Determining novel candidate anti-hepatocellular carcinoma drugs using interaction networks and molecular docking between drug targets and natural compounds of SiNiSan
Background SiNiSan (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. Methods Th...
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PeerJ Inc.
2021-02-01
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| author | Qin Zhang Zhangying Feng Mengxi Gao Liru Guo |
| author_facet | Qin Zhang Zhangying Feng Mengxi Gao Liru Guo |
| author_sort | Qin Zhang |
| collection | DOAJ |
| description | Background SiNiSan (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. Methods The 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. Results A 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. Conclusions Our 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. |
| first_indexed | 2024-03-09T07:06:31Z |
| format | Article |
| id | doaj.art-ae2fa215e63e45fd993021140c4a05b5 |
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| issn | 2167-8359 |
| language | English |
| last_indexed | 2024-03-09T07:06:31Z |
| publishDate | 2021-02-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ |
| spelling | doaj.art-ae2fa215e63e45fd993021140c4a05b52023-12-03T09:30:52ZengPeerJ Inc.PeerJ2167-83592021-02-019e1074510.7717/peerj.10745Determining novel candidate anti-hepatocellular carcinoma drugs using interaction networks and molecular docking between drug targets and natural compounds of SiNiSanQin Zhang0Zhangying Feng1Mengxi Gao2Liru Guo3The Fourth Hospital of Hebei Medical University, Department of General Medicine, Shijiazhuang, Hebei, ChinaThe Fourth Hospital of Hebei Medical University, Department of Clinical Pharmacology, Shijiazhuang, Hebei, ChinaThe Fourth Hospital of Hebei Medical University, Department of General Medicine, Shijiazhuang, Hebei, ChinaThe Fourth Hospital of Hebei Medical University, Department of General Medicine, Shijiazhuang, Hebei, ChinaBackground SiNiSan (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. Methods The 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. Results A 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. Conclusions Our 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.https://peerj.com/articles/10745.pdfSiNiSanNetwork pharmacologyHepatocellular carcinomaMolecular docking |
| spellingShingle | Qin Zhang Zhangying Feng Mengxi Gao Liru Guo Determining novel candidate anti-hepatocellular carcinoma drugs using interaction networks and molecular docking between drug targets and natural compounds of SiNiSan PeerJ SiNiSan Network pharmacology Hepatocellular carcinoma Molecular docking |
| title | Determining novel candidate anti-hepatocellular carcinoma drugs using interaction networks and molecular docking between drug targets and natural compounds of SiNiSan |
| title_full | Determining novel candidate anti-hepatocellular carcinoma drugs using interaction networks and molecular docking between drug targets and natural compounds of SiNiSan |
| title_fullStr | Determining novel candidate anti-hepatocellular carcinoma drugs using interaction networks and molecular docking between drug targets and natural compounds of SiNiSan |
| title_full_unstemmed | Determining novel candidate anti-hepatocellular carcinoma drugs using interaction networks and molecular docking between drug targets and natural compounds of SiNiSan |
| title_short | Determining novel candidate anti-hepatocellular carcinoma drugs using interaction networks and molecular docking between drug targets and natural compounds of SiNiSan |
| title_sort | determining novel candidate anti hepatocellular carcinoma drugs using interaction networks and molecular docking between drug targets and natural compounds of sinisan |
| topic | SiNiSan Network pharmacology Hepatocellular carcinoma Molecular docking |
| url | https://peerj.com/articles/10745.pdf |
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