Exploring the mechanism of avenanthramide in the treatment of atherosclerosis based on network pharmacology and molecular docking: An observational study

Atherosclerosis (AS) is a disease characterized by the buildup of fat and fibrous elements within the walls of arteries and is a primary factor in the occurrence of heart failure and mortality. The potential targets and mechanisms underlying the anti-atherosclerotic effects of avenanthramide (Avn) were investigated using network pharmacology, molecular docking, and molecular dynamics simulations. Target information for Avn A, B, and C was collected from the PubChem and Swiss Target Prediction databases. Potential therapeutic targets for AS were identified by mining the OMIM, DrugBank, DisGeNET, and GeneCards databases. A protein-protein interaction (PPI) network of shared targets was constructed and visualized using the STRING database and Cytoscape 3.9.1. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were conducted to explore the functions of core targets within the PPI network. Molecular docking was performed using the AutoDockTool to verify the correlation between the 3 types of Avns and the core targets. Furthermore, molecular dynamics simulations were performed using the 3 highest molecular docking binding energies to validate and confirm the binding of potent compounds to the target. The results revealed 109 respective targets for Avn, with 55 common targets identified by intersection with AS-related targets. Five pivotal genes, matrix metalloproteinase-9 (MMP9), epidermal growth factor receptor (EGFR), ICAM1, CASP3, and MMP2, were selected from the PPI network. Molecular docking results showed a strong binding affinity between Avn and MMP9 as well as EGFR. Molecular dynamics simulations showed good binding capacity of Avn A, B, and C with EGFR, validating the reliability of the molecular docking results. Avn potentially exerts its effects through multiple targets and displays anti-inflammatory and anti-oxidative stress properties.

Authors

Institutions

Publication Details

Journal
Medicine
Published
2024-12-20
DOI
https://doi.org/10.1097/md.0000000000040932
Citations
1
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.36
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploring the mechanism of avenanthramide in the treatment of atherosclerosis based on network pharmacology and molecular docking: An observational study

Meng Han, Kaifeng Liu, Yibei Zhan, Zhigang Wang et al.
1 citations
Medicine
Computational Drug Discovery Methods
0.36
article

Exploring the mechanism of avenanthramide in the treatment of atherosclerosis based on network pharmacology and molecular docking: An observational study

Meng Han, Kaifeng Liu, Yibei Zhan, Zhigang Wang, Fang Li, Yuanmei Zheng
article en
1 citations

Abstract

Atherosclerosis (AS) is a disease characterized by the buildup of fat and fibrous elements within the walls of arteries and is a primary factor in the occurrence of heart failure and mortality. The potential targets and mechanisms underlying the anti-atherosclerotic effects of avenanthramide (Avn) were investigated using network pharmacology, molecular docking, and molecular dynamics simulations. Target information for Avn A, B, and C was collected from the PubChem and Swiss Target Prediction databases. Potential therapeutic targets for AS were identified by mining the OMIM, DrugBank, DisGeNET, and GeneCards databases. A protein-protein interaction (PPI) network of shared targets was constructed and visualized using the STRING database and Cytoscape 3.9.1. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were conducted to explore the functions of core targets within the PPI network. Molecular docking was performed using the AutoDockTool to verify the correlation between the 3 types of Avns and the core targets. Furthermore, molecular dynamics simulations were performed using the 3 highest molecular docking binding energies to validate and confirm the binding of potent compounds to the target. The results revealed 109 respective targets for Avn, with 55 common targets identified by intersection with AS-related targets. Five pivotal genes, matrix metalloproteinase-9 (MMP9), epidermal growth factor receptor (EGFR), ICAM1, CASP3, and MMP2, were selected from the PPI network. Molecular docking results showed a strong binding affinity between Avn and MMP9 as well as EGFR. Molecular dynamics simulations showed good binding capacity of Avn A, B, and C with EGFR, validating the reliability of the molecular docking results. Avn potentially exerts its effects through multiple targets and displays anti-inflammatory and anti-oxidative stress properties.

MedicineVol. 103(51)
Hubei Polytechnic University (CN)
Good health and well-being
Openalex Percentile: Top 33%
Computational Drug Discovery Methods
0.36
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.