图1 GSE89632数据集差异基因的火山图和热图

Fig.1 Volcano map and heat map of the differentially expressed genes (DEGs) in the GSE89632 dataset. A: Volcano map of the detected genes. Each point represents a gene. Blue dots represent down-regulated genes, and red dots represent up-regulated genes. The screening criteria for important genes are: |Log2FC|>1 and P.adj<0.05. B: Heat map of DEGs clustering. Blue indicates low expression and red indicates high expression.

图2 Scu的药效团靶网络

Fig.2 Pharmacophore target network of scutellarin. A: Drug-target network. Scutellarin is located at the center of the network. The potential therapeutic gene (PT gene) for treating MASLD is marked yellow. B: Intersecting DEGs obtained from GSE89632 as the target genes of scutellarin are considered to be the PT genes.

图3 GO功能富集分析

Fig.3 GO functional enrichment analysis. The top 5 are cellular components (CC), biological processes (BP), and molecular functions (MF). A: Rich in MASLD-related DEGs. B: Target gene of S-CU. C: Potential therapeutic genes (PT genes). D: Venn diagrams of GO for DEG and scutellarin (cell component). E: Venn diagrams of GO for DEG and scutellarin (biological process). F: Venn diagrams of GO for DEG and scutellarin (molecular function).

图4 KEGG通路富集分析前10名KEGG

Fig.4 Top 10 KEGGs in KEGG pathway enrichment analysis. A: MASLD-related DEGs. B: Target genes of scutellarin. C: Potential therapeutic genes (PT genes). D: Venn diagrams of the KEGG pathways in DEG and scutellarin.

图5 关键治疗基因(KT基因)筛选

Fig.5 Protein-protein interaction diagram of the key therapeutic gene screening. A: PT gene. B: The top 11 key genes calculated by cytoHubba. C: Analysis of the key module genes using MCODE.

图6 Scu与关键治疗基因(KT基因)蛋白质受体的分子对接

Fig.6 Molecular docking of scutellarin with the protein receptor of the key therapeutic genes. A: Molecular docking display diagram of MMP7. B: Molecular docking display diagram of MMP9. C: Molecular docking display diagram of LCN2. D: Molecular docking display diagram of SELE.

图7 Scu与MMP7的分子动力学模拟

Fig.7 Molecular dynamics simulation of scutellarin and MMP7. A: Root mean square deviation (RMSD) of the protein backbone over time, indicating stabilization after approximately 10 ns. B: Radius of gyration analysis of the protein complex, which stabilizes at 1.46 nm, suggesting a stable complex structure. C: Solvent accessible surface area (SASA) analysis of the complex, remaining stable at approximately 92.5 nm². D: Residue fluctuation analysis of MMP7, showing higher flexibility around residues 165 and 167. E: Hydrogen bond analysis between scutellarin and MMP7, showing an average number of 4.469 hydrogen bonds. F: Free energy landscape.

图8 Scu与LCN2的分子动力学模拟

Fig.8 Molecular dynamics simulation of scutellarin and LCN2. A: RMSD of the protein backbone over time, indicating stabilization after approximately 20 ns. B: Radius of gyration analysis of the protein complex, which stabilizes at 1.54 nm, suggesting a stable complex structure. C: SASA analysis of the complex, remaining stable at approximately 107 nm². D: Residue fluctuation analysis of LCN2, showing higher flexibility around residues 100 and 103. E: Hydrogen bond analysis between scutellarin and LCN2, showing an average number of 8.989 hydrogen bonds. F: Free energy landscape.

图9 Scu与MMP9的分子动力学模拟

Fig.9 Molecular dynamics simulation of scutellarin and MMP9. A: RMSD of the protein backbone over time, indicating stabilization after approximately 7 ns. B: Radius of gyration analysis of the protein complex, which stabilizes at 1.8 nm, suggesting a stable complex structure. C: SASA analysis of the complex, remaining stable at approximately 128 nm². D: Residue fluctuation analysis of MMP9, showing higher flexibility around residue 179. E: Hydrogen bond analysis between scutellarin and MMP9, with an average number of 4.48 hydrogen bonds. F: Free energy landscape.

图10 Scu与SELE的分子动力学模拟

Fig.10 Molecular dynamics simulation of scutellarin and SELE. A: RMSD of the protein backbone over time, indicating stabilization after approximately 7 ns. B: Radius of gyration analysis of the protein complex, which stabilizes at 1.8 nm, suggesting a stable complex structure. C: SASA analysis of the complex, remaining stable at approximately 98 nm². D: Residue fluctuation analysis of SELE, showing higher flexibility around residue 84. E: Hydrogen bond analysis between scutellarin and SELE, showing an average number of 4.46 hydrogen bonds. F: Free energy landscape.

图11 Scu对MASLD大鼠生化指标的影响

Fig.11 Effects of scutellarin on biochemical parameters in MASLD rats. A: Changes in liver-to-body weight ratio across different treatment groups. B: Effects of different scutellarin doses on liver function markers (ALT, AST, and ALP). C: Effects of different scutellarin doses on inflammatory cytokines (IL-1β, IL-6, and TNF-α). D: Effects of different scutellarin doses on serum lipid profiles (TG, TC, LDL, and HDL). E: Effects of different scutellarin doses on blood glucose, insulin levels, and insulin resistance. *P<0.05 vs Model. #P<0.05 vs Control.

图12 Scu对MASLD大鼠肝组织病理学改变的影响

Fig.12 Effects of scutellarin on histopathological alterations in liver tissues of MASLD rats. A: HE staining of liver sections from different treatment groups, showing a notable increase in fat vacuoles in the MASLD group, which was reduced following scutellarin treatment. B: Oil Red O staining of liver sections from different treatment groups, revealing severe hepatic steatosis in the MASLD group and obvious improvement after scutellarin treatment. C: Masson staining of liver sections from different treatment groups (scale bar=50 μm).

图13 Scu对MASLD大鼠肝组织MMP7和LCN2表达的影响

Fig.13 Effects of scutellarin on MMP7 and LCN2 expression in liver tissues of MASLD rats. A, B: qRT-PCR analysis of MMP7 and LCN2 mRNA expression levels in liver tissues from different treatment groups. C, D: Western blotting analysis of MMP7 and LCN2 protein expression levels in liver tissues from different treatment groups. #P<0.05 vs control group; *P<0.05 vs model group (n=10).