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Li XL, Guo ZF, Wen XD, Li MN, Yang H. A molecular networking-assisted automatic database screening strategy for comprehensive annotation of small molecules in complex matrices. J Chromatogr A 2023; 1710:464417. [PMID: 37778098 DOI: 10.1016/j.chroma.2023.464417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 09/14/2023] [Accepted: 09/26/2023] [Indexed: 10/03/2023]
Abstract
Liquid chromatography-tandem with high-resolution mass spectrometry (LCHRMS) has proven challenging for annotating multiple small molecules within complex matrices due to the complexities of chemical structure and raw LCHRMS data, as well as limitations in previous literatures and reference spectra related to those molecules. In this study, we developed a molecular networking assisted automatic database screening (MN/auto-DBS) strategy to examine the combined effect of MS1 exact mass screening and MS2 similarity analysis. We compiled all previously reported compounds from the relevant literatures. With the development of a Python software, the in-house database (DB) was created by automatically calculating the m/z and data from experimental MS1 hits were rapid screened with DB. We then performed a feature-based molecular network analysis on the auto-MS2 data for supplementary identification of unreported compounds, including clustered FBMN and annotated GNPS compounds. Finally, the results from both strategies were merged and manually curated for correct structural assignment. To demonstrate the applicability of MN/auto-DBS, we selected the Huangqi-Danshen herb pair (HD), commonly used in prescriptions or patent medicines to treat diabetic nephropathy and cerebrovascular disease. A total of 223 compounds were annotated, including 65 molecules not previously reported in HD, such as aromatic polyketides, coumarins, and diarylheptanoids. Using MN/auto-DBS, we can profile and mine a wide range of complex matrices for potentially new compounds.
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Affiliation(s)
- Xin-Lu Li
- State Key Laboratory of Natural Medicines, China Pharmaceutical University, No. 24 Tongjia Xiang, Nanjing 210009, China
| | - Zi-Fan Guo
- State Key Laboratory of Natural Medicines, China Pharmaceutical University, No. 24 Tongjia Xiang, Nanjing 210009, China
| | - Xiao-Dong Wen
- State Key Laboratory of Natural Medicines, China Pharmaceutical University, No. 24 Tongjia Xiang, Nanjing 210009, China.
| | - Meng-Ning Li
- State Key Laboratory of Natural Medicines, China Pharmaceutical University, No. 24 Tongjia Xiang, Nanjing 210009, China.
| | - Hua Yang
- State Key Laboratory of Natural Medicines, China Pharmaceutical University, No. 24 Tongjia Xiang, Nanjing 210009, China.
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Xu S, Tan Y, Xia Y, Tang H, Li J, Tan N. Targeted characterization and guided isolation of chemical components in Scrophulariae Radix based on LC-MS. J Pharm Biomed Anal 2023; 235:115569. [PMID: 37557064 DOI: 10.1016/j.jpba.2023.115569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 07/07/2023] [Accepted: 07/09/2023] [Indexed: 08/11/2023]
Abstract
How to achieve rapid characterization and efficient isolation of chemical components from traditional Chinese medicines (TCMs) is what the researchers have been exploring. Herein, a strategy integrated diagnostic ion filtering (DIF) and selected ion recording (SIR)-based screen was firstly proposed and successfully applied for targeted characterization and guided isolation of the chemical components from Scrophulariae Radix, one of TCMs. After acquiring the Q-TOF-MS/MS untargeted data, 128 compounds were characterized based on DIF, a self-built database and comparison of the related literatures, in which 38 compounds were reported for the first time. Subsequently, the SIR method of UPLC-QqQ-MS/MS was adopted to guide the isolation of potential new compounds. Finally, three new compounds together with one known compound with the same skeleton were isolated, and unambiguously elucidated by NMR and acid hydrolysis. These results indicated that this integrated analytical approach is effective and reliable in targeted characterizing chemical components and isolating new compounds from the extract of Scrophulariae Radix.
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Affiliation(s)
- Siyi Xu
- Department of TCMs Pharmaceuticals, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 211198, PR China
| | - Yajie Tan
- Department of TCMs Pharmaceuticals, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 211198, PR China
| | - Yun Xia
- Jinling Pharmaceutical Co., Ltd., Nanjing 210009, PR China
| | - Haojun Tang
- Department of TCMs Pharmaceuticals, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 211198, PR China
| | - Jian Li
- Jinling Pharmaceutical Co., Ltd., Nanjing 210009, PR China.
| | - Ninghua Tan
- Department of TCMs Pharmaceuticals, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 211198, PR China.
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Wen JH, Guo AQ, Li MN, Yang H. A structural similarity networking assisted collision cross-section prediction interval filtering strategy for multi-compound identification of complex matrix by ion-mobility mass spectrometry. Anal Chim Acta 2023; 1278:341720. [PMID: 37709461 DOI: 10.1016/j.aca.2023.341720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 07/28/2023] [Accepted: 08/14/2023] [Indexed: 09/16/2023]
Abstract
Ion mobility coupled with mass spectrometry (IM-MS), an emerging technology for analysis of complex matrix, has been facing challenges due to the complexities of chemical structures and original data, as well as low-efficiency and error-proneness of manual operations. In this study, we developed a structural similarity networking assisted collision cross-section prediction interval filtering (SSN-CCSPIF) strategy. We first carried out a structural similarity networking (SSN) based on Tanimoto similarities among Morgan fingerprints to classify the authentic compounds potentially existing in complex matrix. By performing automatic regressive prediction statistics on mass-to-charge ratios (m/z) and collision cross-sections (CCS) with a self-built Python software, we explored the IM-MS feature trendlines, established filtering intervals and filtered potential compounds for each SSN classification. Chemical structures of all filtered compounds were further characterized by interpreting their multidimensional IM-MS data. To evaluate the applicability of SSN-CCSPIF, we selected Ginkgo biloba extract and dripping pills. The SSN-CCSPIF subtracted more background interferences (43.24%∼43.92%) than other similar strategies with conventional ClassyFire criteria (10.71%∼12.13%) or without compound classification (35.73%∼36.63%). Totally, 229 compounds, including eight potential new compounds, were characterized. Among them, seven isomeric pairs were discriminated with the integration of IM-separation. Using SSN-CCSPIF, we can achieve high-efficient analysis of complex IM-MS data and comprehensive chemical profiling of complex matrix to reveal their material basis.
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Affiliation(s)
- Jia-Hui Wen
- State Key Laboratory of Natural Medicines, China Pharmaceutical University, No. 24 Tongjia Xiang, Nanjing, 210009, China
| | - An-Qi Guo
- State Key Laboratory of Natural Medicines, China Pharmaceutical University, No. 24 Tongjia Xiang, Nanjing, 210009, China
| | - Meng-Ning Li
- State Key Laboratory of Natural Medicines, China Pharmaceutical University, No. 24 Tongjia Xiang, Nanjing, 210009, China.
| | - Hua Yang
- State Key Laboratory of Natural Medicines, China Pharmaceutical University, No. 24 Tongjia Xiang, Nanjing, 210009, China.
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Du Z, Wang H, Li X, Dong M, Chi B, Tian Z, Wang Z, Jiang H. Rapid screening and characterization of 2-(2-phenylethyl)chromones in agarwood by UHPLC-Q-Exactive Orbitrap-MS. Food Chem 2023; 424:136400. [PMID: 37236079 DOI: 10.1016/j.foodchem.2023.136400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 05/10/2023] [Accepted: 05/15/2023] [Indexed: 05/28/2023]
Abstract
The purpose of this study is to develop an improved comprehensive data filtering strategy, which was implemented primarily through the Microsoft Office platform's Excel software for rapid screening of potential 2-(2-phenylethyl)chromone (PEC) monomers and their dimers (PEC dimers) obtained from agarwood. A total of 108 PEC monomers and 30 PEC dimers in agarwood were characterized. In conclusion, the results obtained in this work could provide useful information for the future utilization of agarwood. In particular, it is the first time to conduct an in-depth analysis of the MS/MS fragmentation behavior of a large number of PEC monomers and PEC dimers, including the identification of substituent positions of them. The proposed data filtering strategy could improve the comprehensive characterization efficiency of complex components in spices.
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Affiliation(s)
- Zhen Du
- Innovation Institute of Chinese Medicine and Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan 250355, China
| | - Huanjun Wang
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan 250355, China
| | - Xueling Li
- College of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan 250355, China
| | - Meiyue Dong
- Innovation Institute of Chinese Medicine and Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan 250355, China
| | - Bingqing Chi
- College of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan 250355, China
| | - Zhenhua Tian
- Experimental Center, Shandong University of Traditional Chinese Medicine, Jinan 250355, China.
| | - Zhenguo Wang
- Shandong Provincial Key Laboratory of Traditional Chinese Medicine for Basic Research, Jinan 250355, China; State Key Laboratory, State Ministry of Education Key Laboratory, Jinan 250355, China.
| | - Haiqiang Jiang
- Innovation Institute of Chinese Medicine and Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan 250355, China; Shandong Provincial Key Laboratory of Traditional Chinese Medicine for Basic Research, Jinan 250355, China; Shandong Province Cardiovascular Disease TCM Precision Treatment Engineering Laboratory, China.
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Zhang W, Li WB, Wang Q, Liu XY, Liu YM, Huang HP, Hu B, Yin S, Wang YK. An innovative impurity profiling of Esmolol Hydrochloride Injection using UPLC-MS based multiple mass defect filter and chemometrics with in-silico toxicity prediction. ARAB J CHEM 2023. [DOI: 10.1016/j.arabjc.2023.104573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023] Open
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Wang SY, Liu H, Zhu JH, Zhou SS, Xu JD, Zhou J, Mao Q, Kong M, Li SL, Zhu H. 2,4-dinitrophenylhydrazine capturing combined with mass defect filtering strategy to identify aliphatic aldehydes in biological samples. J Chromatogr A 2022; 1679:463405. [DOI: 10.1016/j.chroma.2022.463405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 08/03/2022] [Accepted: 08/05/2022] [Indexed: 10/15/2022]
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