| Literature DB >> 31594914 |
Yin Zhang1, Xiaoyan Li2, Xianlin Xu1, Ningxi Yang3.
Abstract
BACKGROUND Paeonia lactiflora is the main active ingredient of peony decoction, which is used to treat ulcerative colitis (UC) in traditional Chinese medicine (TCM). Network pharmacology indicates the multiple interactions among genes, proteins, and metabolites associated with diseases and drugs from the network perspective, which shows the multi-component and multi-target attributes of TCM. This study predicted the pharmacological mechanism of Paeonia lactiflora in the treatment of UC by network pharmacological method. MATERIAL AND METHODS Chemical constituents of Paeonia lactiflora were searched from TCMSP data, gene names of target sites were extracted from UniProt database, and disease targets of ulcerative colitis were obtained from the CTD disease database. Use Venny online tools to obtain common targets for drugs and diseases. The DAVID database was used to enrich GO and KEGG for the common target, and the related functions and pathways were obtained. Cytoscape 3.7.1 was used to construct the 'drug-compound-target-disease' network. RESULTS There are 70 common target genes between Paeonia lactiflora and UC. GO analysis showed that the biological functions of the common target genes of Paeonia lactiflora and UC include response to lipopolysaccharide, response to estradiol, response to drug, positive regulation of nitric oxide biosynthetic process, and steroid hormone-mediated signaling pathway. Enrichment of the KEGG signaling pathway mainly involves signaling pathways, including Pathways in cancer, TNF signaling pathway, Tuberculosis, Hepatitis B, and Toxoplasmosis. CONCLUSIONS The network pharmacology intuitively shows the multi-component, multi-target, and multi-channel pharmacological effects of Paeonia lactiflora on UC, and provides a scientific basis for studying the mechanism of the effect of Paeonia lactiflora on UC.Entities:
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Year: 2019 PMID: 31594914 PMCID: PMC6798801 DOI: 10.12659/MSM.917695
Source DB: PubMed Journal: Med Sci Monit ISSN: 1234-1010
Compounds in Paeonia lactiflora.
| Mol ID | Molecule name | OB (%) | DL |
|---|---|---|---|
| MOL000492 | (+)-catechin | 54.83 | 0.24 |
| MOL001919 | (3S,5R,8R,9R,10S,14S)-3,17-dihydroxy-4,4,8,10,14-pentamethyl-2,3,5,6,7,9-hexahydro-1H-cyclopenta[a]phenanthrene-15,16-dione | 43.56 | 0.53 |
| MOL001910 | 11alpha,12alpha-epoxy-3beta-23-dihydroxy-30-norolean-20-en-28,12beta-olide | 64.77 | 0.38 |
| MOL001928 | Albiflorin_qt | 66.64 | 0.33 |
| MOL001930 | Benzoyl paeoniflorin | 31.27 | 0.75 |
| MOL000358 | beta-sitosterol | 36.91 | 0.75 |
| MOL000422 | Kaempferol | 41.88 | 0.24 |
| MOL001921 | Lactiflorin | 49.12 | 0.8 |
| MOL000211 | Mairin | 55.38 | 0.78 |
| MOL001918 | Paeoniflorgenone | 87.59 | 0.37 |
| MOL001924 | Paeoniflorin | 53.87 | 0.79 |
| MOL001925 | Paeoniflorin_qt | 68.18 | 0.4 |
| MOL000359 | Sitosterol | 36.91 | 0.75 |
Figure 1Venn diagram of disease and drug targets.
GO functional enrichment analysis of common targets (top 10).
| Biological processes | GO ID | Related targets | FDR |
|---|---|---|---|
| Response to lipopolysaccharide | 0032496 | OPRM1, VCAM1, CASP3, CYP1A1, CASP9, PTGS2, JUN, CASP8, SLPI, CYP1A2, LBP, SELE | 9.99E-08 |
| Response to estradiol | 0032355 | CASP3, CASP9, PTGS2, SLC6A4, CASP8, ESR1, F7, CAT, CYP1A2, GSTP1 | 1.90E-07 |
| Response to drug | 0042493 | ICAM1, CASP3, IL6, CYP1A1, PTGS2, SLC6A2, JUN, BCL2, RELA, SLC6A4, PPARG, ADRA1A, CAT, STAT1 | 4.40E-07 |
| Positive regulation of nitric oxide biosynthetic process | 0045429 | OPRM1, AKT1, ICAM1, IL6, PTGS2, ESR1, INSR | 3.38E-05 |
| Steroid hormone mediated signaling pathway | 0043401 | PGR, NR1I3, NR1I2, RXRA, PPARG, NR3C2, ESR1 | 1.93E-04 |
| Aging | 0007568 | VCAM1, AKT1, IL6, CYP1A1, CASP9, RELA, JUN, ADRA1A, CAT | 5.98E-04 |
| Cellular response to lipopolysaccharide | 0071222 | ICAM1, IL6, RELA, MAPK8, LBP, NOS2, CD14, GSTP1 | 6.43E-04 |
| Xenobiotic metabolic process | 0006805 | CYP3A4, NR1I2, CYP1B1, PTGS1, CYP1A2, GSTP1, AHR | 4.00E+00 |
| Response to toxic substance | 0009636 | CYP1B1, BAX, BCL2, SLC6A4, PON1, GSTP1, AHR | 1.00E+00 |
| Positive regulation of transcription from RNA polymerase II promoter | 0045944 | AR, IL6, RXRA, RELA, PPARG, ESR1, STAT1, AHR, PGR, AKT1, ADRB2, NR1I3, NR1I2, NCOA2, JUN, PPP3CA, IKBKB | 3.00E+00 |
Figure 2GO functional enrichment. The X-axis represents the number of genes enriched in function, the y-axis GO function annotation, and the color represents the significance of enrichment. The bluer the color, the higher the significance.
KEGG functional enrichment analysis of common targets (top 10).
| Term | Fold enrichment | Related targets | FDR |
|---|---|---|---|
| hsa05200: Pathways in cancer | 5.739 | PRKCA, AR, IL6, PTGS2, RXRA, RELA, PPARG, STAT1, MMP1, AKT1, CASP3, CASP9, JUN, BAX, BCL2, CASP8, MAPK8, NOS2, IKBKB, GSTP1 | 4.45E-07 |
| hsa04668: TNF signaling pathway | 12.647 | VCAM1, AKT1, ICAM1, CASP3, IL6, PTGS2, RELA, JUN, CASP8, MAPK8, IKBKB, SELE | 1.69E-06 |
| hsa05152: Tuberculosis | 8.9197 | AKT1, CASP3, IL6, CASP9, BCL2, RELA, BAX, CASP8, MAPK8, LBP, PPP3CA, NOS2, STAT1, CD14 | 3.06E-06 |
| hsa05161: Hepatitis B | 10.11 | PRKCA, IL6, RELA, STAT1, AKT1, CASP3, CASP9, BCL2, BAX, JUN, CASP8, MAPK8, IKBKB | 3.49E-06 |
| hsa05145: Toxoplasmosis | 11.277 | AKT1, CASP3, CASP9, RELA, BCL2, CASP8, MAPK8, ALOX5, NOS2, IKBKB, STAT1 | 3.40E-05 |
| hsa04620: Toll-like receptor signaling pathway | 10.639 | AKT1, IL6, RELA, JUN, CASP8, MAPK8, LBP, IKBKB, STAT1, CD14 | 3.26E-04 |
| hsa04932: Non-alcoholic fatty liver disease (NAFLD) | 8.2151 | AKT1, CASP3, IL6, RELA, JUN, RXRA, BAX, CASP8, MAPK8, IKBKB, INSR | 6.91E-04 |
| hsa04210: Apoptosis | 14.551 | AKT1, CASP3, CASP9, RELA, BAX, BCL2, CASP8, IKBKB | 0.001105 |
| hsa05164: Influenza A | 7.1292 | PRKCA, AKT1, ICAM1, IL6, CASP9, RELA, JUN, PRSS1, MAPK8, IKBKB, STAT1 | 0.002545 |
| hsa05204: Chemical carcinogenesis | 11.277 | GSTM1, CYP3A4, GSTM2, CYP1B1, CYP1A1, PTGS2, CYP1A2, GSTP1 | 0.006317 |
Figure 3KEGG pathway enrichment.
Figure 4Drug-compound-target-disease network map.