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<p>Semiaquilegiae Radix demonstrates significant anti-inflammatory potential. However, comprehensive investigations into its anti-inflammatory effects remain sparse. This study seeks to systematically explore the chemical composition of Semiaquilegiae Radix and its underlying anti-inflammatory mechanisms utilizing Ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF–MS/MS), network pharmacology, and molecular docking techniques. Initially, the chemical constituents of Semiaquilegiae Radix were identified and characterized via UHPLC-Q-TOF–MS/MS. Subsequently, the relevant targets were predicted and screened through databases such as PharmMapper and SwissTargetPrediction, in conjunction with protein–protein interaction (PPI) network analysis. Next, Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genome (KEGG) enrichment analyses were performed using the Metascape platform. Eventually, molecular docking was carried out via AutoDock Vina and visualized results with PyMOL. From Semiaquilegiae Radix, 19 active compounds were identified, 18 showing activity against inflammation-related targets. 510 drug targets were identified, 188 of which intersected with inflammation-related targets and PPI network analysis pinpointed six core potential targets. These overlapping targets are involved in several critical signaling pathways, including the AGE-RAGE signaling pathway in diabetic complications and pathways related to lipid metabolism and atherosclerosis. Molecular docking showed the primary seven active compounds can effectively bind to key targets. This study elucidates the chemical constituents of Semiaquilegiae Radix and highlights its multi-compound, multi-target, and multi-pathway mechanisms of action against inflammation. This research method provides a robust theoretical foundation for further experimental validation and the development of novel anti-inflammatory therapies.</p>

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Exploring chemical constituents and anti-inflammatory mechanisms of Semiaquilegiae Radix via an integrated strategy combining UHPLC-Q-TOF–MS analysis, network pharmacology and molecular docking

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月8日

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  • Gengyi Shang,
  • Xun Gao,
  • Rong Guo,
  • Ying Zhang,
  • Chenfeng Zhang,
  • Yun Shi,
  • Kunming Qin

摘要

Semiaquilegiae Radix demonstrates significant anti-inflammatory potential. However, comprehensive investigations into its anti-inflammatory effects remain sparse. This study seeks to systematically explore the chemical composition of Semiaquilegiae Radix and its underlying anti-inflammatory mechanisms utilizing Ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF–MS/MS), network pharmacology, and molecular docking techniques. Initially, the chemical constituents of Semiaquilegiae Radix were identified and characterized via UHPLC-Q-TOF–MS/MS. Subsequently, the relevant targets were predicted and screened through databases such as PharmMapper and SwissTargetPrediction, in conjunction with protein–protein interaction (PPI) network analysis. Next, Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genome (KEGG) enrichment analyses were performed using the Metascape platform. Eventually, molecular docking was carried out via AutoDock Vina and visualized results with PyMOL. From Semiaquilegiae Radix, 19 active compounds were identified, 18 showing activity against inflammation-related targets. 510 drug targets were identified, 188 of which intersected with inflammation-related targets and PPI network analysis pinpointed six core potential targets. These overlapping targets are involved in several critical signaling pathways, including the AGE-RAGE signaling pathway in diabetic complications and pathways related to lipid metabolism and atherosclerosis. Molecular docking showed the primary seven active compounds can effectively bind to key targets. This study elucidates the chemical constituents of Semiaquilegiae Radix and highlights its multi-compound, multi-target, and multi-pathway mechanisms of action against inflammation. This research method provides a robust theoretical foundation for further experimental validation and the development of novel anti-inflammatory therapies.