Article(id=1308455583988871667, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1308455410751525737, articleNumber=null, orderNo=null, doi=10.16438/j.0513-4870.2025-0108, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1738944000000, receivedDateStr=2025-02-08, revisedDate=1745424000000, revisedDateStr=2025-04-24, acceptedDate=null, acceptedDateStr=null, onlineDate=1789889721151, onlineDateStr=2026-09-20, pubDate=1754928000000, pubDateStr=2025-08-12, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1789889721151, onlineIssueDateStr=2026-09-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1789889721151, creator=13701087609, updateTime=1789889721151, updator=13701087609, issue=Issue{id=1308455410751525737, tenantId=1146029695717560320, journalId=1189982191388893191, year='2025', volume='60', issue='8', pageStart='2375', pageEnd='2648', issueExtLink='null', onlineDate='null', pubDate='1754928000000', pubDateStr='2025-08-12', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1789889679849, creator='13701087609', updateTime=1789893542748, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1308471612978786380, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1308455410751525737, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1308471612978786381, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1308455410751525737, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=2573, endPage=2584, ext={EN=ArticleExt(id=1308455584190198260, articleId=1308455583988871667, tenantId=1146029695717560320, journalId=1189982191388893191, language=EN, title=Post-acquisition strategy integrating precursor ion targeting recognition and diagnostic ion filtering to realize the rapid chemical profiling of Dengzhan Shengmai capsule using UHPLC-Q-Exactive-Orbitrap analysis, columnId=1190335348761793317, journalTitle=Acta Pharmaceutica Sinica, columnName=Original Articles, runingTitle=null, highlight=null, articleAbstract=

The chemical profiling of Dengzhan Shengmai capsules were characterized using ultra high performance liquid chromatography/tandem quadrupole electrostatic field orbitrap (UHPLC-Q-Exactive-Orbitrap) high resolution mass spectrometry analysis. The post-acquisition strategy integrating precursor ion targeting recognition and diagnostic ion filtering was proposed to realize the identification of components in Dengzhan Shengmai capsules. The mass spectrometric data were acquired in both positive and negative ion modes using a full-scan MS1 coupled with data-dependent automatic triggering of MS/MS. By employing the similarity analysis function within the Access database software, precursor ions were promptly identified by comparing determined accurate masses to the in-house mass spectrometry database specific to Dengzhan Shengmai capsules. A diagnostic ion database encompassing a variety of compounds found in Dengzhan Shengmai capsules was compiled based on the mass spectrometry fragmentation patterns of 16 reference components. Ultimately, 248 compounds were characterized utilizing the diagnostic ion filtering method, comprising 51 caffeoyl esters, 38 flavonoids, 63 ginsenosides, 19 steroidal saponins, 11 nortriterpenoids, 21 homoisoflavones, 39 lignans and 6 other class constituents. The developed qualitative analysis approach enables swift and effective identification of chemical components present in Dengzhan Shengmai capsules, serving as a scientific basis for quality assessment and clinical utilization. This innovative strategy on high-resolution mass spectrometry data analysis, integrating precursor ion targeting recognition together with diagnostic ion filtering, introduced a novel methodology for the comprehensive analysis of complex substance systems in traditional Chinese medicine.

, authors=Ye-han CAI1, 2, 3, Yu-qian LIN1, 2, 3, Fang YUAN4, Shu-mei WANG1, 2, 3, Yuan-yuan XIE1, 2, 3, *, authorsList=Ye-han CAI, Yu-qian LIN, Fang YUAN, Shu-mei WANG, Yuan-yuan XIE, authorCompany=null, correspAuthors=Yuan-yuan XIE, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright ©2025 Acta Pharmaceutica Sinica. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1308455586098606594, articleId=1308455583988871667, tenantId=1146029695717560320, journalId=1189982191388893191, language=CN, title=前体离子靶向识别结合诊断离子过滤的数据处理策略快速鉴定灯盏生脉胶囊的化学成分, columnId=1190335348896011050, journalTitle=药学学报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=

通过超高效液相色谱串联四极杆静电场轨道阱(UHPLC-Q-Exactive-Orbitrap) 高分辨质谱分析, 耦合前体离子靶向识别结合诊断离子过滤的数据处理策略对灯盏生脉胶囊的化学成分进行分析鉴定。采用一级全扫描加数据依赖自动触发二级质谱扫描模式, 在正负离子模式下采集质谱数据。采用Access数据库相似性分析函数将获取的精确质量数与自建灯盏生脉胶囊化学成分质谱数据库匹配分析快速识别前体离子; 基于16个代表性成分的质谱裂解规律构建灯盏生脉胶囊中各类化合物的诊断离子数据库, 并利用诊断离子过滤策略, 鉴定了其中248个化合物的结构, 包括51个咖啡酰酯类、38个黄酮类、63个人参皂苷类、19个甾体皂苷类成分、11个降三萜类、21个高异黄酮类、39个木脂素类成分和6个其他类成分。本研究所建立的定性分析方法能快速、高效地对灯盏生脉胶囊的化学成分进行分析鉴定, 为其质量评价和临床应用提供了科学依据, 所建立的前体离子靶向识别与诊断离子过滤相结合的高分辨质谱数据解析策略为中药复杂物质体系成分分析提供了新的思路。

, authors=蔡烨函1, 2, 3, 林于茜1, 2, 3, 袁芳4, 王淑美1, 2, 3, 谢媛媛1, 2, 3, *, authorsList=蔡烨函, 林于茜, 袁芳, 王淑美, 谢媛媛, authorCompany=null, correspAuthors=谢媛媛, authorNote=

作者贡献:

蔡烨函负责数据库构建、结构鉴定及文章撰写与修改; 林于茜和袁芳负责相关实验操作及数据库资料收集; 王淑美和谢媛媛指导本文的选题设计、实验指导、实验数据处理、文章撰写。

, correspAuthorsNote=
谢媛媛, E-mail:
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前体离子靶向识别结合诊断离子过滤的数据处理策略快速鉴定灯盏生脉胶囊的化学成分
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蔡烨函 1, 2, 3 , 林于茜 1, 2, 3 , 袁芳 4 , 王淑美 1, 2, 3 , 谢媛媛 1, 2, 3, *
药学学报 | 研究论文 2025,60(8): 2573-2584
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药学学报 |研究论文 2025 , 60 (8) : 2573 -2584
前体离子靶向识别结合诊断离子过滤的数据处理策略快速鉴定灯盏生脉胶囊的化学成分
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蔡烨函1, 2, 3, 林于茜1, 2, 3, 袁芳4, 王淑美1, 2, 3, 谢媛媛1, 2, 3, *
作者信息
  • 1广东药科大学中药学院, 广东 广州 510006
  • 2广东省中药质量工程技术研究中心, 广东 广州 510006
  • 3国家中医药管理局中药数字化质量评价技术重点研究室, 广东 广州 510006
  • 4广东药科大学药学院, 广东 广州 510006
通讯作者:
谢媛媛, E-mail:
作者简介:

作者贡献:

蔡烨函负责数据库构建、结构鉴定及文章撰写与修改; 林于茜和袁芳负责相关实验操作及数据库资料收集; 王淑美和谢媛媛指导本文的选题设计、实验指导、实验数据处理、文章撰写。

Post-acquisition strategy integrating precursor ion targeting recognition and diagnostic ion filtering to realize the rapid chemical profiling of Dengzhan Shengmai capsule using UHPLC-Q-Exactive-Orbitrap analysis
Ye-han CAI1, 2, 3, Yu-qian LIN1, 2, 3, Fang YUAN4, Shu-mei WANG1, 2, 3, Yuan-yuan XIE1, 2, 3, *
Affiliations
  • 1School of Chinese Materia Medica, Guangdong Pharmaceutical University, Guangzhou 510006, China
  • 2Guangdong Provincial Traditional Chinese Medicine Quality Engineering and Technology Research Center, Guangzhou 510006, China
  • 3Key Laboratory of Digital Quality Evaluation Technology of Traditional Chinese Medicine, National Administration of Traditional Chinese Medicine, Guangzhou 510006, China
  • 4School of Pharmacy, Guangdong Pharmaceutical University, Guangzhou 510006, China
出版时间: 2025-08-12 doi: 10.16438/j.0513-4870.2025-0108
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通过超高效液相色谱串联四极杆静电场轨道阱(UHPLC-Q-Exactive-Orbitrap) 高分辨质谱分析, 耦合前体离子靶向识别结合诊断离子过滤的数据处理策略对灯盏生脉胶囊的化学成分进行分析鉴定。采用一级全扫描加数据依赖自动触发二级质谱扫描模式, 在正负离子模式下采集质谱数据。采用Access数据库相似性分析函数将获取的精确质量数与自建灯盏生脉胶囊化学成分质谱数据库匹配分析快速识别前体离子; 基于16个代表性成分的质谱裂解规律构建灯盏生脉胶囊中各类化合物的诊断离子数据库, 并利用诊断离子过滤策略, 鉴定了其中248个化合物的结构, 包括51个咖啡酰酯类、38个黄酮类、63个人参皂苷类、19个甾体皂苷类成分、11个降三萜类、21个高异黄酮类、39个木脂素类成分和6个其他类成分。本研究所建立的定性分析方法能快速、高效地对灯盏生脉胶囊的化学成分进行分析鉴定, 为其质量评价和临床应用提供了科学依据, 所建立的前体离子靶向识别与诊断离子过滤相结合的高分辨质谱数据解析策略为中药复杂物质体系成分分析提供了新的思路。

诊断离子过滤  /  前体离子靶向识别  /  UPLC-Q-Exactive-Orbitrap MS  /  灯盏生脉胶囊  /  定性分析

The chemical profiling of Dengzhan Shengmai capsules were characterized using ultra high performance liquid chromatography/tandem quadrupole electrostatic field orbitrap (UHPLC-Q-Exactive-Orbitrap) high resolution mass spectrometry analysis. The post-acquisition strategy integrating precursor ion targeting recognition and diagnostic ion filtering was proposed to realize the identification of components in Dengzhan Shengmai capsules. The mass spectrometric data were acquired in both positive and negative ion modes using a full-scan MS1 coupled with data-dependent automatic triggering of MS/MS. By employing the similarity analysis function within the Access database software, precursor ions were promptly identified by comparing determined accurate masses to the in-house mass spectrometry database specific to Dengzhan Shengmai capsules. A diagnostic ion database encompassing a variety of compounds found in Dengzhan Shengmai capsules was compiled based on the mass spectrometry fragmentation patterns of 16 reference components. Ultimately, 248 compounds were characterized utilizing the diagnostic ion filtering method, comprising 51 caffeoyl esters, 38 flavonoids, 63 ginsenosides, 19 steroidal saponins, 11 nortriterpenoids, 21 homoisoflavones, 39 lignans and 6 other class constituents. The developed qualitative analysis approach enables swift and effective identification of chemical components present in Dengzhan Shengmai capsules, serving as a scientific basis for quality assessment and clinical utilization. This innovative strategy on high-resolution mass spectrometry data analysis, integrating precursor ion targeting recognition together with diagnostic ion filtering, introduced a novel methodology for the comprehensive analysis of complex substance systems in traditional Chinese medicine.

diagnostic ion filtering  /  precursor ion targeting recognition  /  UPLC-Q-Exactive-Orbitrap MS  /  Dengzhan Shengmai capsule  /  qualitative analysis
蔡烨函, 林于茜, 袁芳, 王淑美, 谢媛媛. 前体离子靶向识别结合诊断离子过滤的数据处理策略快速鉴定灯盏生脉胶囊的化学成分. 药学学报, 2025 , 60 (8) : 2573 -2584 . DOI: 10.16438/j.0513-4870.2025-0108
Ye-han CAI, Yu-qian LIN, Fang YUAN, Shu-mei WANG, Yuan-yuan XIE. Post-acquisition strategy integrating precursor ion targeting recognition and diagnostic ion filtering to realize the rapid chemical profiling of Dengzhan Shengmai capsule using UHPLC-Q-Exactive-Orbitrap analysis[J]. Acta Pharmaceutica Sinica, 2025 , 60 (8) : 2573 -2584 . DOI: 10.16438/j.0513-4870.2025-0108
灯盏生脉胶囊(DZSMC) 是由灯盏细辛、人参、麦冬和五味子提取精制而成的中药大品种之一, 具有益气养阴、活血通络的功效, 主要用于缺血性心脑血管疾病恢复期的治疗, 也是目前具有循证医学证据的脑卒中二级预防用中成药, 已纳入2018版国家基本药物和国家基本医疗保险药品目录2023版乙类产品[1, 2]。前期研究表明, DZSMC可通过调控PI3K/AKT/caspase-3、Nrf2/Keap1、JAK2/STAT3和NF-κB等信号通路相关因子的蛋白及基因表达, 改善微循环, 抑制血小板聚集和血栓形成, 清除自由基, 减轻氧化应激对心脑血管的损伤, 抑制炎症反应, 缓解缺血引起的血管炎症损伤, 促进神经功能恢复, 从而发挥治疗心脑血管疾病的作用[3-7]。灯盏生脉胶囊中的化学成分多样, 主要包括黄酮类、酚酸类、皂苷类和木脂素类等成分[3]。虽已有研究采用全二维液相色谱联用四极杆飞行时间质谱对灯盏生脉胶囊中的化合物进行了全面表征, 但主要通过二维色谱分离增加峰容量提高各类化合物的检出效率, 缺少主要类别化合物的质谱裂解规律的总结分析[8], 限制了基于LC-MS的灯盏生脉胶囊体内成分定性分析的效率。
液质联用技术以其强大的分离性能和结构解析能力成为阐明中药化学物质基础的有效工具之一。质量亏损过滤、诊断离子过滤、质谱树状图相似性分析和分子网络等高效的数据后处理方法可以帮助研究者更准确地鉴定中药成分的结构[9, 10]。前体离子识别在质谱数据解析中至关重要, 直接影响鉴定结果的准确性。UNIFI、Compound Discovery等商业软件通过将高分辨质谱分析获取的峰表与商业化的质谱数据库进行匹配后可快速识别前体离子, 但由于商业化数据库专属性不强等问题, 常常会产生大量假阳性结果, 需要耗费时间和精力去甄别, 且甄别过程对操作人员的专业性和经验要求较高。因此, 基于高分辨质谱的中药复杂物质体系成分结构解析中, 往往需要自建质谱数据库。Microsoft Office Access软件通过内置字符串函数、自定义VBA (visual basic for applications) 函数(如Levenshtein距离) 等进行相似性识别, 将获取的精确质量数信息与自建质谱数据库快速匹配, 可实现前体离子的快速靶向识别, 提高鉴定效率。诊断离子过滤(diagnostic ion filtering, DIF) 是利用同类化合物具有相同裂解规律, 会产生相同碎片离子(即特征离子), 进而通过特征离子获取具有相似结构的化学成分信息的数据后处理方法, 具有操作简单、识别准确率高、结构注释能力强等优点[11-13]。
本研究以DZSMC为研究对象, 通过超高效液相色谱串联四极杆静电场轨道阱(UHPLC-Q-Exactive-Orbitrap) 高分辨质谱分析, 耦合前体离子靶向识别结合诊断离子过滤的数据处理策略对灯盏生脉胶囊的化学成分进行分析鉴定, 并对化合物进行归类和归属, 以期为DZSMC的药效物质基础与作用机制研究提供理论依据和数据支持。
仪器  Thermo Ulti Mate 3000超高效液相色谱系统(配有LPG-3400SD二元液相泵、二极管阵列检测器、WPS-3000TRS动进样器、在线脱气机、TCC-3200柱温箱); Q-Exactive Focus四极杆-静电场轨道阱质谱仪, 配有电喷雾离子源(ESI, 美国Thermo-Fisher公司); KQ-400DE数控超声波清洗仪(昆山市超声仪器有限公司); SQP型十万分之一电子天平(德国赛多利斯科学仪器有限公司)。
试剂和药品  野黄芩素(批号: ST06340120)、异绿原酸A (批号: STC0680120) 和芹菜素-7-O-β-D-葡萄糖醛酸苷(批号: ST08920120) 均购自上海诗丹德生物技术有限公司; 五味子乙素(批号: 110765-201512) 购自中国食品药品检定研究所; 野黄芩苷(批号: CHB201130)、绿原酸(批号: CHB201114)、异绿原酸C (批号: CHB210104)、人参皂苷Rc (批号: CHB190104)、人参皂苷Rf (批号: CHB190108)、人参皂苷Rd (批号: CHB210114)、人参皂苷Re (批号: CHB190107)、人参皂苷Rg1 (批号: CHB201101)、人参皂苷Rb1 (批号: CHB210113)、五味子醇甲(批号: CHB0106)、戈米辛D (批号: CHB201118) 和麦冬皂苷D (批号: CHB201105) 均购自成都克洛玛生物科技有限公司, 本研究所用对照品纯度均大于98%。灯盏生脉胶囊(批号: 20200420) 购自云南生物谷制药有限公司。甲酸(LC-MS级)、甲醇(LC-MS级) 和乙腈(LC-MS级) 均购自美国Fisher公司; Watsons屈臣氏蒸馏水(广州屈臣氏食品饮料有限公司)。
对照品与供试品溶液制备
对照品溶液的制备  分别精密称取野黄芩苷、灯盏甲素、野黄芩素、绿原酸、3,5二咖啡酰奎宁酸、4,5二咖啡酰奎宁酸、人参皂苷Re、人参皂苷Rb1、人参皂苷Rg1、人参皂苷Rd、人参皂苷Rf、人参皂苷Rc、麦冬皂苷D、五味子醇甲、五味子乙素、戈米辛D对照品加适量甲醇和水, 制得浓度为15 mmol·L-1的对照品溶液。
供试品溶液的制备  称取0.5 g灯盏生脉胶囊内容物, 精密称定, 加入10 mL 50%甲醇, 超声(功率250 W, 40 kHz) 处理30 min, 离心10 min (4 000 r·min-1), 取上清液经0.22 µm微孔滤膜滤过, 即得。
色谱条件与质谱条件
色谱条件  采用ACQUITY BEH C18 (100 mm × 2.1 mm, 1.7 μm) 色谱柱; 流动相: A为0.1%甲酸-水溶液, B为0.1%甲酸-乙腈溶液, 梯度洗脱, 洗脱程序为: 0~2 min, 5% B; 2~15 min, 5%~7% B; 15~22 min, 7%~20% B; 22~35 min, 20%~40% B; 35~40 min, 40%~60% B; 40~43 min, 60%~65% B; 43~50 min, 65%~90% B; 50~55 min, 90% B; 55~60 min, 90%~5% B。柱温30 ℃, 流速0.4 mL·min-1, 进样量2 μL。
质谱条件  电喷雾离子源, 正负离子模式同时检测, 喷雾电压+3.00 kV/-2.80 kV, 离子源温度320 ℃, 鞘气流速35 Arb, 辅助气流速10 Arb, 毛细管温度320 ℃。采用Full mass/dd-MS2 (TopN) 采集一级质谱数据, 质量范围m/z 100~1 500, 分辨率分别为一级质谱70 K, 二级质谱17 500, AGC (auto gain control) 分别设为100 000 (一级) 和20 000 (二级), 最大注射液时间分别设为150和80 ms。采用高能诱导裂解(HCD) 方式裂解, 碰撞能量分别为20/40/60 V, 归一化碰撞能量30%, FT采集二级质谱数据, 采用“Top-Speed”算法进行数据依赖扫描, 离子强度高于2.0×105的一级离子进行二级碎裂, 动态排除时间为6 s。数据采集和处理使用Xcalibur 4.0软件。
数据处理  使用XcaliburTM 4.0软件进行数据采集。将获得的高分辨率质谱数据导入Compound Discover 3.1软件(美国Thermo Fisher公司) 进行数据预处理, 包括峰对齐、峰提取和精确质量拟合分子式。参数设置如下: 正离子模式: [M+H]+, [M+Na]+, 负离子模式: [M-H]-, [M+HCOO]-; 保留时间设置在0~60 min; 保留时间公差设置0.2 min; 最小前体质量: 0 Da; 最大值前驱体质量: 5 000 Da; 对齐保留时间: 最大移位2 min; 质量公差: 5 ppm; 强度耐受度: 30%; Min. Peak Intensity: 100 000; 信噪比阈值: 3。获取由分子式、分子量、保留时间及其相关峰面积组成的原始数据列表(峰矩阵)。基于精确质量数和碎片离子等信息采用Compound Discover 3.1软件进行自动搜库(如mzClould、mzVault和Chemspider等)。在该软件中, 根据从高分辨率质谱中获得的精确分子量确定可能的元素组成。将由此提取的峰表导入到Microsoft Office Access 2021数据库中作为比较的源数据, 创建查询。以灯盏生脉方in-house质谱数据库作为数据库。查询语句设置为: SELECT source data. *, database. *; FROM source data LEFT JOIN database ON [abs (source data. Mass-database. Mass) < 0.02]。
DZSMC化学成分in-house质谱数据库的建立  对PubMed (https://pubmed.ncbi.nlm.nih.gov/)、Chemspider (https://www.chemspider.com)、SciFinder (https://scifinder-n.cas.org)、中国知网等数据库进行系统性的检索, 收集DZSMC中4味药材(即灯盏细辛、人参、麦冬和五味子) 的化学成分信息, 共收集658种化合物的信息, 其中灯盏细辛(黄酮类、酚酸和挥发油) 有190种化合物, 人参(人参皂苷) 有121种化合物, 麦冬(甾体皂苷和高异黄酮) 有166种化合物, 五味子(木脂素和降三萜) 有181种化合物。包括化合物名称、结构、分子式、精确分子量和来源等信息, 将其制成Excel电子表格, 同时用ChemDraw绘制结构式并保存.mol文件即得。
按上述色谱质谱条件进样供试品和对照品, XcaliburTM 4.0 (美国Thermo Fisher公司) 质谱工作站采集化学成分质谱数据, 得到各色谱峰的保留时间、精确分子量和碎片离子信息。正、负离子模式下获取样品总离子流图, 详见图1。
通过Compound Discover 3.1分析软件对DZSMC的质谱文件进行峰提取, 生成由保留时间、准确质量和分子式组成的原始数据列表。通过筛选最终在DZSMC正离子模式下获取的质谱文件中提取到14 575个峰; 在DZSMC负离子模式下获取的质谱文件中提取到10 956个峰, 即总峰提取数25 531个。与空白样品匹配上的正离子415个峰, 负离子7个峰, 即空白样假阳性(blank false positive, FPblank) 为422。利用Microsoft Office Access 2021软件, 采用相似性分析函数, 通过将获取质谱数据中的精确质量数与in-house质谱数据库进行匹配, 共得到719个灯盏细辛前体离子、169个人参前体离子、414个麦冬前体离子和489个五味子前体离子(总匹配峰数为1 791个)。对假阳性结果进行甄别, 如同一化合物被匹配到多种提取离子色谱峰, 或该碎片离子与其他分子离子峰的保留时间相近, 且为该分子离子峰的碎片的则视为假阳性匹配结果而剔除。最后, 识别出来源于灯盏细辛的308个前体离子, 人参的107个前体离子, 麦冬的118个前体离子和五味子的169个前体离子, 共702个, 通过前体离子识别初步匹配的假阳性FP1为1 089 (总匹配峰数-初步剔除后剩余数)。
选取灯盏生脉胶囊中的16个代表性成分的标准品进行液质联用分析, 获取保留时间、质谱碎片信息、相对分子质量等质谱信息。结合文献归纳各类成分的特征碎片、裂解规律。并在此基础上建立各类化合物的诊断离子数据库, 并进行诊断离子筛查, 筛查策略如图2所示。
本研究以DZSMC为研究对象, 通过超高效液相色谱串联四极杆静电场轨道阱(UHPLC-Q-Exactive-Orbitrap) 高分辨质谱分析, 耦合前体离子靶向识别结合诊断离子过滤的数据处理策略在灯盏生脉胶囊中鉴定了248个化合物的结构, 包括51个咖啡酰酯类、38个黄酮类、63个人参皂苷类、19个甾体皂苷类成分、11个降三萜类、21个高异黄酮类、39个木脂素类成分和6个其他类成分。诊断离子过滤后假阳性FP2为454 (初步剔除后剩余数-最终确认峰数), 假阳性数FP为FP1+FP2 = 1 543, 总假阳性数FPtotal为FP+FPblank = 1 965, 真阴性数量(true negative, TN) 为25 283 (总提取峰数-最终确认峰数), 依据公式FPR = $ \frac{\mathrm{F}\mathrm{P}}{\mathrm{F}\mathrm{P}+\mathrm{T}\mathrm{N}} $, 假阳性率(false positive rate, FPR) 为7.2%。诊断离子过滤筛查结果如图3所示。
灯盏细辛的主要化学成分是黄酮类和咖啡酰酯类。本研究选取咖啡酰酯类代表化合物绿原酸、异绿原酸A和异绿原酸C进行质谱解析。基于标准品及文献[14]信息总结咖啡酰酯类化合物的质谱碎裂规律如下(图4A): 该类成分包含咖啡酰基奎宁酸(CQA)、咖啡酰-2,7-脱氢-3-脱氧-2-辛酮糖酸(CDOA)、咖啡酰-2,7-脱氢-2-辛酮糖酸(COA) 和咖啡酰-1-(2′-λ-吡喃酮) (CPO) 四类化合物, 主要围绕酯键裂解, 在负离子模式下化合物会裂解形成[caffeic acid-H]-和[M-caffeoyl-H]-两个特征碎片离子。酯键断裂导致丢失咖啡酸片段后, 产生515.11、353.08、191.05等特征离子。
基于诊断离子过滤策略, 本研究鉴定出51个咖啡酰酯类化合物, 其中基于特征碎片m/z 353.08、m/z 191.05, 快速识别到28个CQA类化合物。11个CDOA类化合物通过特征离子m/z 381.08、m/z 161.02鉴定; 5个COA类化合物通过m/z 235.04、m/z 397.07辨识; 2个CPO类化合物(27、29) 则通过特征离子m/z 179.03、m/z 435.09识别; 此外还有5个其他类咖啡酰酯类化合物。通过标准品比对, 可确定化合物5、53、62分别为3-咖啡酰基奎宁酸、3,5-二咖啡酰基奎宁酸和4, 5-二咖啡酰基奎宁酸(图4A)。以化合物73、77、101为例, 其在负离子模式下的分子离子峰均为677.15 [M-H]-, 在二级质谱中, 均通过酯键断裂连续丢失咖啡酰基[caffeic acid-H]-产生m/z 515.11、m/z 353.08和m/z 191.05的碎片, 故推测其为三咖啡酰奎宁酸。根据保留时间[15], 推测化合物73、77、101分别为1,3,5-三咖啡酰奎宁酸、1,3,4-三咖啡酰奎宁酸、3,4,5-三咖啡酰奎宁酸。化合物79在负离子模式下的分子离子峰为721.141 6 [M-H]- (C35H30O17, tR = 27.16 min), 在二级质谱中, 存在m/z 559.108 2、m/z 397.078 3和m/z 235.045 8的特征碎片, 为酯键断裂连续丢失咖啡酰基[caffeic acid-H]-产生的碎片, 因此, 该化合物为有3个咖啡酰基的COA类化合物, 推测化合物79为3, 4, 9-咖啡酰-2,7-脱氢-2-辛酮糖酸。
野黄芩苷、野黄芩素和灯盏甲素是灯盏细辛中代表性黄酮类成分。这类化合物质谱裂解规律如下[16-21]: 糖苷键裂解是黄酮类氧化糖苷的主要裂解方式, 导致中性分子如C6H10O5 (162 Da) 的丢失; 黄酮苷元在质谱中的裂解模式主要涉及逆狄尔斯-阿尔德(Retro Diels-Alder reaction, RDA) 裂解, 产生两个特征片段: A环片段(m/z 151.00, 107.01) 和B环片段(m/z 133.02, 119.05)。此外, 还存在中性小分子碎片(CO2、C3O2、C2H2O) 丢失, 形成m/z 241.05和m/z 257.04等碎片, 这些特征离子用作筛选黄酮类化合物的诊断离子。
通过黄酮苷元的RDA裂解碎片如m/z 151.00、119.05及小分子碎片m/z 241.05、175.04靶向筛选黄酮苷类化合物, 共识别了38个黄酮类成分。化合物71的化学式为C15H10O6, 通过标准品比对, 确认化合物71为野黄芩素(图4B)。化合物71的分子离子峰为m/z 285.040 7 [M-H]- (C15H10O6, tR = 26.46 min), 经过RDA裂解断裂C2-C3键, 得到碎片离子m/z 169.065 0和m/z 119.050 3。黄酮苷类的鉴定以苷元为依据, 在苷元的基础上连接糖基, 根据苷与苷元的质量差, 进一步确定黄酮苷所连接糖基的种类, 最终确定黄酮苷结构。以化合物47为例, 其在负离子模式下的分子离子峰为593.152 4 [M-H]- (C27H30O15, tR = 24.22 min), 在二级谱图中产生m/z 285.040 4的高丰度特征碎片, 结合RDA裂解得到的特征碎片133.029 6和151.003 9, 推测该黄酮苷元在A环上有2个羟基, 在B环上有1个羟基, 因此推测该苷元为山柰酚。再根据苷与苷元的质量差为(146 Da + 162 Da), 结合低质量碎片149.045 7、101.024 4、113.024 5等糖基碎片, 最终确定该化合物是苷元山柰酚与一分子葡萄糖和一分子鼠李糖(芸香糖苷) 相连, 故化合物47为山柰酚-3-O-β-D-芸香糖苷。
人参皂苷类是人参主要活性成分, 根据母核的不同可分为四种类型: 原人参二醇型人参皂苷、原人参三醇型人参皂苷、C-17支链变化和齐墩果酸型人参皂苷。本研究基于人参皂苷Rb1、Rd、Rc、Re、Rf和Rg1等标准品进行质谱分析, 总结人参皂苷的质谱碎裂规律(图4C)[22-29]。人参皂苷的母核通常较稳定, 不易裂解。在负离子模式下, 原人参二醇型的母核特征离子为m/z 459.38, 原人参三醇型的母核特征离子碎片为m/z 475.37, 齐墩果酸型的母核特征离子碎片为m/z 455.35。皂苷中大多带有配糖基或丙二酰基, 一般在母核的C-3、C-6、C-20位上与葡萄糖、鼠李糖等单糖相连, 且糖苷键或酯键容易断裂, 获得162、42 Da等中性丢失碎片信息。因此, 选择母核的四个特征离子作为诊断离子。
从灯盏生脉中共鉴定出63种人参皂苷, 其中包括38种原人参二醇型皂苷、14种原人参三醇型皂苷、7种齐墩果酸型皂苷和4种C-17支链变化的三萜皂苷。根据原人参二醇型皂苷的母核特征离子m/z 459.38及文献信息[22-29], 快速识别了38个原人参二醇型化合物, 根据母核特征离子m/z 475.37、637.43共筛查出14个原人参三醇型皂苷化合物。通过齐墩果烷型皂苷的母核特征离子m/z 455.350 0靶向筛选共识别了7个化合物为齐墩果烷型皂苷。此外, 还有一类C-17支链变化的三萜皂苷, 基于特征离子m/z 603.42、m/z 441.37快速识别了化合物189、230、231、235。以化合物127、137例, 化合物127、137在负离子模式下的分子离子峰都为m/z 1 123.59 [M+HCOO]-, 在高质量区域糖基逐个损失, 通过丢失一分子木糖(132 Da) 和两分子葡萄糖(162 Da) 产生m/z 1 077.58、m/z 945.54、m/z 783.49、m/z 621.43等碎片, 最终脱糖成苷元(m/z 459.38), 故推测化合物127、137为人参皂苷Rb2或Rb3, 经文献比对[23], 根据保留时间差异推测化合物127、137分别为人参皂苷Rb2、Rb3。丙二酰基人参皂苷是一种酸性人参皂苷, 其在葡萄糖基部分的6′位上有一个丙二酰基。大多数丙二酰基人参皂苷来源于原人参二醇型人参皂苷, 因此都与原人参二醇型人参皂苷有共同的母核结构。如化合物131、140、142, 分子离子峰皆为1 163.58 [M-H]-, 在二级质谱中, 通过丢失一分子CO2 (44 Da) 或一分子乙酰基(86 Da) 产生m/z 1 119.59、m/z 1 077.58, 后续的碎片信息与化合物127、134、137一致, 故推测它们是相应的丙二酰人参皂苷, 根据保留时间差异, 推测化合物131、140、142分别为丙二酰人参皂苷Rb2、Rc、Rb3。
甾体皂苷包括螺甾烷醇和呋喃甾烷醇苷, 是麦冬的主要成分。根据苷元的结构[30]可分为: Ⅰ型甾体皂苷(母核结构为鲁斯可皂苷元/偏诺皂苷元+ C6H10O5)、Ⅱ型甾体皂苷(母核结构为薯蓣皂苷元/鲁斯可皂苷元+ C6H10O4)、Ⅲ型甾体皂苷(母核结构为麦冬皂苷元)、Ⅳ型甾体皂苷(母核结构为鲁斯可皂苷元)、Ⅴ型甾体皂苷(母核结构为薯蓣皂苷元/呋甾烷)。选取甾体皂苷代表化合物麦冬皂苷D进行质谱裂解规律分析, 发现主要是糖苷键的裂解, 苷元部分很难裂解, 一般产生特征碎片[M-H+单糖]-。故该类化合物均以其母核离子(如m/z 591.35, m/z 575.35等) 为特征离子(图5)。
本研究共鉴定出19个甾体皂苷类成分, 其中Ⅰ型甾体皂苷5个, Ⅱ型甾体皂苷9个, Ⅲ型甾体皂苷3个, Ⅳ型甾体皂苷2个。以Ⅰ型甾体皂苷为例, 具体裂解途径如图5A。在Ⅰ型甾体皂苷的特征离子m/z 591.35的DIF色谱图中识别到5个峰; 在Ⅱ型甾体皂苷的特征离子m/z 721.41、m/z 575.35的DIF色谱图中识别到17个峰, 通过去除假阳性结果, 最终得到8个化合物为Ⅱ型甾体皂苷。以化合物228为例, 化合物228的负离子的分子离子峰为m/z 721.415 5 [M-H]- (C39H62O12, tR = 42.27 min), 在MS/MS谱图中, 存在101.024 4、119.035 0等糖基碎片, 提示存在葡萄糖链。碎片m/z 205.071 7提示该化合物存在芸香糖苷侧链。据此推测该化合物通过丢失一分子鼠李糖(146 Da) 产生m/z 575.35的碎片离子, 故推测化合物228可能是麦冬皂苷B。通过Ⅲ型甾体皂苷的特征离子m/z 753.40筛选, 经亚特征离子Ⅲ型甾体皂苷母核碎片m/z 445.29重筛选后, 共鉴定了3个潜在的Ⅲ型甾体皂苷化合物。
Ⅳ型为呋甾烷醇糖苷, 在苷元的C26羟基上连有一分子葡萄糖, 通过丢失C6H12O6 (180 Da) 转化为相应的螺烷醇糖苷。基于特征离子m/z 429.30、m/z 771.41识别了2个Ⅳ型甾体皂苷。以化合物160为例, 化合物160在负离子模式下的分子离子峰为m/z 753.406 5 [M-H]- (C39H62O14, tR = 36.11 min), 在二级质谱中, 存在205.071 8的芸香糖苷侧链特征碎片及101.024 5、113.024 5等葡萄糖碎片提示该化合物通过丢失一分子鼠李糖(146 Da) 和一分子葡萄糖(162 Da) 最终得到m/z 445.298 0的母核碎片离子, 故化合物160是在麦冬皂苷苷元的基础上再连一分子鼠李糖和一分子葡萄糖, 推测化合物160是麦冬皂苷Ra。
高异黄酮类化合物也是麦冬的主要成分, 高异黄酮是比异黄酮多1个亚甲基的特殊黄酮, 亚甲基的存在导致9位容易发生质谱裂解反应, 从而产生失去B环的碎片离子[31]。根据母核结构的差异, 高异黄酮主要分为3类: Ⅰ型高异黄酮、Ⅱ型高异黄酮和Ⅲ型高异黄酮。本研究根据诊断离子过滤策略及文献比对, 共鉴定出21个高异黄酮类成分, 其中Ⅰ型高异黄酮9个、Ⅱ型高异黄酮10个和Ⅲ型高异黄酮2个。
Ⅰ型高异黄酮C2-C3通过双键连接, C9-C1′和C9-C3断裂失去B环, 生成两个相差13 Da的产物离子, 根据文献[32, 33]及特征质量差可用来鉴别Ⅰ型高异黄酮。基于特征离子和中性丢失识别了9个Ⅰ型高异黄酮化合物; 化合物218的准分子离子峰m/z 339.087 6 ([M-H]-, C19H16O6), 在二级谱图中产生m/z 218.057 2 [M-H-B-ring]-、m/z 205.050 3 [M-H-B-ring-CH2]-等典型离子碎片, 提示该化合物为Ⅰ型高异黄酮, m/z 218.057 2是化合物断裂B环的产物碎片离子, 故推测B环上连有-O-CH2-O-的基团, 推测化合物218为甲基麦冬黄酮A (图5B); Ⅱ型高异黄酮C2-C3键是饱和键, 一般是C3-C9断裂失去B环, 然后C4处损失分子CO。两种产物离子的质量相差28 Da, 根据文献[34, 35]及特征质量差可用于区分不同高异黄酮的结构类型, 由此共识别10个Ⅱ型高异黄酮。Ⅲ型高异黄酮的A环上带有甲酰基, 无论C2-C3键是否饱和, 一般会先断裂甲酰基, 产生M-28质量数的产物离子。基于此规律识别化合物240、241。以化合物241为例, 其分子离子峰为m/z 355.082 9 [M-H]-, 在m/z 327.087 1 [M-H-CO]-、m/z 192.042 6 [M-H-CH2O2-B-ring-CO]-、m/z164.047 9 [M-H-CH2O2-B-ring-2CO]-等表现出典型的碎片离子, 说明有甲酰基的存在, 故推测该化合物为麦冬黄烷酮C。
木脂素是五味子的主要成分, 根据取代基的有无可分为四类: C环上无氧基(A型); C环上连羟基(B型); C环上连有酯基或羟基(C型) 和苯环上连羟基(D型)。本研究选取五味子醇甲、五味子甲素和戈米辛D的标准品解析它们的质谱裂解规律[36, 37]: 在正离子模式下, A型木脂素类一般是在C6-C7和C9-C10键断裂失去C5H10 (70 Da) 或C2H4O (44 Da), C环转变为五元环, 然后C1位的甲氧基被去除; 若C6或C7上存在羟基, 则会在C环上形成双键产生主要碎片离子[M+H-H2O]+, 之后C环失去C5H9 (69 Da), 产生[M+H-H2O-C5H9]+; 若C6位有酯基、在C7位有羟基, 通常先失去酯基, 形成强离子[M+H-C4H7COOH/C5H6COOH]+。即木脂素可能产生70和44 Da等中性片段, 这些片段可作为识别木脂素的关键中性碎片, 用于后续鉴定。
基于特征离子383.140 0和中性碎片70、31 Da等, 共筛查到39个联苯环辛二烯型木脂素。化合物245在m/z 401.194 7 [M+H]+处出现分子离子峰。在m/z 300.097 9 [M+H-C5H10-OCH3]+和m/z 331.116 1 [M+H-C5H10]+处的高丰度碎片离子表明它是A型木脂素。经与对照品比对鉴定为五味子乙素, 裂解途径如图6A。化合物168在m/z 346.139 8 [M-H-H2O-C5H9]+、m/z 384.191 9 [M+H-H2O-OCH3]+、m/z 369.168 8 [M+H-H2O-C3H6]+和m/z 415.210 2 [M+H-H2O]+处产生碎片离子, 表明它属于B型木脂素, C环上有羟基。经与对照品比对鉴定为五味子醇甲。化合物224在m/z 537.207 9 (C30H32O9) 处表现出[M-H]-离子, 在m/z 415.173 6、m/z 371.147 8产生特征离子片段[M+H-C6H5COOH]+、[M+H-C6H5COOH-C2H4O]+, 说明该化合物为C型木脂素, 故推测其为五味子酯甲。
降三萜类化合物是五味子的主要成分之一, 是一类结构新颖、高度氧化且骨架重排的三萜类化合物, 母核如图6B所示。本研究根据裂解规律及相关文献[38], 共鉴定出11个降三萜类成分。降三萜类化合物一般有内酯环和羟基取代。在正离子模式下内酯环裂解失去中性碎片CH2C(OH)2 (60 Da)、CH3CH=C(OH)2 (74 Da)、CO2 (44 Da) 等生成特征碎片离子[M+H-CH2C(OH)2]+、[M+H-CH3CH=C(OH)2]+或[M+H-CO2]+。结构中有羟基还会失去一分子水。根据多个中性丢失碎片信息, 快速识别11个降三萜类成分。
根据成分数据库精确质量数分子量匹配、文献对比, 共鉴定到6个特征离子归属性不强的成分, 以芳香族成分居多。
本文通过前体离子靶向识别技术结合诊断离子过滤策略, 对DZSMC的化学成分进行了系统分析。从DZSMC中鉴定出了248种化合物, 其中在负离子模式下检测到198个化合物, 在正离子模式下检测到50个化合物。这种差异主要源于各药材特征成分的电离特性: 灯盏细辛中的酚酸类和黄酮类、人参中的人参皂苷类, 以及麦冬中的甾体皂苷和高异黄酮类成分在负离子模式下具有更高的电离效率, 其一级和二级质谱均呈现较强的响应信号; 而五味子中的木脂素类及降三萜类成分则在正离子模式下表现出更优的质谱响应特性。本研究选取了16种代表性成分, 涵盖DZSMC中主要的5类化合物, 包括咖啡酰基奎宁酸类(绿原酸、异绿原酸A、异绿原酸C)、黄酮类(野黄芩苷、野黄芩素、灯盏甲素)、木脂素类(五味子醇甲、五味子甲素、戈米辛D)、甾体皂苷类(麦冬皂苷D) 以及人参皂苷类(人参皂苷Rg1等6种)。这些成分的选取不仅能够验证鉴定结果的准确性, 还可用于构建诊断离子库, 为后续全成分解析提供可靠的鉴定依据。
研究表明, 黄酮类化合物中的野黄芩苷能减轻小胶质细胞介导的神经炎症, 还能促进星形胶质细胞增生, 促进脑缺血组织的修复[39]; 人参皂苷类化合物如人参皂苷Rb1、人参皂苷Rg1、人参皂苷Rg3和人参皂苷CK等已被证明通过调节NF-κB等信号通路发挥抗炎作用[40]; 木脂素类化合物中的五味子醇乙可能通过抑制MAPKs信号通路来减弱神经炎症反应, 从而发挥神经保护作用[41]; 咖啡酰基奎宁酸类成分如3,5-二咖啡酰奎宁酸对缺血再灌注动物具有脑缺血保护、防止神经元损伤等作用[42]。以上研究提示, DZSMC中的活性成分可能通过协同作用, 共同发挥神经保护、抗炎和抗脑缺血损伤等多重药理作用。
本研究提出的前体离子靶向识别与诊断离子过滤相结合的数据鉴别策略, 相较于传统的数据依赖采集(DDA)、数据非依赖采集(DIA) 或全扫描筛选方法及同类诊断离子筛查方法[22, 43, 44], 在效率、特异性等方面均有显著优势: 首先, 基于Access软件与in-house质谱数据库进行快速相似性分析, 通过筛选DZSMC目标化合物的前体离子, 实现一级靶向降噪, 直接规避非目标离子峰的计算(如m/z 100以内的区间的背景信号), 显著减少背景噪声和共洗脱化合物的干扰。相较文献[22]的全扫描遍历策略(耗时通常超过10分钟/样本), 本方法通过DZSMC前体离子搜索将数据库匹配速度提升至 < 1分钟/样本, 数据冗余量减少80%。其次, 突破常规诊断离子筛查[44]的局限性, 基于16种中药对照品构建含母离子-多碎片离子组合的专属诊断离子库。目标物需同时满足前体离子匹配(Δm/z < 0.01) 及≥ 2个特征碎片离子的验证条件, 使假阳性率降至7.2%, 大幅提升鉴别的准确性。
本策略通过母离子靶向识别和诊断离子筛选两步过滤, 仅保留高置信度数据, 减少分析的数据量, 提高了鉴定效率。这一方法的特色在于将靶向分析的精准性与非靶向筛查的广覆盖性结合, 优先采集前体离子, 确保低丰度离子不被遗漏, 同时又保证准确度, 尤其适合复杂体系的化合物鉴别, 为中药化学成分分析研究提供了新思路。

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2025年第60卷第8期
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doi: 10.16438/j.0513-4870.2025-0108
  • 接收时间:2025-02-08
  • 首发时间:2026-09-20
  • 出版时间:2025-08-12
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  • 收稿日期:2025-02-08
  • 修回日期:2025-04-24
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    1广东药科大学中药学院, 广东 广州 510006
    2广东省中药质量工程技术研究中心, 广东 广州 510006
    3国家中医药管理局中药数字化质量评价技术重点研究室, 广东 广州 510006
    4广东药科大学药学院, 广东 广州 510006

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2种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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