Elucidating the therapeutic mechanisms of Angelica dahurica in knee osteoarthritis: An integrative network pharmacology and molecular docking approach

• Multi-target mechanism : Angelica dahurica interacts with multiple targets (e.g., AR, BCL2, ESR1, PLAU, PRKCA, PTGS1, PTGS2) involved in critical pathways such as NF-kappa B signaling and VEGF signaling. • Functional enrichment : The identified targets are involved in biological processes related to inflammation, apoptosis, and angiogenesis, suggesting a comprehensive therapeutic effect. • Molecular docking validation : The strong binding affinities of key compounds to their targets validate the network pharmacology predictions and support the potential therapeutic efficacy of Angelica dahurica in KOA. This study aims to elucidate the molecular mechanisms underlying the therapeutic effects of Angelica dahurica in knee osteoarthritis (KOA) using an integrated network pharmacology and molecular docking approach. Active compounds of Angelica dahurica were identified using the TCMSP database, and their potential targets were retrieved from Traditional Chinese Medicine Systems Pharmacology (TCMSP) and UniProt databases. KOA-related targets were obtained from GeneCards. Shared targets were identified using Jvenn, and a "compound-target" interaction network was constructed using Cytoscape. Protein-protein interactions (PPIs) were analyzed via Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and functional enrichment analysis was performed using (RoSS Ihaka and Robert Gentleman) R software. Molecular docking studies were performed for key compounds (β-sitosterol and prangenidin) with their respective targets. Twenty active compounds targeting 62 distinct proteins were identified, with key compounds including β-sitosterol and prangenidin. Thirteen shared targets were identified between Angelica dahurica and KOA, including AR, BCL2, ESR1, PLAU, PRKCA, PTGS1, PTGS2, and VEGFA. Angelica dahurica significantly modulates pathways such as the NF-κB signaling pathway and the VEGF signaling pathway. Key compounds exhibited strong binding affinities to their targets, with docking scores below -6 kcal/mol, indicating strong and favorable binding affinities. Angelica dahurica demonstrates potential in managing KOA through a multi-component, multi-target, and multi-pathway approach. This study provides a solid foundation for further experimental validation and mechanistic investigations into the therapeutic effects of Angelica dahurica against KOA.

Authors

Institutions

Publication Details

Journal
Current Proteomics
Published
2025-04-01
DOI
https://doi.org/10.1016/j.curpro.2025.100017
Primary Topic
Inflammatory mediators and NSAID effects
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Elucidating the therapeutic mechanisms of Angelica dahurica in knee osteoarthritis: An integrative network pharmacology and molecular docking approach

Jiayong Liang, Bailin Feng, Hui Cheng, Zhenming Liang et al.
Current Proteomics
Inflammatory mediators and NSAID effects
article

Elucidating the therapeutic mechanisms of Angelica dahurica in knee osteoarthritis: An integrative network pharmacology and molecular docking approach

Jiayong Liang, Bailin Feng, Hui Cheng, Zhenming Liang, Xiaofeng Cai, Di Li, X. Luo, Huan Zhong, Rui Xie
article en

Abstract

• Multi-target mechanism : Angelica dahurica interacts with multiple targets (e.g., AR, BCL2, ESR1, PLAU, PRKCA, PTGS1, PTGS2) involved in critical pathways such as NF-kappa B signaling and VEGF signaling. • Functional enrichment : The identified targets are involved in biological processes related to inflammation, apoptosis, and angiogenesis, suggesting a comprehensive therapeutic effect. • Molecular docking validation : The strong binding affinities of key compounds to their targets validate the network pharmacology predictions and support the potential therapeutic efficacy of Angelica dahurica in KOA. This study aims to elucidate the molecular mechanisms underlying the therapeutic effects of Angelica dahurica in knee osteoarthritis (KOA) using an integrated network pharmacology and molecular docking approach. Active compounds of Angelica dahurica were identified using the TCMSP database, and their potential targets were retrieved from Traditional Chinese Medicine Systems Pharmacology (TCMSP) and UniProt databases. KOA-related targets were obtained from GeneCards. Shared targets were identified using Jvenn, and a "compound-target" interaction network was constructed using Cytoscape. Protein-protein interactions (PPIs) were analyzed via Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and functional enrichment analysis was performed using (RoSS Ihaka and Robert Gentleman) R software. Molecular docking studies were performed for key compounds (β-sitosterol and prangenidin) with their respective targets. Twenty active compounds targeting 62 distinct proteins were identified, with key compounds including β-sitosterol and prangenidin. Thirteen shared targets were identified between Angelica dahurica and KOA, including AR, BCL2, ESR1, PLAU, PRKCA, PTGS1, PTGS2, and VEGFA. Angelica dahurica significantly modulates pathways such as the NF-κB signaling pathway and the VEGF signaling pathway. Key compounds exhibited strong binding affinities to their targets, with docking scores below -6 kcal/mol, indicating strong and favorable binding affinities. Angelica dahurica demonstrates potential in managing KOA through a multi-component, multi-target, and multi-pathway approach. This study provides a solid foundation for further experimental validation and mechanistic investigations into the therapeutic effects of Angelica dahurica against KOA.

Current ProteomicsVol. 22(2)
Guangdong Medical College (CN), Soochow University (CN), Affiliated Hospital of Guangdong Medical College Hospital (CN)
Openalex Percentile: Top 75%
Inflammatory mediators and NSAID effects
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.