Combinatorial Chemistry & High Throughput Screening

Author(s): Anlei Yuan, Chaoqun Liu, Wenqing Feng, Beiyan Li, Lulu Zheng, Jiaye Tian, Bin Yu and Yanling Zhang*

DOI: 10.2174/0113862073313394240430072032

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Integrating Network Pharmacology, Quantitative Metabolic Network Analysis, In Vitro Experiments, and Molecular Dynamics to Explore the Mechanism of Angelica Sinensis for Regulating Bone Metabolism

Page: [1054 - 1071] Pages: 18

  • * (Excluding Mailing and Handling)

Abstract

Background: Bone metabolic diseases are serious health issues worldwide. Angelica sinensis (AS) is traditionally used in Chinese medicine for treating bone metabolism diseases clinically. However, the mechanism of AS in regulating bone metabolism remains uncertain.

Objective: The current investigation was structured to elucidate the potential mechanisms of AS for modulating bone metabolism.

Methods: Firstly, targets of AS regulating bone metabolism were collected by network pharmacology. Then, the transcriptional regulation of RUNX2 was enriched as one of the key pathways for AS to regulate bone metabolism, constructing its metabolic network. Secondly, combining molecular docking, network efficiency, and network flux analyses, we conducted a quantitative evaluation of the metabolic network to reveal the potential mechanisms and components of AS regulating bone metabolism. Finally, we explored the effect of AS on the differentiation of osteoclasts from M-CSF and RANKL-induced RAW264.7 cells, as well as its impact on the osteogenic induction of MC3T3-E1 cells. We verified the mechanism and key targets of AS on bone metabolism using qRT-PCR. Furthermore, the key component was preliminarily validated through molecular dynamics simulation.

Results: Quantitative metabolic network of the transcriptional regulation of RUNX2 was constructed to illustrate the potential mechanism of AS for regulating bone metabolism, indicating that ferulic acid may be a pharmacological component of AS that interferes with bone metabolism. AS suppressed osteoclast differentiation in M-CSF and RANKL-induced RAW264.7 cells and reversed the expressions of osteoclastic differentiation markers, including RUNX2 and SRC. Additionally, AS induced osteogenic generation in MC3T3-E1 cells and reversed the expressions of markers associated with osteoblastic generation, such as RUNX2 and HDAC4. Molecular dynamics simulation indicated that ferulic acid had a strong binding affinity with HDAC4 and SRC.

Conclusion: This study reveals a systematic perspective on the intervention bone mechanism of AS by transcriptive regulation by RUNX2, guiding the clinical use of AS in treating diseases of the skeletal system.

Keywords: Angelica sinensis, bone metabolism, network pharmacology, quantitative metabolic network analysis, in vitro experiments, molecular dynamics.