ArticleChinese medicine2021
The combination of UHPLC-HRMS and molecular networking improving discovery efficiency of chemical components in Chinese Classical Formula.
Article in Chinese medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 21 citations in OpenAlex.
- Revealing the Pharmacological Mechanism of Tibetan Medicine Wugeng San in Treating Rheumatoid Arthritis Through an Integrated Strategy of Chemical Composition Analysis, Network Pharmacology, Machine Learning, and In Vivo Experiments.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Rapid Analysis of the Chemical Composition of Xiaoban Kangfu Capsules Based on UHPLC-Q-Exactive Orbitrap MS/MS Combined with Molecular Networks.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Safety of NADES Extract ofMolecules (Basel, Switzerland) · 2025Article
- Analysis of Three Species ofInternational journal of molecular sciences · 2023Article
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- Natural products provide a new perspective for anti-complement treatment of severe COVID-19: a review.Chinese medicine · 2021Review
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9 authors at 3 institutions in 1 country.
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Abstract
backgroundIt is essential to identify the chemical components for the quality control methods establishment of Chinese Classical Formula (CCF). However, CCF are complex mixture of several herbal medicines with huge number of different compounds and they are not equal to the combination of chemical components from each herb due to particular formula ratio and preparation techniques. Therefore, it is time-consuming to identify compounds in a CCF by analyzing the LC-MS/MS data one by one, especially for unknown components.
methodsAn ultra-high pressure liquid chromatography-linear ion trap-orbitrap high resolution mass spectrometry (UHPLC-LTQ-Orbitrap-MS/MS) approach was developed to comprehensively profile and characterize multi-components in CCF with Erdong decoction composed of eight herbal medicines as an example. Then the MS data of Erdong decoction was analyzed by MS/MS-based molecular networking and these compounds with similar structures were connected to each other into a cluster in the network map. Then the unknown compounds connected to known compounds in a cluster of the network map were identified due to their similar structures.
resultsBased on the clusters of the molecular networking, 113 compounds were rapidly tentative identification from Erdong decoction for the first time in the negative mode, which including steroidal saponins, triterpenoid saponins, flavonoid O-glycosides and flavonoid C-glycosides. In addition, 10 alkaloids were tentatively identified in the positive mode from Nelumbinis folium by comparison with literatures.
conclusionMS/MS-based molecular networking technique is very useful for the rapid identification of components in CCF. In Erdong decoction, this method was very suitable for the identification of major steroidal saponins, triterpenoid saponins, and flavonoid C-glycosides.
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