Piperlongumine

Ankylosing Spondylitis (AS) and Systemic Sclerosis (SSc) are both autoimmune diseases, albeit with distinct anatomical targets. AS primarily affects the spine and sacroiliac joints, triggering inflammation and eventual fusion of the vertebrae. SSc predominantly impacts the skin and connective tissues, leading to skin fibrosis, thickening, and potential damage to vital organs such as the lungs, heart, and kidneys. Despite their differing anatomical manifestations, inflammation serves as a pivotal factor in both conditions. Exploring the causes of the different pathogenesis of inflammation in AS and SSc could provide new insights into their treatment. We selected RNA-seq profiles of peripheral blood mononuclear cells (PBMCs) from the GEO datasets GSE73754 and GSE19617. DEGs were identified using the Limma R package with an adjusted p-value cutoff of < 0.05. Gene Ontology pathway analysis, SVM recursive feature elimination, and Gene Set Enrichment Analysis (GSEA) were conducted to analyze the DEGs. CIBERSORT was applied to estimate immune cell composition and its correlation with hub genes. Single-cell RNA sequencing data from peripheral blood mononuclear cells in the GSE194315 dataset were included to support differential expression analysis and biomarker identification. Additionally, single-cell RNA sequencing data from bone marrow blood samples were utilized to further validate these findings, offering complementary insights into biomarker expression across distinct sample types. A total of 762 DEGs were identified between AS patients and controls, and 441 DEGs between SSc patients and controls. Both conditions showed enrichment in the Natural killer cell mediated cytotoxicity pathway. ZSWIM6 and CCL3L3 were identified as potential biomarkers in AS and SSc, with significant diagnostic capabilities demonstrated by ROC analysis. Correlation analysis revealed associations between these biomarkers and specific immune cell types. The study utilizing ZSWIM6 and CCL3L3 as potential biomarkers provides deep insights into the distinct molecular mechanisms of SSc and AS. These findings lay the foundation for future research on targeted therapies and enhance our understanding of immune cell interactions in these autoimmune diseases.

This study aimed to identify the active components and related target pathways as well as examine the potential mechanisms of action of Sugemule-4 (SGML-4) for the treatment of insomnia, based on network pharmacology, molecular docking analysis, and molecular dynamics simulation. The active compounds of SGML-4 were retrieved from the Traditional Chinese Medicine Systems Pharmacology, Herbal Medicine Resource, and Encyclopedia of Traditional Chinese Medicine databases. Their potential targets were predicted using the SwissTargetPrediction platform, while known insomnia-related targets were gathered from GeneCards, Online Mendelian Inheritance in Man, Therapeutic Target Database, Drugbank, and PharmGKB. The intersection of compound-related targets was then determined. Next, a protein–protein interaction network was constructed and visualized using the STRING online platform and Cytoscape 3.10.3 software. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were conducted using the DAVID platform. Based on these analyses, key targets and the principal active compounds of Sugemule IV were selected for molecular docking studies using AutoDock software to evaluate their potential interactions. Finally, molecular dynamics simulations were conducted using GROMACS software to assess the stability of the protein–compound complexes. A total of 106 active compounds and 364 overlapping targets were identified. Luteolin, pinocembrin, piplartine, lysicamine, and apigenin showed the highest degree values, and AKT1, glyceraldehyde-3-phosphate dehydrogenase, tumor necrosis factor, albumin, and epidermal growth factor receptor (EGFR) were identified as core targets. Gene Ontology analysis indicated enrichment in chemical synaptic transmission and G protein-coupled receptor signaling. Kyoto Encyclopedia of Genes and Genomes analysis revealed serotonergic synapse and calcium signaling as major pathways. Molecular docking showed strong binding affinities between active compounds and targets, particularly EGFR, which formed stable hydrogen bonds. Molecular dynamics confirmed stable interactions of EGFR with apigenin, luteolin, and piplartine. SGML-4 exerts anti-insomnia effects through multi-target and multi-pathway mechanisms. Apigenin, luteolin, and piplartine are the core active components, and EGFR is identified as the central target, potentially acting through serotonergic synapses and calcium signaling pathways.