中国中药杂志2026，Vol.51Issue(11)：3067-3079,13.DOI:10.19540/j.cnki.cjcmm.20260309.901
基于液质联合下的生物信息学和机器学习探究养阴益肺通络丸改善特发性肺纤维化的作用机制
Investigating on mechanism of Yangyin Yifei Tongluo Pills in improving idiopathic pulmonary fibrosis based on bioinformatics and machine learning combined with UHPLC-Q Exactive Orbitrap-HRMS
摘要
Abstract
Idiopathic pulmonary fibrosis(IPF)is a fatal interstitial lung disease with limited clinical therapeutic options.Traditional Chinese medicine formulas,characterized by multi-component,multi-target,and holistic regulatory properties,have shown unique potential in the prevention and treatment of IPF.Yangyin Yifei Tongluo Pills(YF)is a TCM formula with demonstrated clinical efficacy.However,its modern pharmacological mechanism against IPF remains to be systematically elucidated.In this study,ultra-high-performance liquid chromatography coupled with quadrupole-Orbitrap high-resolution mass spectrometry(UHPLC-Q Exactive Orbitrap-HRMS)was employed to identify the chemical constituents of YF.A total of 76 potential bioactive compounds were characterized,including flavonoids,phenylpropanoids and other chemicals.By integrating network pharmacology and bioinformatics analyses,drug-related targets,IPF-associated targets,differentially expressed genes,and WGCNA-derived key module genes were intersected,yielding 15 potential targets.Based on a systematic evaluation using nine machine learning algorithms,arginase 1(ARG1)and matrix metalloproteinase 14(MMP14)were identified as key core targets.Gene Ontology and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses indicated that these targets were mainly involved in inflammatory regulation,signal transduction,and extracellular matrix(ECM)remodeling,with significant enrichment in key signaling pathways such as the TNF signaling pathway.Immune microenvironment analysis revealed that the expression levels of ARG1 and MMP14 were closely associated with immune and stromal cell infiltration characteristics.Molecular docking demonstrated favorable binding affinities between ARG1/MMP14 and several core components,including miltirone,peimine,cryptotanshinone,and sec-O-glucosylhamaudol,while molecular dynamics simulations further confirmed the conformational stability of miltirone and sec-O-glucosylhamaudol,as core potential bioactive components,with the targets under dynamic conditions.Collectively,these findings suggest that YF may exert anti-IPF effects by targeting ARG1 and MMP14 through its core potential bioactive components,synergistically modulating key processes including the immune microenvironment,fibroblast activation,and extracellular matrix remodeling.By integrating LC-MS,bioinformatics,machine learning,immune infiltration analysis,molecular docking,and molecular dynamics simulation,this study systematically elucidates the multi-component and multi-target mechanisms of YF,providing new insights and a foundation for the intervention and treatment of IPF and the mechanistic study of TCM formulas.关键词
特发性肺纤维化/养阴益肺通络丸/生物信息学/机器学习/超高效液相色谱-四极杆轨道阱高分辨质谱Key words
idiopathic pulmonary fibrosis/Yangyin Yifei Tongluo Pills/bioinformatics/machine learning/ultra-high-performance liquid chromatography coupled with quadrupole-Orbitrap high-resolution mass spectrometry(UHPLC-Q Exactive Orbitrap-HRMS)引用本文复制引用
文科涵,赵琪,郭奥杰,吴秩超,夏霄霖,陈乐乐,徐泳,肖娜..基于液质联合下的生物信息学和机器学习探究养阴益肺通络丸改善特发性肺纤维化的作用机制[J].中国中药杂志,2026,51(11):3067-3079,13.基金项目
江苏省高等学校基础科学(自然科学)研究面上项目(24KJB360009) （自然科学）
