ArticleFrontiers in pharmacology2026
SPP1 and MMP1 as key therapeutic targets of Jingfang Granule in idiopathic pulmonary fibrosis: integrated bioinformatics and machine learning analysis.
Article in Frontiers in pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disease with limited therapeutic options. This study aims to identify potential efficacy biomarkers of Jingfang Granule (JFG) and investigate the therapeutic mechanism of its key active components against critical targets in IPF. Methods: IPF-related targets were identified through bioinformatics analysis of a public IPF dataset. Co-expressed gene modules were identified using Weighted Gene Co-expression Network Analysis (WGCNA). The JFG-PF interaction network was constructed employing protein-protein interaction (PPI) methods and functional enrichment analysis, which included Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Variation Analysis (GSVA). Additionally, five types of machine learning techniques were utilized to obtain diagnostic markers, which were further analyzed in immune infiltration assessments to evaluate their associations with immune cells and potential therapeutic effects. Molecular docking and molecular dynamics simulations were conducted to validate these analytical results. Finally, immunohistochemistry and immunofluorescence were used for verification. Results: A total of 3, 360 upregulated and 240 downregulated differentially expressed genes (DEGs) were identified in IPF sample. Integration of WGCNA findings with 1, 077 targets of JFG pinpointed 57 key genes lingking with IPF and JFG. Machine learning algorithms further refined this list, identifying four diagnostic markers:SPP1, MMP1, AKR1B10, and HTR2A. Immune infiltration analysis revealed that these biomarkers are significantly correlated with alterations in multiple immune cell populations within the IPF microenvironment. Molecular docking experiments strong binding affinities between the active compounds of JFG and these protein biomarkers. Subsequent Conclusion: The study identified four key genes as potential diagnostic markers for IPF and therapeutic targets for JFG. The finding preliminarily elucidate ther mechanisms of JFG in mitigating pulmonary fibrosis vis regulation of fibrotic pathways and the immune microenvironment, thereby providing an integrativeevidence chain for the development of novel-fibrotic therapeutic.
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