Based on network pharmacology and molecular docking to predict the mechanism of Huangqi in the treatment of castration-resistant prostate cancer

Abstract

Background: As a kind of traditional Chinese medicine, HQ is widely mentioned in the treatment of cancerous diseases in China, which has been proven to have a therapeutic effect on cancerous diseases, such as prostate cancer. To predict the specific mechanism of HQ in the treatment of CRPC, we will conduct preliminary verification and discussion based on a comprehensive consideration of network pharmacology and molecular docking.

Methods: TCMSP was used to obtain the compounds and reach the effective targets of HQ. The targets of CRPC were reached based on GeneCards database and CTD database. GO and KEGG were utilized for the analysis of overlapping targets. The software of Openbabel was used to convert the formats of ligands and reporters. In addition, molecular docking studies were performed by using the software of Autodock Vina.

Result: It can be seen from the database results that there were 87 active compounds (20 key active compounds) in HQ, and 33 targets were screened out for CRPC treatment. GO and KEGG pathway enrichment analyses identified 81 significant GO terms and 24 significant KEGG pathways. There is a difference in terms of the expression of core protein between cancer patients and healthy people. The expression of core protein in patients also has an impact on the life cycle. The results of molecular docking showed that the docking activity of drug molecules and core proteins was better.

Conclusions: It is concluded from the results of this network pharmacology and molecular docking that HQ makes a multi-target and multi-biological process, and results in the multi-channel synergistic effect on the treatment of CRPC by regulating cell apoptosis, proliferation and metastasis, which still needs further verification by experimental research.

Fig 1. Venny diagram.

33 overlapped target genes were from three databases (TCMSP, CTD and GeneCards).

Fig 2. Compound–target network.

The Compound-target network of HQ. The blue circle is the compound and the purple triangle is the target protein.

Fig 3. PPI network.

33 overlapped target genes were used to constructed PPI network and hub genes in PPI network. The purple triangle is the target protein. The size of the triangle represents the weight of the target protein.

Fig 4. GO.

33 overlapped genes were analysis by GO annotation. BP/CC/MF are all shown in the figure, the specific meaning can be seen in the text under the bar graph.

Fig 5. KEGG.

33 overlapped genes was analysis by KEGG, which enriched in 24 pathways. The darker the color, the greater the weight, and the larger the circle, the greater the genenumber.

Fig 6. Prostate cancer pathway.

Prostate cancer pathway information generated by KEGG. The highlighted part of the pathways and protein nodes related to this research.

Fig 7. Immunohistochemistry.

The expressions of 5 targets in prostate tissues of cancer patients and normal people.

Fig 8. Survival analysis of five core proteins.

Survival analysis involves five core proteins. The blue line in the figure indicates the survival of prostate cancer patients whose targets had not changed. Non-blue lines show changes in the survival of prostate cancer patients with changed targets.

Fig 9. Survival analysis of AR.

Survival analysis involves AR gene. The blue line in the figure indicates the survival of prostate cancer patients whose targets had not changed. Non-blue lines show changes in the survival of prostate cancer patients with changed targets.

Fig 10. Core targets molecular docking.

Core targets molecular docking. The meaning of colors and graphics can be known from the legend.