Integrated network pharmacology and bioinformatics analysis reveals multi-target mechanisms of HeJie Shengfa Decoction against alopecia areata
Abstract
Background: Alopecia areata (AA) is a common non-scarring autoimmune disease with a complex pathogenesis, high recurrence rates, and difficulty in achieving a cure. Recent years have seen an increasing focus on both clinical and basic research regarding AA. Hejie Shengfa Decoction (HSD), a traditional Chinese medicine formula, has shown certain efficacy in the clinical treatment of AA, though its underlying mechanisms remain unclear.
Methods: In this study, we retrieved the active ingredients of HSD and their associated targets from public databases. We then identified AA-related targets through bioinformatics analysis of publicly available AA datasets. A protein-protein interaction (PPI) network was constructed to generate the HSD-AA action network by integrating drug-specific targets and disease-related targets. Functional enrichment analysis was subsequently performed. To further investigate key genes, three machine learning algorithms-least absolute shrinkage and selection operator (LASSO) regression, support vector machine-recursive feature elimination (SVM-RFE), and Random Forest-were applied Additionally, immune cell infiltration analysis was carried out to examine the roles of these key genes in the local immune microenvironment. Molecular docking and molecular dynamics simulations were employed to assess the binding stability of the active ingredients with the core targets.
Results: The results revealed that HSD contains 96 active ingredients and 985 related…
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