ArticleScientific reports2023
System biology mediated assessment of molecular mechanism for sinapic acid against breast cancer: via network pharmacology and molecular dynamic simulation.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 17 citations in OpenAlex.
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- Sinapic Acid Ameliorates Doxorubicin-Induced Cardiotoxicity in H9c2 Cardiomyoblasts by Inhibiting Oxidative Stress Through Activation of the Nrf2 Signaling Pathway.Antioxidants (Basel, Switzerland) · 2025Article
- Physiological Mechanisms by Which the Functional Ingredients in Beer Impact Human Health.Molecules (Basel, Switzerland) · 2024Review
- Transethosomal gel for enhancing transdermal delivery of natural therapeutics.Nanomedicine (London, England) · 2024Review
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sinapic acid is a hydroxycinnamic acid widespread in the plant kingdom, known to be a potent anti-oxidant used for the treatment of cancer, infections, oxidative stress, and inflammation. However, the mode of action for its chemotherapeutic properties has yet not been unleashed. Hence, we aimed to identify potential targets to propose a possible molecular mechanism for sinapic acid against breast cancer. We utilized multiple system biology tools and databases like DisGeNET, DIGEP-Pred, Cytoscape, STRING, AutoDock 4.2, AutoDock vina, Schrodinger, and gromacs to predict a probable molecular mechanism for sinapic acid against breast cancer. Targets for the disease breast cancer, were identified via DisGeNET database which were further matched with proteins predicted to be modulated by sinapic acid. In addition, KEGG pathway analysis was used to identify pathways; a protein-pathway network was constructed via Cytoscape. Molecular docking was performed using three different algorithms followed by molecular dynamic simulations and MMPBSA analysis. Moreover, cluster analysis and gene ontology (GO) analysis were performed. A total of 6776 targets were identified for breast cancer; 95.38% of genes predicted to be modulated by sinapic acid were common with genes of breast cancer. The 'Pathways in cancer' was predicted to be modulated by most umber of proteins. Further, PRKCA, CASP8, and CTNNB1 were predicted to be the top 3 hub genes. In addition, molecular docking studies revealed CYP3A4, CYP1A1, and SIRT1 to be the lead proteins identified from AutoDock 4.2, AutoDock Vina, and Schrodinger suite Glide respectively. Molecular dynamic simulation and MMPBSA were performed for the complex of sinapic acid with above mentioned proteins which revealed a stable complex throughout simulation. The predictions revealed that the mechanism of sinapic acid in breast cancer may be due to regulation of multiple proteins like CTNNB1, PRKCA, CASP8, SIRT1, and cytochrome enzymes (CYP1A1 & CYP3A4); the majorly regulated pathway was predicted to be 'Pathways in cancer'. This indicates the rationale for sinapic acid to be used in the treatment of breast cancer. However, these are predictions and need to be validated and looked upon in-depth to confirm the exact mechanism of sinapic acid in the treatment of breast cancer; this is future scope as well as a drawback of the current study.
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