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2015 ; 5
(ä): 17646
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Prediction and Characterisation of the System Effects of Aristolochic Acid: A
Novel Joint Network Analysis towards Therapeutic and Toxicological Mechanisms
#MMPMID26620132
Nie W
; Lv Y
; Yan L
; Chen X
; Lv H
Sci Rep
2015[Dec]; 5
(ä): 17646
PMID26620132
show ga
Aristolochic acid (AA) is the major active component of medicinal plants from the
Aristolochiaceae family of flowering plants widely utilized for medicinal
purposes. However, the molecular mechanisms of AA systems effects remain poorly
understood. Here, we employed a joint network analysis that combines network
pharmacology, a protein-protein interaction (PPI) database, biological processes
analysis and functional annotation analysis to explore system effects. Firstly,
we selected 15 protein targets (14 genes) in the PubChem database as the
potential target genes and used PPI knowledge to incorporate these genes into an
AA-specific gene network that contains 129 genes. Secondly, we performed
biological processes analysis for these AA-related targets using ClueGO, some of
new targeted genes were randomly selected and experimentally verified by
employing the Quantitative Real-Time PCR assay for targeting the systems effects
of AA in HK-2 cells with observed dependency of concentration. Thirdly, the
pathway-based functional enrichment analysis was manipulated using WebGestalt to
identify the mostly significant pathways associated with AA. At last, we built an
AA target pathway network of significant pathways to predict the system effects.
Taken together, this joint network analysis revealed that the systematic
regulatory effects of AA on multidimensional pathways involving both therapeutic
action and toxicity.