基于UPLC-Q-TOF-MS/MS与Python算法的伤科接骨片成分自动解析OA

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.