Network toxicology combined with molecular docking technology to explore the molecular mechanism of amatoxin causing liver injury

小桶 肝损伤 生物信息学 计算生物学 药理学 基因 生物信息学 癌症研究 生物 基因本体论 生物化学 基因表达
作者
Chenglin Wang,Xin Wang,Yaxing Deng,Yingchun Hu,Hu Li
出处
期刊:Scientific Reports [Nature Portfolio]
卷期号:15 (1): 26068-26068 被引量:9
标识
DOI:10.1038/s41598-025-11720-5
摘要

As one of the most toxic molecules in the fungal kingdom, amatoxin exhibit exceptional thermal stability and acid resistance. Once ingested, these compounds are rapidly absorbed and transported unimpeded to vital organs. They disrupt cellular metabolism by inhibiting nucleic acid and protein synthesis in target organs, ultimately causing hepatic and renal necrosis. Without prompt intervention, this molecular sabotage can progress to multiorgan failure and death. Early diagnosis combined with aggressive therapeutic measures is crucial for mitigating acute hepatic damage and significantly improving survival outcomes. This study aims to elucidate the molecular mechanisms underlying amatoxin-induced hepatic injury and establish a theoretical framework for targeted therapeutic interventions. Computational toxicology approaches utilizing ProTox-3.0 and ADMETlab 2.0 platforms were employed to characterize amatoxin's toxicological profile. Target prediction was performed through STITCH and SwissTargetPrediction databases, while liver injury-associated targets were identified from GeneCards, OMIM, and TTD repositories. The intersectional targets underwent systematic bioinformatics analysis, including protein-protein interaction (PPI) network construction, Gene Ontology (GO) annotation, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Molecular docking simulations were subsequently conducted to characterize three-dimensional binding conformations between amatoxin and core target proteins. Computational screening identified 11 potential amatoxin targets using STITCH and SwissTargetPrediction databases. Parallel interrogation of GeneCards, OMIM, and TTD repositories yielded 1,730 liver injury-related genes. Venn diagram analysis pinpointed SP1 and CNR1 as consensus molecular targets at the amatoxin-hepatic injury interface. PPI network topology revealed critical nodal connections, while functional enrichment analyses delineated key biological processes and signaling pathways associated with these targets. Molecular docking simulations demonstrated high-affinity binding between amatoxin and both SP1 and CNR1, suggesting direct mechanistic interactions. Amatoxin likely exerts hepatotoxic effects through direct binding to the core molecular targets SP1 and CNR1, thereby perturbing downstream transcriptional regulation and disrupting critical signaling cascades, ultimately culminating in hepatic necrosis.
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