数字中医药（英文）2025，Vol.8Issue(2)：206-218,13.DOI:10.1016/j.dcmed.2025.05.007
TCMHTI:基于Transformer的青附蠲痹汤治疗类风湿关节炎的中药-靶点相互作用预测模型
TCMHTI:a Transformer-based herb-target interaction prediction model for Qingfu Juanbi Decoction in rheumatoid arthritis
摘要
Abstract
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.关键词
Transformer/青附蠲痹汤/类风湿关节炎/深度学习/网络药理学Key words
Transformer/Qingfu Juanbi Decoction/Rheumatoid arthritis/Deep learning/Network pharmacology引用本文复制引用
梁振忠,丁长松..TCMHTI:基于Transformer的青附蠲痹汤治疗类风湿关节炎的中药-靶点相互作用预测模型[J].数字中医药（英文）,2025,8(2):206-218,13.基金项目
General Program of the National Natural Science Foun-dation of China(82474352),and Natural Science Founda-tion of Hunan Province(2023JJ60124). （82474352）
