ArticlePeerJ2021
Determining novel candidate anti-hepatocellular carcinoma drugs using interaction networks and molecular docking between drug targets and natural compounds of SiNiSan.
Article in PeerJ, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 16 citations in OpenAlex.
- Review
- Bioactive aporphines and flavonoids from a fermented beverage target metabolic inflammatory pathways in obesity and type 2 diabetes.Scientific reports · 2025Article
- Integrative Investigation of Flavonoids Targeting YBX1 Protein-Protein Interaction Network in Breast Cancer: From Computational Analysis to Experimental Validation.Molecular biotechnology · 2025Article
- MCF-DTI: Multi-Scale Convolutional Local-Global Feature Fusion for Drug-Target Interaction Prediction.Molecules (Basel, Switzerland) · 2025Article
- Constructing a prognostic model for hepatocellular carcinoma based on bioinformatics analysis of inflammation-related genes.Frontiers in medicine · 2024Article
- A systematic study on the treatment of hepatitis B-related hepatocellular carcinoma with drugs based on bioinformatics and key target reverse network pharmacology and experimental verification.Infectious agents and cancer · 2023Article
- Molecular docking and in vitro experiments verified that kaempferol induced apoptosis and inhibited human HepG2 cell proliferation by targeting BAX, CDK1, and JUN.Molecular and cellular biochemistry · 2023Article
- Molecular and genetic markers in hepatocellular carcinoma:World journal of gastrointestinal pathophysiology · 2022Article
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4 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundSiNiSan (SNS) is an ancient traditional Chinese medicine (TCM) used to treat liver and spleen deficiencies. We studied the unique advantages of using SNS to treat hepatocellular carcinoma (HCC) with multiple components and targets to determine its potential mechanism of action.
methodsThe active compounds from the individual herbs in the SNS formula and their targets were mined from Traditional Chinese Medicine Systems Pharmacology Database (TCMSP). HCC-associated targets were collected from the TCGA and GEO databases and samples were collected from patients with stage III hepatocellular carcinoma. A compound-disease target network was constructed, visualized, and analyzed using Cytoscape software. We built a protein-protein interaction (PPI) network using the String database. We enriched and analyzed key targets using GSEA, GO, and KEGG in order to explore their functions. Autodock software was used to simulate the process of SNS molecules acting on HCC targets.
resultsA total of 113 candidate compounds were taken from SNS, and 64 of the same targets were chosen from HCC and SNS. The predominant targets genes were PTGS2, ESR1, CHEK1, CCNA2, NOS2 and AR; kaempferol and quercetin from SNS were the principal ingredients in HCC treatment. The compounds may work against HCC due to a cellular response to steroid hormones and histone phosphorylation. The P53 signaling pathway was significantly enriched in the gene set GSEA enrichment analysis and differential gene KEGG enrichment analysis.
conclusionsOur results showed that the SNS component has a large number of stage III HCC targets. Among the targets, the sex hormone receptors, the AR and ESR1 genes, are the core targets of SNS component and the most active proteins in the PPI network. In addition, quercetin, which has the most targets, can act on the main targets (BAX, CDK1, CCNB1, SERPINE1, CHEK2, and IGFBP3) of the P53 pathway to treat HCC.
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