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Updated: Jun 30, 2026

Chemotherapy-induced Vascular Toxicity - Real-time In vivo Imaging of Vessel Impairment
Published on: January 7, 2015
Systematic analysis of doxorubicin-induced myocardial injury mechanisms using network toxicology and molecular
Feng Jiang1, Zhen Zheng2, Kaitai Liu2
1Department of Cardiovascular Medicine, The Second Hospital of Yinzhou, Ningbo, Zhejiang Province, China.
Abstract:
To systematically investigate the molecular mechanisms of doxorubicin (DOX)-induced myocardial injury through network toxicology, molecular docking, and molecular dynamics simulations, aiming to identify critical molecular targets for reducing DOX's cardiotoxicity. Multiple databases were systematically mined to identify DOX-related targets. A protein-protein interaction network was constructed using STRING database and analyzed via Cytoscape. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using WebGestalt. Molecular docking simulations evaluated binding interactions between DOX and identified hub proteins, followed by 100 ns molecular dynamics simulations to assess complex stability. Results: Network analysis identified 5 critical hub genes (AKT1, TP53, EGFR, HIF1A, and BCL2) among 47 overlapping targets between DOX activity and myocardial injury pathways. Functional enrichment demonstrated significant involvement in cellular responses to oxidative stress, reactive oxygen species (ROS) metabolism, and membrane-associated processes. Molecular docking revealed strong binding interactions with energies from -5.2 to -7.8 kcal/mol. Molecular dynamics simulations confirmed varying complex stability, with EGFR showing superior stability (root mean square deviation [RMSD] = 0.1-0.4 nm), AKT1 and BCL2 displaying moderate fluctuations (~0.6 nm), and HIF1A and TP53 exhibiting greater conformational variability (0.6-0.7 nm). This integrated computational analysis provides insights into DOX-induced myocardial injury mechanisms. The identification of key targets and their differential binding stability with DOX establishes a foundation for developing targeted strategies to minimize cardiotoxicity while preserving therapeutic efficacy.
Insights
This study identifies key molecular targets like AKT1 and EGFR involved in doxorubicin-induced cardiotoxicity using computational methods. Findings pave the way for strategies to reduce heart damage from this chemotherapy drug.
Area of Science:
- Pharmacology
- Computational Biology
- Toxicology
Background:
- Doxorubicin (DOX) is a vital chemotherapy agent but causes significant cardiotoxicity.
- Understanding the molecular mechanisms of DOX-induced myocardial injury is crucial for mitigating its adverse effects.
Purpose of the Study:
- To systematically investigate the molecular mechanisms of doxorubicin-induced myocardial injury.
- To identify critical molecular targets for reducing doxorubicin's cardiotoxicity using network toxicology, molecular docking, and molecular dynamics simulations.
Main Methods:
- Systematic mining of multiple databases for DOX-related targets.
- Construction and analysis of a protein-protein interaction network using STRING and Cytoscape.
- Gene Ontology and KEGG pathway enrichment analysis via WebGestalt.
- Molecular docking and 100 ns molecular dynamics simulations to assess drug-target interactions and complex stability.
Main Results:
- Identified 5 critical hub genes (AKT1, TP53, EGFR, HIF1A, BCL2) involved in DOX-induced myocardial injury.
- Functional enrichment highlighted roles in oxidative stress, ROS metabolism, and membrane processes.
- Molecular docking showed strong binding interactions (-5.2 to -7.8 kcal/mol).
- Molecular dynamics simulations revealed differential complex stability, with EGFR being the most stable.
Conclusions:
- This integrated computational approach elucidates DOX-induced myocardial injury mechanisms.
- Key targets and their binding stability with DOX were identified.
- Provides a foundation for developing targeted strategies to minimize cardiotoxicity while maintaining therapeutic efficacy.

