Computers in biology and medicine · 2025
Computational network toxicology of non-nutritive sweeteners in ulcerative colitis: From Aspartame-MMP9 interaction to mechanism-guided intervention.
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Feng Yubin, Huang Shiyuan, Huang Ziyan, Luo Lianxiang
Аннотация
BACKGROUND: Non-nutritive sweeteners (NNS), including aspartame, sucralose, and saccharin, are widely consumed globally. Ulcerative colitis (UC) manifests as epithelial barrier dysfunction accompanied by complex metabolic and immune system remodeling. However, the mechanistic link between NNS exposure and UC, along with clinically interpretable biomarkers, remains unclear.
METHODS: We integrated NNS ADMET properties and aggregated targets from six chemogenomic resources. Subsequently we scored 114 metabolic pathways using ssGSEA and classified metabolic reprogramming subtypes via consensus clustering. Network-based prioritization and cross-evidence triangulation were conducted using STRING/CytoHubba/MCODE analysis, GO/KEGG enrichment analysis, and C-T-P-D mapping. Multi-model integration (GMM-LR, DNN) based on interpretable models identified MMP9 as a prioritized core target, which was validated in independent cohorts. Immune deconvolution (CIBERSORT) and CellChat quantified MMP9's role in immune signaling remodeling. Docking with MMP-9 (PDB: 8K5Y) and 100 ns molecular dynamics simulations explored binding mechanisms.
RESULTS: NNS exhibit unique ADMET characteristics. Through intersection analysis, we ultimately identified 104 core proteins shared across these compounds. Ulcerative colitis was classified into barrier-dominant (MBC1) and inflammation-dominant (MBC2) metabolic subtypes. Forty-eight cross-gene sets enrich multiple inflammatory pathways, with the MMP9/HRAS pathway exhibiting highest priority. The optimal GMM-LR model demonstrated generalization across three cohorts. High-MMP9 samples exhibited marked immune infiltration, with high-MMP9 macrophages acting as signaling hubs. Docking ranked aspartame higher, while MD indicated marimastat is more conformationally stable and aspartame is more flexible.
CONCLUSION: Based on the computationally predicted aspartame-MMP9 interaction, MMP9 emerges as a potential molecular axis linking non-nutritive sweetener exposure to ulcerative colitis.
METHODS: We integrated NNS ADMET properties and aggregated targets from six chemogenomic resources. Subsequently we scored 114 metabolic pathways using ssGSEA and classified metabolic reprogramming subtypes via consensus clustering. Network-based prioritization and cross-evidence triangulation were conducted using STRING/CytoHubba/MCODE analysis, GO/KEGG enrichment analysis, and C-T-P-D mapping. Multi-model integration (GMM-LR, DNN) based on interpretable models identified MMP9 as a prioritized core target, which was validated in independent cohorts. Immune deconvolution (CIBERSORT) and CellChat quantified MMP9's role in immune signaling remodeling. Docking with MMP-9 (PDB: 8K5Y) and 100 ns molecular dynamics simulations explored binding mechanisms.
RESULTS: NNS exhibit unique ADMET characteristics. Through intersection analysis, we ultimately identified 104 core proteins shared across these compounds. Ulcerative colitis was classified into barrier-dominant (MBC1) and inflammation-dominant (MBC2) metabolic subtypes. Forty-eight cross-gene sets enrich multiple inflammatory pathways, with the MMP9/HRAS pathway exhibiting highest priority. The optimal GMM-LR model demonstrated generalization across three cohorts. High-MMP9 samples exhibited marked immune infiltration, with high-MMP9 macrophages acting as signaling hubs. Docking ranked aspartame higher, while MD indicated marimastat is more conformationally stable and aspartame is more flexible.
CONCLUSION: Based on the computationally predicted aspartame-MMP9 interaction, MMP9 emerges as a potential molecular axis linking non-nutritive sweetener exposure to ulcerative colitis.