CHEN Y J， WANG Y， et al. Synthesis of the progress of research on Coptis chinensis［J］. Anhui Agric Sci Bull， 2023， 29（7）： 37-41.
9	李家奇，薛珍珍，杨滨. 不同产地和树龄厚朴样本姜炙前后化学成分的定性定量分析［J］. 中国中药杂志， 2023， 48（9）： 2435-2454.
	LI J Q， XUE Z Z， YANG B. Qualitative and quantitative analysis of chemical constituents of Houpao samples of different origins and ages before and after ginger-roasting［J］. Chin J Chin Mater Med， 2023， 48（9）： 2435-2454.
10	穆成林，周欣，卢焘韬，等. 基于HPLC与化学计量学方法的姜黄连饮片指纹图谱研究［J］. 中药材， 2019， 42（9）： 2086-2090.
	MU C L， ZHOU X， LU T T， et al. Fingerprinting study of Jianghuanglian drinking tablets based on HPLC and chemometric methods［J］. Chin Med Mat， 2019， 42（9）： 2086-2090.
11	黄玲. 黄连化学成分及有效成分药理活性的研究进展［J］. 中西医结合心血管病电子杂志， 2020， 8（17）： 136-137.
	HUANG L. Progress in the study of chemical composition and pharmacological activity of active ingredients of Rhizoma Coptidis［J］. Cardiovascular Dis J Integr Tradit Chin West Med， 2020， 8（17）： 136-137.
12	张景，冯亭亭，张明柱. 淡豆豉UPLC指纹图谱［J］. 中成药， 2017， 39（7）： 1531-1533.
	ZHANG J， FENG T T， ZHANG M Z. UPLC fingerprint of tempeh［J］. Chin Traditi Pat Med， 2017， 39（7）： 1531-1533.
13	雷磊，王玉，霍志鹏，等. LCMS-IT-TOF分析栀子炒焦前后化学成分的变化［J］. 中国实验方剂学杂志， 2019， 25（17）： 88-97.
	LEI L， WANG Y， HUO Z P， et al. LCMS-IT-TOF analysis of changes in chemical composition of Gardenia jasminoides before and after frying and scorching［J］. Chin J Exp Tradit Med Formulae， 2019， 25（17）： 88-97.
14	马莎莎. 石菖蒲的化学指纹图谱及易混淆品化学成分比较研究［D］. 昆明：昆明理工大学， 2018.
	MA S S. Chemical fingerprinting of Acorus calamus and comparative study on the chemical constituents of the confusibles［D］. Kunming： Kunming University of Science and Technology， 2018.
15	王中华，郭庆梅，周凤琴. 芦根化学成分、药理作用及开发利用研究进展［J］. 辽宁中医药大学学报， 2014， 16（12）： 81-83.
	WANG Z H， GUO Q M， ZHOU F Q. Advances in chemical composition， pharmacological effects and development and utilization of rutabaga root［J］. J Liaoning UnivTradit Chin Med， 2014， 16（12）： 81-83.
16	左军，牟景光，胡晓阳. 半夏化学成分及现代药理作用研究进展［J］. 辽宁中医药大学学报， 2019， 21（9）： 26-29.
	ZUO J， MOU J G， HU X Y. Progress in the study of chemical constituents and modern pharmacological effects of Pinellia ternata［J］. J Liaoning Univ Tradit Chin Med， 2019， 21（9）： 26-29.
17	汤书婉，李新亮，马莉，等. 基于HPLC指纹图谱和LC-Q-TOF/MS的加味黄芪桂枝五物汤化学成分研究［J］. 中草药， 2023， 54（3）： 711-721.
	TANG S G， LI X L， MA L， et al. Study on the chemical constituents of Flavored Astragalus and Gui Zhi Wu Wu Wu Tang based on HPLC fingerprints and LC-Q-TOF/MS［J］. Chin Tradit Herbal Drugs， 2023， 54（3）： 711-721.
18	张维方，张强，贾豪，等. 经典名方一贯煎HPLC指纹图谱及化学模式识别研究［J］. 药物分析杂志， 2022， 42（12）： 2169-2178.
	ZHANG W F， ZHANG Q， JIA H， et al. HPLC fingerprinting and chemical pattern recognition study of the classical famous formula consistently decoction［J］. Chin J Pharm Anal， 2022， 42（12）： 2169-2178.
19	薛晓霞，靳如娜，王学圆，等. 经典名方二冬汤基准样品的指标成分含量测定及量值传递规律探索［J］. 中国实验方剂学杂志， 2022， 28（11）： 1-7.
	XUE X X， JIN R N， WANG X Y， et al. Determination of indicator components in benchmark samples of the classic formula Erdong Tang and exploration of the law of quantitative value transmission［J］. Chin J Exp Tradit Med Formulae， 2022， 28（11）： 1-7.
20	国家中医药管理局、卫生部关于印发医疗机构中药煎药室管理规范的通知（国中医药发〔2009〕3号）［J］. 2009（6）： 29-31.
	State Administration of Traditional Chinese Medicine， Ministry of Health on the issuance of medical institutions of Chinese medicine decoction room management norms notice （State Administration of Traditional Chinese Medicine issued ［2009］ No. 3）［J］. 2009（6）： 29-31.
21	崔美娜，钟凌云，兰泽伦，等. 基于UPLC-Q-TOF-MS/MS分析多物料多流程炮制对半夏化学成分的影响［J］. 中草药， 2021， 52（24）： 7428-7437.
	CUI M N， ZHONG L Y， LAN Z L， et al. UPLC-Q-TOF-MS/MS-based analysis of the effects of multi-material and multi-process concoctions on the chemical composition of Pinellia ternata［J］. Chin Tradit Herbal Drugs， 2021， 52（24）： 7428-7437.
22	聂黎行，王馨平，黄烈岩，等. 板蓝根化学成分信息库的构建［J］. 中国药学杂志， 2022， 57（6）： 428-452.
	NIE L X， WANG X P， HUANG L Y， et al. Construction of an information base of chemical components of Panax quinquefolium［J］. Chin Pharm J， 2022， 57（6）： 428-452.
23	CHEN Q C， ZHANG W Y， YOUN U， et al. Iridoid glycosides from Gardeniae Fructus for treatment of ankle sprain［J］. Phytochemistry， 2009， 70（6）： 779-784.
24	HAN Y， WEN J， ZHOU T， et al. Chemical fingerprinting of Gardenia jasminoides Ellis by HPLC-DAD-ESI-MS combined with chemometrics methods［J］. Food Chem， 2015， 188： 648-657.
25	WANG L， LIU S， ZHANG X， et al. A strategy for identification and structural characterization of compounds from Gardenia jasminoides by integrating macroporous resin column chromatography and liquid chromatography-tandem mass spectrometry combined with ion-mobility spectrometry［J］. J Chromatogr， 2016， 1452： 47-57.
26	田世民，谢锦，尚强，等. 基于UPLC-Q-Orbitrap HRMS和GC-MS技术的抗病毒颗粒化学成分分析［J］. 中国医院药学杂志， 2023， 43（2）： 134-144.
	TIAN S M， XIE J， SHANG Q， et al. Chemical composition analysis of antiviral particles based on UPLC-Q-Orbitrap HRMS and GC-MS techniques［J］. Chin J Hosp Pharm， 2023， 43（2）： 134-144.
27	孙淑玲. 中药芦根的药理作用及临床应用［J］. 中西医结合心血管病电子杂志， 2016， 4（36）： 165.
	SUN S L. Pharmacological actions and clinical applications of the Chinese medicine rehmannia glutinosa［J］. Cardiovascular Dis J Integr Tradit Chin West Med， 2016， 4（36）： 165.
28	陈梦倩，王允吉，冯芳. 基于UPLC-Q-Exactive Orbitrap-MS的栀子甘草豉汤化学成分分析［J］. 广州化工， 2021， 49（8）： 97-103.
	CHEN M Q， WANG Y J， FENG F. Analysis of the chemical constituents of Gardenia Glycyrrhiza Glutinosa and Blac Bean Soup based on UPLC-Q-Exactive Orbitrap-MS［J］. Guangzhou Chem Ind， 2021， 49（8）： 97-103.
29	王永丽，黄广建，刘从进，等. UHPLC-Q-Exactive Orbitrap HRMS分析黄连解毒汤的化学成分及大鼠组织分布［J］. 中草药， 2022， 53（22）： 6985-7000.
	WANG Y L， HUANG G J， LIU C J， et al. Analysis of the chemical constituents and rat tissue distribution of Rhizoma Coptidis Toxin Relieving Tang by UHPLC-Q-Exactive Orbitrap HRMS［J］. Chin Tradit Herbal Drugs， 2022， 53（22）： 6985-7000.
30	张烨，邓琦，魏敏，等. 黄连花薹化学成分的UPLC-Q-Orbitrap HRMS鉴定［J］. 中国实验方剂学杂志， 2021， 27（15）： 91-99.
	ZHANG Y， DENG Q， WEI M， et al. UPLC-Q-Orbitrap HRMS for the identification of the chemical constituents of Rhizoma Coptidis Carex［J］. Chin J Exp Tradit Med Formulae， 2021， 27（15）： 91-99.
31	胥爱丽，肖观林，毕晓黎，等. 厚朴温中汤化学成分快速分析［J］. 中药新药与临床药理， 2021， 32（2）： 252-258.
	XU A L， XIAO G L， BI X L， et al. Rapid analysis of the chemical composition of Houpu Wenzhong Tang［J］. Tradit Chin Drugs Clin Remed Pharmacol， 2021， 32（2）： 252-258.
32	张国升，李前荣，尹浩，等. 气相色谱-飞行时间质谱法快速测定和鉴定芦根中阿魏酸的含量与结构［J］. 中草药， 2005（3）： 333-335.
	ZHANG G S， LI Q R， YIN H， et al. Rapid determination and structural characterization of ferulic acid in rehmanniaglutinosa by gas chromatography-time-of-flight mass spectrometry［J］. Chin Tradit Herbal Drugs， 2005（3）： 333-335.
33	赵权，张优，陈影，等. HPLC-VWD-Q-TOF-MS/MS法定性与定量分析枳实栀子豉汤成分［J］. 中成药， 2021， 43（11）： 3067-3075.
	ZHAO Q， ZHANG Y， CHEN Y， et al. Qualitative and quantitative analysis of the components of Citrus aurantium jasminoides and black beans soup by HPLC-VWD-Q-TOF-MS/MS［J］. Chin Tradit Herbal Drugs， 2021， 43（11）： 3067-3075.
34	王月红，王磊，张洪兵，等. 基于HPLC-Q/TOF-MS的六经头痛片血中移行成分研究［J］. 中草药， 2017， 48（20）： 4151-4156.
	WANG Y H， WANG L， ZHANG H B， et al. HPLC-Q/TOF-MS-based study of migratory componentsin the blood of Hexagram Headache Tablet［J］. Chin Tradit Herbal Drugs， 2017， 48（20）： 4151-4156.
35	石坚宏，姬丽婷，骆启晗，等. 石菖蒲化学成分、药理作用及质量标志物预测分析研究进展［J］. 中成药， 2021， 43（5）： 1286-1290.
	SHI J H， JI L T， LUO Q H， et al. Progress in the study of chemical composition， pharmacological effects and predictive analysis of quality markers of Acorus calamus［J］. Chin Tradit Pat Med， 2021， 43（5）： 1286-1290.
36	马燕玲，王一名，初坤，等. 超高效液相色谱串联质谱法测定葡萄酒中酚酸和酚醛类化合物［J］. 化学试剂， 2023， 45（2）： 141-147.
	MA Y L， WANG Y Y， CHU K， et al. Determination of phenolic acids and phenolic aldehydes in wine by ultra performance liquid chromatography tandem mass spectrometry［J］. Chem Reag， 2023， 45（2）： 141-147.
37	LEE E M， PARK S J， LEE J， et al. Highly geographical specificity of metabolomic traits among Korean domestic soybeans （Glycine max）［J］. Food Res Int， 2019， 120： 12-18.
38	杨鹤年，吴宿慧，李寒冰，等. 石菖蒲的研究进展及质量标志物预测分析［J］. 中国新药杂志， 2021， 30（13）： 1213-1219.
	YANG H N， WU S H， LI H B， et al. Research progress of Acorus calamus and analysis of quality markers prediction［J］. Chin New Drugs J， 2021， 30（13）： 1213-1219.
39	郝艺铭，霍金海，王涛，等. UPLC-Q-TOF/MS技术分析黄连中非生物碱类成分［J］. 中药材， 2020， 43（2）： 354-358.
	HAO Y M， HUO J H， WANG T， et al. Analysis of non-alkaloids in rhizoma coptidis by UPLC-Q-TOF/MS technique［J］. Chin Med Mat， 2020， 43（2）： 354-358.
40	梁颖，许文佳，符策奕，等. HPLC-MS/MS法同时测定枫蓼肠胃康合剂、胶囊中10种成分［J］. 中成药， 2019， 41（5）： 983-987.
	LIANG Y， XU W J， FU C Y， et al. Simultaneous determination of 10 components in Feng Polygonum Enterogastricum Combination and Capsules by HPLC-MS/MS method［J］. Chin Tradit Pat Med， 2019， 41（5）： 983-987.
41	王彬，裴科，汪小莉，等. 气相色谱-质谱联用测定石菖蒲中26种挥发性成分的研究［J］. 时珍国医国药， 2015， 26（11）： 2627-2630.
	WANG B， PEI K， WANG X L， et al. Determination of 26 volatile components in Acorus calamus by gas chromatography-mass spectrometry［J］. Lishizhen Med Mater Med， 2015， 26（11）： 2627-2630.
42	邰佳，邹俊波，史亚军，等. GC-MS分析水蒸气蒸馏法提取石菖蒲挥发油过程中油水分配规律［J］. 中草药， 2020， 51（1）： 59-66.
	TAI J， ZOU J B， SHI Y J， et al. GC-MS analysis of oil-water partitioning in the extraction of volatile oil from Acorus calamus by water vapor distillation［J］. Chin Tradit Herbal Drugs， 2020， 51（1）： 59-66.

No.	S1	S2	S2	S4	S5	S6	S7	S8	S9	S10	S11	S12	S13	S14	S15	R
S1	1.000	0.971	0.982	0.999	0.950	0.934	0.993	0.995	0.975	0.997	0.917	0.918	0.926	0.998	0.971	0.981
S2	0.971	1.000	0.998	0.970	0.995	0.990	0.993	0.989	0.999	0.986	0.957	0.957	0.962	0.974	0.999	0.999
S3	0.982	0.998	1.000	0.980	0.991	0.984	0.997	0.996	0.999	0.992	0.940	0.940	0.945	0.984	0.998	0.999
S4	0.999	0.970	0.980	1.000	0.947	0.931	0.992	0.993	0.973	0.997	0.917	0.919	0.907	0.999	0.970	0.979
S5	0.950	0.995	0.991	0.947	1.000	0.998	0.980	0.976	0.995	0.968	0.972	0.971	0.974	0.954	0.995	0.992
S6	0.934	0.990	0.984	0.931	0.998	1.000	0.969	0.964	0.989	0.955	0.980	0.979	0.981	0.938	0.990	0.985
S7	0.993	0.993	0.997	0.992	0.980	0.969	1.000	0.999	0.994	0.998	0.919	0.920	0.926	0.994	0.992	0.997
S8	0.995	0.989	0.996	0.993	0.976	0.964	0.999	1.000	0.992	0.999	0.909	0.910	0.916	0.996	0.989	0.995
S9	0.975	0.999	0.999	0.973	0.995	0.989	0.994	0.992	1.000	0.988	0.951	0.951	0.955	0.977	0.999	0.999
S10	0.997	0.986	0.992	0.997	0.968	0.955	0.998	0.999	0.988	1.000	0.918	0.919	0.916	0.998	0.985	0.992
S11	0.917	0.957	0.940	0.917	0.972	0.980	0.919	0.909	0.951	0.918	1.000	0.998	0.999	0.912	0.958	0.946
S12	0.918	0.957	0.940	0.919	0.971	0.979	0.920	0.910	0.951	0.919	0.998	1.000	0.999	0.913	0.958	0.947
S13	0.926	0.962	0.945	0.907	0.974	0.981	0.926	0.916	0.955	0.916	0.999	0.999	1.000	0.911	0.963	0.952
S14	0.998	0.974	0.984	0.999	0.954	0.938	0.994	0.996	0.977	0.998	0.912	0.913	0.911	1.000	0.973	0.983
S15	0.971	0.999	0.998	0.970	0.995	0.990	0.992	0.989	0.999	0.985	0.958	0.958	0.963	0.973	1.000	0.999
R	0.981	0.999	0.999	0.979	0.992	0.985	0.997	0.995	0.999	0.992	0.946	0.947	0.952	0.983	0.999	1.000

No.	S1	S2	S2	S4	S5	S6	S7	S8	S9	S10	S11	S12	S13	S14	S15	R
S1	1.000	0.971	0.982	0.999	0.950	0.934	0.993	0.995	0.975	0.997	0.917	0.918	0.926	0.998	0.971	0.981
S2	0.971	1.000	0.998	0.970	0.995	0.990	0.993	0.989	0.999	0.986	0.957	0.957	0.962	0.974	0.999	0.999
S3	0.982	0.998	1.000	0.980	0.991	0.984	0.997	0.996	0.999	0.992	0.940	0.940	0.945	0.984	0.998	0.999
S4	0.999	0.970	0.980	1.000	0.947	0.931	0.992	0.993	0.973	0.997	0.917	0.919	0.907	0.999	0.970	0.979
S5	0.950	0.995	0.991	0.947	1.000	0.998	0.980	0.976	0.995	0.968	0.972	0.971	0.974	0.954	0.995	0.992
S6	0.934	0.990	0.984	0.931	0.998	1.000	0.969	0.964	0.989	0.955	0.980	0.979	0.981	0.938	0.990	0.985
S7	0.993	0.993	0.997	0.992	0.980	0.969	1.000	0.999	0.994	0.998	0.919	0.920	0.926	0.994	0.992	0.997
S8	0.995	0.989	0.996	0.993	0.976	0.964	0.999	1.000	0.992	0.999	0.909	0.910	0.916	0.996	0.989	0.995
S9	0.975	0.999	0.999	0.973	0.995	0.989	0.994	0.992	1.000	0.988	0.951	0.951	0.955	0.977	0.999	0.999
S10	0.997	0.986	0.992	0.997	0.968	0.955	0.998	0.999	0.988	1.000	0.918	0.919	0.916	0.998	0.985	0.992
S11	0.917	0.957	0.940	0.917	0.972	0.980	0.919	0.909	0.951	0.918	1.000	0.998	0.999	0.912	0.958	0.946
S12	0.918	0.957	0.940	0.919	0.971	0.979	0.920	0.910	0.951	0.919	0.998	1.000	0.999	0.913	0.958	0.947
S13	0.926	0.962	0.945	0.907	0.974	0.981	0.926	0.916	0.955	0.916	0.999	0.999	1.000	0.911	0.963	0.952
S14	0.998	0.974	0.984	0.999	0.954	0.938	0.994	0.996	0.977	0.998	0.912	0.913	0.911	1.000	0.973	0.983
S15	0.971	0.999	0.998	0.970	0.995	0.990	0.992	0.989	0.999	0.985	0.958	0.958	0.963	0.973	1.000	0.999
R	0.981	0.999	0.999	0.979	0.992	0.985	0.997	0.995	0.999	0.992	0.946	0.947	0.952	0.983	0.999	1.000

Principal component	Eigenvalue	Variance contribution/%	Cumulative variance contribution/%
1	8.57	37.26	37.26
2	8.10	35.20	72.45
3	3.66	15.91	88.36
4	1.12	4.88	93.24

Principal component	Eigenvalue	Variance contribution/%	Cumulative variance contribution/%
1	8.57	37.26	37.26
2	8.10	35.20	72.45
3	3.66	15.91	88.36
4	1.12	4.88	93.24

Peak No.	Principal component 1	Principal component 2	Principal component 3	Principal component 4
1	-0.612	0.672	0.345	0.06
2	-0.48	0.513	0.663	0.206
3	-0.633	0.65	0.33	0.006
4	0.859	-0.306	-0.302	-0.054
5	0.465	-0.721	0.34	0.358
6	0.221	-0.811	0.283	0.243
7	0.847	0.408	0.265	-0.192
8	0.812	0.411	0.359	-0.174
9	0.583	-0.696	0.364	0.145
10	0.839	0.4	0.261	-0.21
11	0.83	0.382	0.331	-0.201
12	0.866	0.38	0.214	-0.145
13	0.585	0.602	-0.294	0.755
14	0.197	0.945	-0.088	0.226
15	-0.056	0.913	0.047	0.303
16	-0.172	0.867	-0.43	-0.082
17	0.565	0.74	-0.26	0.229
18	0.741	0.518	-0.229	0.259
19	0.847	0.048	-0.374	0.122
20	-0.535	0.724	-0.321	-0.07
21	0.464	0.022	0.766	-0.084
22	-0.351	0.411	0.516	-0.423
23	-0.278	0.252	0.808	0.392

Establishment of High Performance Liquid Chromatographic Fingerprints and Identification of Chemical Constituents in Benchmark Samples of Lianpo Decoction

RichHTML

PDF

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 13

References 42

Related Articles 4

Recommended Articles

Metrics

Comments

No.	F₁	F₂	F₃	F₄	F	Rank
S1	-4.208	-0.654	-1.513	-0.682	-2.224	14
S2	-0.022	0.004	3.447	-0.313	0.566	5
S3	-0.764	0.69	0.628	-2.396	-0.063	7
S4	-3.444	-0.92	0.621	2.615	-1.482	13
S5	1.822	4.451	-1.166	-0.228	2.196	2
S6	4.293	5.025	-2.148	0.568	3.274	1
S7	-2.243	-0.965	-0.606	-0.437	-1.387	12
S8	-1.568	1.017	-1.774	0.182	-0.538	9
S9	1.285	3.426	0.883	0.447	1.980	3
S10	-2.169	0.161	1.15	0.757	-0.571	11
S11	2.83	-3.984	-0.834	-0.543	-0.541	10
S12	3.261	-4.363	-0.723	-0.176	-0.473	8
S13	4.605	-3.949	0.084	0.827	0.411	6
S14	-3.787	-1.023	-2.309	-0.254	-2.309	15
S15	0.109	1.084	4.261	-0.366	1.162	4

No.	t_R /min	Identified constituent	Molecular formula	Theoretical mass	Experimental mass	10⁶ Error	Ionic form	Source
1	0.78	Choline^［21］	C₅H₁₃NO	103.099 7	103.099 8	1.01	P	E
2	0.798	DL-Arginine^［22］	C₆H₁₄N₄O₂	174.111 7	174.111 3	-2.07	P	E
3	0.941	Gluconic acid^［9］	C₆H₁₂O₇	196.058 3	196.057 4	-4.75	P	A
4	0.942	Asparagine	C₄H₈N₂O₃	132.053 5	132.053 3	-1.73	P	G
5	1.04	Adenine^［21］	C₅H₅N₅	135.054 5	135.054 3	-1.16	P	E
6	1.088	Uracil^［21］	C₄H₄N₂O₂	112.027 3	112.027 3	0.27	P	E
7	1.159	Adenosine^［21］	C₁₀H₁₃N₅O₄	267.096 8	267.096 2	-2.27	P	E
8	1.162	2-Hydroxycinnamic acid^［9］	C₉H₈O₃	164.047 3	164.047 1	-1.61	P	A
9	1.21	L-Isoleucine^［21］	C₆H₁₃NO₂	131.094 6	131.094 4	-1.57	P	E
10	1.256	Guanosine^［21］	C₁₀H₁₃N₅O₅	283.091 7	283.090 9	-2.83	P	E
11	1.381	Thymine^［21］	C₅H₆N₂O₂	126.042 9	126.042 8	-1.07	P	E
12	1.886	Geniposidic acid^［23-25］	C₁₆H₂₂O₁₀	374.121 3	374.121 1	-0.62	N	D
13	2.543	2，4，5-Trimethoxybenzoic acid^［26］	C₁₀H₁₂O₅	212.068 5	212.068 0	-2.47	P	F
14	3.328	Coixol	C₈H₇NO₃	165.042 6	165.042 3	-1.83	P	G
15	3.53	Protocatechuic acid	C₇H₆O₄	154.026 6	154.026 3	-2.13	P	E
16	3.611	Maltol^［27］	C₆H₆O₃	126.031 7	126.031 6	-1.03	P	G
17	4.108	Hypocretin methyl ester^［25］	C₁₇H₂₄O₁₁	404.131 9	404.131 7	-0.53	N	D
18	4.131	Coumarin^［9］	C₉H₆O₂	146.036 8	146.036 4	-2.49	P	A
19	4.22	Anethole^［21］	C₁₀H₁₂O	148.088 8	148.088 6	-1.7	P	E
20	4.226	Neochlorogenic acid^［26］	C₁₆H₁₈O₉	354.095 1	354.094 7	-1.21	N	BDF
21	4.232	Jasmin G^［28］	C₁₆H₂₆O₈	346.162 8	346.161 8	-2.79	P	D
22	4.273	5-Hydroxyindole-3-acetic acid^［29］	C₁₀H₉NO₃	191.058 2	191.057 8	-2.31	P	B
23	4.606	Normorphine^［29］	C₁₆H₁₇NO₃	271.120 8	271.120 2	-2.5	P	B
24	4.618	Sinomenine^［9］	C₁₉H₂₃NO₄	329.162 7	329.161 9	-2.6	P	A
25	4.805	Jade leaf auriculosidic acid^［28］	C₂₁H₃₂O₁₀	444.199 6	444.199 4	-0.43	N	D
26	5.002	Salicylic acid^［29］	C₇H₆O₃	138.031 7	138.031 2	-3.32	P	BDF
27	5.029	3-Acetylmorphine^［30］	C₁₉H₂₁NO₄	327.147 1	327.146 1	-2.82	P	B
28	5.059	Ferulaldehyde	C₁₀H₁₀O₃	178.063 0	178.062 9	-0.7	P	G
29	5.128	Chlorogenic acid^［29］	C₁₆H₁₈O₉	354.095 1	354.094 8	-0.83	N	BD
30	5.142	Genipin 1-O-β-D-gentiobioside^［13］	C₂₃H₃₄O₁₅	550.189 8	550.189 5	-0.55	N	D
31	5.162	Ethylmorphine^［31］	C₁₉H₂₃NO₃	313.167 8	313.166 7	-3.48	P	A
32	5.295	Methyl chlorogenate^［30］	C₁₇H₂₀O₉	368.110 7	368.109 7	-2.95	P	BD
33	5.301	Methyl chlorogenate^［30］	C₁₇H₂₀O₉	368.110 7	368.110 3	-1.06	N	BD
34	5.573	6-Acetylmorphine	C₁₉H₂₁NO₄	327.147 1	327.146 0	-3.1	P	B
35	5.59	Geniposide^［13］	C₁₇H₂₄O₁₀	388.137 0	388.136 7	-0.64	N	D
36	5.596	Genipin^［13］	C₁₁H₁₄O₅	226.084 1	226.083 5	-2.99	N	D
37	5.599	Isoferulic acid^［32］	C₁₀H₁₀O₄	194.057 9	194.057 3	-3.12	P	G
38	5.7	6-Acetylcodeine^［31］	C₂₀H₂₃NO₄	341.162 7	341.161 6	-3.23	P	A
39	5.719	Saffronic acid^［28］	C₁₆H₂₆O₈	346.162 8	346.162 6	-0.48	N	D
40	5.769	Syringic acid^［9］	C₉H₁₀O₅	198.052 8	198.052 4	-2.37	N	A
41	5.79	Jasmin T^［28］	C₂₁H₃₄O₁₁	462.210 1	462.208 8	-2.82	P	D
42	5.962	4-Hydroxybenzaldehyde^［26］	C₇H₆O₂	122.036 8	122.036 7	-1.04	P	G
43	5.963	Caffeic acid^［33］	C₉H₈O₄	180.042 3	180.041 8	-2.34	N	CDA
44	5.976	Jasmin A^［28］	C₁₆H₂₆O₇	330.167 9	330.166 9	-2.99	P	D
45	6.046	Methyl chlorogenate^［30］	C₁₇H₂₀O₉	368.110 7	368.110 5	-0.61	N	BD
46	6.052	Daidzin^［34］	C₂₁H₂₀O₉	416.110 7	416.109 5	-3	P	C
47	6.156	Glycitin^［33］	C₂₂H₂₂O₁₀	446.121 3	446.120 3	-2.33	P	C
48	6.357	Erigerin L^［28］	C₂₇H₃₆O₁₂	552.220 7	552.220 5	-0.25	N	D
49	6.409	Rutin^［13］	C₂₇H₃₀O₁₆	610.153 4	610.153 3	-0.08	P	D
50	6.486	Lariciresinol 4-O-glucoside^［9］	C₂₆H₃₄O₁₁	522.210 1	522.209 9	-0.44	N	A
51	6.571	Demethyleneberberine^［29］	C₂₁H₂₂NO₄	352.115 8	352.114 7	-3.27	P	B
52	6.604	Ferulic acid^［32］	C₁₀H₁₀O₄	194.057 9	194.057 5	-2.17	P	G
53	6.648	Kaempferol 7-neohesperidoside^［35］	C₂₇H₃₀O₁₅	594.158 5	594.158 5	-0.01	N	F
54	6.694	Butyraldehyde	C₉H₁₀O₄	182.057 9	182.057 5	-2.18	P	G
55	6.737	6'-o-trans-Mustardoyl gardenia neoside^［28］	C₂₇H₃₂O₁₄	580.179 2	580.177 9	-2.29	P	D
56	6.807	Coptisine^［29］	C₁₉H₁₄NO₄	320.092 3	320.092 6	1.1	N	B
57	7.102	4-Coumaric acid^［36］	C₉H₈O₃	164.047 3	164.046 9	-2.73	P	A
58	7.136	6″-o-trans-Mustard acylkinetic acid gentiobioside^［28］	C₃₄H₄₄O₁₉	756.247 7	756.245 7	-2.59	N	D
59	7.218	4，5-Dicaffeoylquinic acid^［13］	C₂₅H₂₄O₁₂	516.126 8	516.126 4	-0.71	N	D
60	7.243	Jatrorrhizine^［30］	C₂₀H₁₉NO₄	337.131 4	337.130 0	-4.11	P	B
61	7.266	6″-O-Acetylsoyoside^［37］	C₂₃H₂₂O₁₀	458.121 3	458.119 8	-3.34	P	C
62	7.694	6'-o-trans-Mustard acyl kynephoside^［28］	C₂₈H₃₄O₁₄	594.194 9	594.193 2	-2.79	N	D
63	7.893	Berberine^［29］	C₂₀H₁₇NO₄	335.115 8	335.114 5	-3.7	P	B
64	8.297	Feruloyl tyramine^［38］	C₁₈H₁₉NO₄	313.131 4	313.130 4	-3.26	P	F
65	8.354	Daidzein^［33］	C₁₅H₁₀O₄	254.057 9	254.057 2	-2.89	N	C
66	8.519	Disinapoyl Hexoside^［39］	C₂₈H₃₂O₁₄	592.179 2	592.179 0	-0.4	N	B
67	8.56	2，4，5-Trimethoxybenzaldehyde^［26］	C₁₀H₁₂O₄	196.073 6	196.073 1	-2.46	P	F
68	8.611	Glycitein^［33］	C₁₆H₁₂O₅	284.068 5	284.067 6	-2.92	N	C
69	8.93	Quercetin^［40］	C₁₅H₁₀O₇	302.042 7	302.042 3	-1.03	N	D
70	9.153	Crocin^［23］	C₄₄H₆₄O₂₄	976.378 8	976.378 5	-0.23	N	D
71	9.314	Crocetin^［23］	C₂₀H₂₄O₄	328.167 5	328.166 5	-2.95	P	D
72	9.679	Isophorone^［23］	C₉H₁₄O	138.104 5	138.104 2	-2.11	P	D
73	9.682	Crocin Ⅱ^［23］	C₃₈H₅₄O₁₉	814.325 9	814.325 7	-0.25	N	D
74	9.694	Genistein^［33］	C₁₅H₁₀O₅	270.052 8	270.052 1	-2.75	P	C
75	10.32	Crocin 3^［23］	C₃₂H₄₄O₁₄	652.273 1	652.273 1	-0.08	N	D
76	10.675	Oxyberberine^［29］	C₂₀H₁₇NO₅	351.110 7	351.109 6	-3.13	P	B
77	10.849	（-）-Caryophyllene oxide^［41］	C₁₅H₂₄O	220.182 7	220.182 2	-2.42	P	F
78	10.877	Berberrubine^［29］	C₁₉H₁₅NO₄	340.118 5	340.117 5	-2.91	P	B
79	10.983	Sphingomyelin^［21］	C₁₈H₃₉NO₃	317.293 0	317.292 1	-2.91	P	E
80	11.041	Honokiol^［9］	C₁₈H₁₈O₂	266.131 0	266.129 0	-2.92	P	A
81	11.153	Medicarpin^［39］	C₁₆H₁₄O₄	270.089 2	270.088 4	-3.01	P	B
82	11.155	Prespatane^［42］	C₁₅H₂₄	204.187 8	204.187 3	-2.36	P	F
83	11.586	Crocetin^［21］	C₂₀H₂₄O₄	328.167 5	328.167 1	-1.1	N	D
84	12.185	Magnolol^［9］	C₁₈H₁₈O₂	266.130 7	266.129 9	-2.93	P	A
85	13.431	β-Asarone^［26］	C₁₂H₁₆O₃	208.109 9	208.109 4	-2.43	P	F
86	13.522	α-Linolenic acid^［21］	C₁₈H₃₀O₂	278.224 6	278.223 8	-2.79	P	E
87	14.352	Linoleoyl ethanolamide^［21］	C₂₀H₃₇NO₂	323.282 4	323.281 6	-2.65	P	E
88	16.333	Hexadecanamide^［21］	C₁₆H₃₃NO	255.256 2	255.255 3	-3.46	P	E
89	16.456	Ursolic acid^［33］	C₃₀H₄₈O₃	456.360 4	456.359 2	-2.47	P	D
90	16.989	Ceratodictyol^［21］	C₁₉H₃₈O₄	330.277 0	330.276 0	-3.03	P	E
91	18.422	Oleic acid^［21］	C₁₈H₃₄O₂	282.255 9	282.255 6	-1.11	N	FE

[1]	Ying-Xin GAO, Wei XU, Yan-Xu ZHANG, Ye-Chen WANG, Xue-Lian DONG. Evaluation of the Quality of Coptidis Rhizoma from Different Origins by the Combination of Grey Relational Analysis and Chromaticity Method [J]. Chinese Journal of Applied Chemistry, 2022, 39(6): 1000-1010.
[2]	DU Kang, ZHOU Heng-Wei, DING Ming-Ming, YE Feng, SHI Tong-Fei. Cluster Analysis of Correlation Between Rubber Carbon Black Filling and Yeoh Model Parameters [J]. Chinese Journal of Applied Chemistry, 2021, 38(6): 675-684.
[3]	FANG Xiaowei,ZHONG Tao,YAO Guocan,GAO Xiang,YANG Meiling,LI Hui,LE Zhanggao,ZHANG Xinglei. Comparison of Ambient Temperature and Thermal Surface Desorption Atmospheric Pressure Chemical Ionization Mass Spectra for the Pericarp of Navel Orange [J]. Chinese Journal of Applied Chemistry, 2015, 32(10): 1201-1207.
[4]	Xu Jingming, Song Chongli. FUZZY CLUSTER ANALYSIS OF N,N'-DISUBSTITUTED AMIDES [J]. Chinese Journal of Applied Chemistry, 1992, 0(6): 71-76.