Objective To predict the potential targets of Qingfu Juanbi Decoction(青附蠲痹汤,QFJBD)in treating rheumatoid arthritis(RA)using an improved Transformer model and investigate the network pharmacological mechanisms und...Objective To predict the potential targets of Qingfu Juanbi Decoction(青附蠲痹汤,QFJBD)in treating rheumatoid arthritis(RA)using an improved Transformer model and investigate the network pharmacological mechanisms underlying QFJBD’s therapeutic effects on RA.Methods First,a traditional Chinese medicine herb-target interaction(TCMHTI)model was constructed to predict herb-target interactions based on Transformer improvement.The per-formance of the TCMHTI model was evaluated against baseline models using three metrics:area under the receiver operating characteristic curve(AUC),precision-recall curve(PRC),and accuracy.Subsequently,a protein-protein interaction(PPI)network was built based on the predicted targets,with core targets identified as the top nine nodes ranked by degree val-ues.Gene Ontology(GO)functional and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses were performed using the targets predicted by TCMHTI and the targets identified through network pharmacology method for comparison.Then,the re-sults were compared.Finally,the core targets predicted by TCMHTI were validated through molecular docking and literature review.Results The TCMHTI model achieved an AUC of 0.883,PRC of 0.849,and accuracy of 0.818,predicting 49 potential targets for QFJBD in RA treatment.Nine core targets were identified:tumor necrosis factor(TNF)-α,interleukin(IL)-1β,IL-6,IL-10,IL-17A,cluster of differentia-tion 40(CD40),cytotoxic T-lymphocyte-associated protein 4(CTLA4),IL-4,and signal trans-ducer and activator of transcription 3(STAT3).The enrichment analysis demonstrated that the TCMHTI model predicted 49 targets and enriched more pathways directly associated with RA,whereas classical network pharmacology identified 64 targets but enriched pathways showing weaker relevance to RA.Molecular docking demonstrated that the active molecules in QFJBD exhibit favorable binding energy with RA targets,while literature research further revealed that QFJBD can treat RA through 9 core targets.Conclusion The TCMHTI model demonstrated greater accuracy than traditional network pharmacology methods,suggesting QFJBD exerts therapeutic effects on RA by regulating tar-gets like TNF-α,IL-1β,and IL-6,as well as multiple signaling pathways.This study provides a novel framework for bridging traditional herbal knowledge with precision medicine,offering actionable insights for developing targeted TCM therapies against diseases.展开更多
Objective To study the mechanism of Qingfu Daotan(QFDT)Formula in improving polycystic ovary syndromeinsulin resistance(PCOS-IR)based on intestinal flora.Methods Totally 65 female SD rats with normal estrous cycle wer...Objective To study the mechanism of Qingfu Daotan(QFDT)Formula in improving polycystic ovary syndromeinsulin resistance(PCOS-IR)based on intestinal flora.Methods Totally 65 female SD rats with normal estrous cycle were divided into 6 groups according to the weight stratified randomization method:control group,PCOS-IR group,metformin group,QFDT-low dose group(QFDT-L),QFDT-normal dose group(QFDT-N),and QFDT-high dose group(QFDT-H).展开更多
基金General Program of the National Natural Science Foundation of China (82474352)Natural Science Foundation of Hunan Province (2023JJ60124)。
文摘Objective To predict the potential targets of Qingfu Juanbi Decoction(青附蠲痹汤,QFJBD)in treating rheumatoid arthritis(RA)using an improved Transformer model and investigate the network pharmacological mechanisms underlying QFJBD’s therapeutic effects on RA.Methods First,a traditional Chinese medicine herb-target interaction(TCMHTI)model was constructed to predict herb-target interactions based on Transformer improvement.The per-formance of the TCMHTI model was evaluated against baseline models using three metrics:area under the receiver operating characteristic curve(AUC),precision-recall curve(PRC),and accuracy.Subsequently,a protein-protein interaction(PPI)network was built based on the predicted targets,with core targets identified as the top nine nodes ranked by degree val-ues.Gene Ontology(GO)functional and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses were performed using the targets predicted by TCMHTI and the targets identified through network pharmacology method for comparison.Then,the re-sults were compared.Finally,the core targets predicted by TCMHTI were validated through molecular docking and literature review.Results The TCMHTI model achieved an AUC of 0.883,PRC of 0.849,and accuracy of 0.818,predicting 49 potential targets for QFJBD in RA treatment.Nine core targets were identified:tumor necrosis factor(TNF)-α,interleukin(IL)-1β,IL-6,IL-10,IL-17A,cluster of differentia-tion 40(CD40),cytotoxic T-lymphocyte-associated protein 4(CTLA4),IL-4,and signal trans-ducer and activator of transcription 3(STAT3).The enrichment analysis demonstrated that the TCMHTI model predicted 49 targets and enriched more pathways directly associated with RA,whereas classical network pharmacology identified 64 targets but enriched pathways showing weaker relevance to RA.Molecular docking demonstrated that the active molecules in QFJBD exhibit favorable binding energy with RA targets,while literature research further revealed that QFJBD can treat RA through 9 core targets.Conclusion The TCMHTI model demonstrated greater accuracy than traditional network pharmacology methods,suggesting QFJBD exerts therapeutic effects on RA by regulating tar-gets like TNF-α,IL-1β,and IL-6,as well as multiple signaling pathways.This study provides a novel framework for bridging traditional herbal knowledge with precision medicine,offering actionable insights for developing targeted TCM therapies against diseases.
文摘Objective To study the mechanism of Qingfu Daotan(QFDT)Formula in improving polycystic ovary syndromeinsulin resistance(PCOS-IR)based on intestinal flora.Methods Totally 65 female SD rats with normal estrous cycle were divided into 6 groups according to the weight stratified randomization method:control group,PCOS-IR group,metformin group,QFDT-low dose group(QFDT-L),QFDT-normal dose group(QFDT-N),and QFDT-high dose group(QFDT-H).
