Molecular dynamic simulation result

Background. Sepsis-induced lung injury (SLI) is a critical complication arising from sepsis. Although immune escape is a well-recognized mechanism in tumor immunology, its contribution to SLI pathogenesis remains unclear. This research sought to identify and validate immune escape-related hub genes in SLI using bioinformatics and in vivo methods, while also investigating potential therapeutic drugs.
Methods. Transcriptomic datasets (GSE15379, GSE23767, GSE52474, and GSE60088) from the GEO database were analyzed to find differentially expressed genes (DEGs). DEGs were cross-referenced with a selected immune escape gene set to identify immune escape-related DEGs (IE_DEGs). A protein-protein interaction network was constructed, followed by functional enrichment analysis. Three machine learning techniques—SVM-RFE, LASSO, and random forest—were employed to identify hub genes. Diagnostic performance was assessed using a nomogram model and ROC analysis. Additionally, immune infiltration, immune cell correlation, and differential expression analyses were performed. A mouse model of SLI was developed using cecal ligation and puncture (CLP), and hub gene expression was confirmed through H&E staining, immunohistochemistry (IHC), and qRT-PCR. Molecular docking and dynamics simulations were conducted with PyMOL 3.1, AutoDockTools-1.5.6, and GROMACS 2022.2 to evaluate the interactions between IRF1/TNFAIP3 proteins and corosolic acid (CA).
Results. Intersecting 569 DEGs with 182 immune escape-related genes yielded 11 IE_DEGs. Two hub genes, IRF1 and TNFAIP3, were consistently identified by all machine learning methods, were significantly upregulated in SLI, and showed strong predictive value in the diagnostic model. Immune infiltration analysis revealed the involvement of various immune cell populations in SLI and their correlation with the expression of these hub genes. In vivo validation demonstrated significant lung injury in CLP mice, with increased IRF1 and TNFAIP3 expression at protein and mRNA levels. Molecular docking and dynamics simulations demonstrated robust interactions between IRF1/TNFAIP3 and corosolic acid.
Conclusion. IRF1 and TNFAIP3 are crucial genes related to immune escape in SLI and could be valuable as biomarkers and targets for therapy. Corosolic acid represents a potential therapeutic candidate for SLI.