Objective: Excavate the medication rule of traditional Chinese medicine in the treatment of prostate cancer, and predicting the biomolecular level mechanism of high-frequency drug compatibility. Methods: Relevant docu...Objective: Excavate the medication rule of traditional Chinese medicine in the treatment of prostate cancer, and predicting the biomolecular level mechanism of high-frequency drug compatibility. Methods: Relevant documents in CNKI, Wanfang Medical Network and VIP Chinese Biomedical Periodical Database Pubmed, EMbase were collected and collated systematically. Frequency statistics, association rule analysis and new party mining were carried out using TCMISSV2.5. BATMAN-TCM was used to analyze the interaction relationship and related pathways between high-frequency drug targets. Results: Huangqi (Astragalus membranaceus) was the single drug most used of the 102prescriptions included in the standard. There are 6 pairs of combinations with high confidence in association rule analysis. System entropy cluster analysis resulted in 20 core drug combinations and 9 new prescriptions. Through KEGG pathway analysis of Huangqi, Fuling (Poria cocos), Gancao (Glycyrrhiza uralensis) and Dihuang (Rehmannia glutinosa), it was found that the number of potential targets of the neural active ligand receptor rented pathway and purine metabolism pathway was the largest. Conclusions: Prostate cancer is mainly treated with deficiency-tonifying drugs, which are combined with drugs for promoting blood circulation, removing blood stasis, clearing heat, promoting diuresis, detoxifying and resolving hard mass. The mechanism of action of high-frequency traditional Chinese medicine may be realized by interfering with the neuroactive ligand receptor interaction pathway and purine metabolism pathway.展开更多
基金the National Natural Science Foundation of Hebei (No.H2018201179)Hebei University of Science and Technology (No. QN2016077)Health and Family Planning Commission of Hebei (No. 20160388).
文摘Objective: Excavate the medication rule of traditional Chinese medicine in the treatment of prostate cancer, and predicting the biomolecular level mechanism of high-frequency drug compatibility. Methods: Relevant documents in CNKI, Wanfang Medical Network and VIP Chinese Biomedical Periodical Database Pubmed, EMbase were collected and collated systematically. Frequency statistics, association rule analysis and new party mining were carried out using TCMISSV2.5. BATMAN-TCM was used to analyze the interaction relationship and related pathways between high-frequency drug targets. Results: Huangqi (Astragalus membranaceus) was the single drug most used of the 102prescriptions included in the standard. There are 6 pairs of combinations with high confidence in association rule analysis. System entropy cluster analysis resulted in 20 core drug combinations and 9 new prescriptions. Through KEGG pathway analysis of Huangqi, Fuling (Poria cocos), Gancao (Glycyrrhiza uralensis) and Dihuang (Rehmannia glutinosa), it was found that the number of potential targets of the neural active ligand receptor rented pathway and purine metabolism pathway was the largest. Conclusions: Prostate cancer is mainly treated with deficiency-tonifying drugs, which are combined with drugs for promoting blood circulation, removing blood stasis, clearing heat, promoting diuresis, detoxifying and resolving hard mass. The mechanism of action of high-frequency traditional Chinese medicine may be realized by interfering with the neuroactive ligand receptor interaction pathway and purine metabolism pathway.
