分析测试学报2026，Vol.45Issue(6)：1234-1244,11.DOI:10.12452/j.fxcsxb.26020502
基于UPLC-Q-TOF-MS/MS与Python算法的伤科接骨片成分自动解析
Automated Identification of Chemical Constituents in Shangke Jiegu Tablet Based on UPLC-Q-TOF-MS/MS and Python-based Algorithms
摘要
Abstract
Based on ultra-high performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry(UPLC-Q-TOF-MS/MS),this study developed an automated matching algorithm for the theoretical m/z values of characteristic fragment ions,utilizing NumPy matrix operations and Matplotlib visualization in Python.By integrating self-built databases of molecular formulas and char-acteristic fragment ions,the platform achieved rapid screening and automated identification of multi-component in Shangke Jiegu Tablet.The MS/MS fragmentation patterns of various compounds were systematically investigated and validated through comparison with the reference standards and litera-tures.A total of 77 compounds were identified,including 28 triterpenoids,16 saponins,9 amino acids,9 flavonoid glycosides,6 alkaloids,6 fatty acids,2 iridoid glycosides,and 1 pigment.Per-formance validation demonstrates that this Python algorithm achieves the detection rate of 100%,rela-tive standard deviations(RSDs)less than 3.0%,and false matching rate of 2.5%.This research pro-vides scientific data and technical support for the study of the pharmacodynamic material basis and quality evaluation of this traditional Chinese medicine prescription.关键词
伤科接骨片/超高效液相色谱-四极杆-飞行时间串联质谱/Python算法/成分自动解析/质谱裂解机理Key words
Shangke Jiegu Tablet/UPLC-Q-TOF-MS/MS/Python-based algorithm/automated identification of constituents/mass spectrometry fragmentation mechanism分类
化学化工引用本文复制引用
张新佳,王戟森,梅宇翔,周志刚,肖雪,章弘扬..基于UPLC-Q-TOF-MS/MS与Python算法的伤科接骨片成分自动解析[J].分析测试学报,2026,45(6):1234-1244,11.基金项目
中国仪器仪表学会科学仪器托举计划项目(CISTJ2024) （CISTJ2024）
国家药品监督管理局药品快速检验技术重点实验室开放课题(KF2022006) （KF2022006）
