The FP-growth Algorithm Based Compatibility Of Traditional Chinese Medicine Antiviral Prescription And Optimization Of Network Pharmacology Method

Object: There is great research value and significance on knowledge discovery and compatibility law from the antiviral traditional Chinese medicine prescriptions,that is could provide medication guidelines for rational clinical prescription and promote the development of new drugs from traditional Chinese medicine.The mechanism of action of TCM molecules in human body was analyzed by network pharmacology,and the bioactive compounds and mechanism of huanglian jiedu decoction in cancer treatment were discussed.Method: Based on this crucial point,the exploratory studies are carried on the compatibility laws of 961 pretreated antiviral traditional Chinese medicine prescriptions,which are based on the Frequent Pattern-growth(FP-growth)algorithm without generating candidate items.In this study,the FP tree is constructed by utilizing the data set firstly;then the frequent item sets are established and the association rules are extracted from the FP tree;finally,the frequency and association rules are analyzed according to the dosage forms(decoction,pill,paste and ingot).Herbal medicines constituents were screened by Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP).Constructed network by Cytoscape.Target prediction and selection used Pharm Mapper and Uni Prot KB database.Clue GO a Cytoscape plug-in was used to decipher functionally grouped gene ontology and pathway networks.Pathway-disease annotated and analysis on Kyoto Encyclopedia of Genes and Genomes(KEGG)database and then constructed Pathways-Targets network.The target-pathway was analyzed by FP-growth algorithm.Results: The main and core drug combinations of decoction,pill,cream and tablet were obtained.In the decoction,the drug combination with the highest frequency and high confidence is licorice-gardenia-scutellaria baicalensis,while the corresponding drug combination of pill is ginger-jujube-licorice,the drug combination of paste is scutellaria baicalensis-habitat-hornbill horn,and the drug combination of lozenges is scutellaria-gypsum-licorice.A total of 85 bioactive components were screened out and 225 targets were predicted.Of the 22 pathways identified,17 were associated with cancer.Target-pathway frequent item set 34 with frequency greater than 10.There were 12 groups with confidence greater than 50%.Conclusion: The experiment results show that the FP-growth algorithm has good performance especially has the strong generalization and robustness in the application of data mining on the large scale traditional Chinese medicine prescriptions.Moreover,the exploratory study demonstrate there exist obvious differences in the main and core herbs of combination decoction,pill,paste and tablet four formulations,and it also verified the significance and necessity of the different dosage formulation and preparation naturally.This study reveals the main bioactive constituents and mechanism of Huanglian Jiedu decoction for treatment of cancer and verified the characteristics of multi-components,multi-targets,and integral regulation for Huanglian Jiedu decoction based on network pharmacology.This paper can provide references for development of anti-cancer and the discovery of qualitymarkers of Huanglian Jiedu decoction for anti-cancer.