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Prediction and Characterisation of the System Effects of Aristolochic Acid: A Novel Joint Network Analysis towards Therapeutic and Toxicological Mechanisms.

Nie W, Lv Y, Yan L, Chen X, Lv H - Sci Rep (2015)

Bottom Line: 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.Thirdly, the pathway-based functional enrichment analysis was manipulated using WebGestalt to identify the mostly significant pathways associated with AA.

View Article: PubMed Central - PubMed

Affiliation: Chongqing University Innovative Drug Research Centre, School of Chemistry and Chemical Engineering, Chongqing 401331, P.R. China.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus

AA-specific protein network.Green denotes genes that can directly associate with AA. Pink denotes genes that can indirectly associate with AA.
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f2: AA-specific protein network.Green denotes genes that can directly associate with AA. Pink denotes genes that can indirectly associate with AA.

Mentions: We retrieved 15 potential protein targets (14 target genes) from the PubChem database (see Table 1) and 115 candidate protein targets (target genes) from the STRING database. The 129 genes were globally evaluated using the STRING database to characterise the interactions among them. As a result, an AA-specific protein network was constructed using the STRING database and then visualised using Cytoscape. This network involved 129 gene and 1250 interactions (Fig. 2). All genes in this network can be either directly or indirectly associated with AA according to literature retrieval and relevant network analyses.


Prediction and Characterisation of the System Effects of Aristolochic Acid: A Novel Joint Network Analysis towards Therapeutic and Toxicological Mechanisms.

Nie W, Lv Y, Yan L, Chen X, Lv H - Sci Rep (2015)

AA-specific protein network.Green denotes genes that can directly associate with AA. Pink denotes genes that can indirectly associate with AA.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4664954&req=5

f2: AA-specific protein network.Green denotes genes that can directly associate with AA. Pink denotes genes that can indirectly associate with AA.
Mentions: We retrieved 15 potential protein targets (14 target genes) from the PubChem database (see Table 1) and 115 candidate protein targets (target genes) from the STRING database. The 129 genes were globally evaluated using the STRING database to characterise the interactions among them. As a result, an AA-specific protein network was constructed using the STRING database and then visualised using Cytoscape. This network involved 129 gene and 1250 interactions (Fig. 2). All genes in this network can be either directly or indirectly associated with AA according to literature retrieval and relevant network analyses.

Bottom Line: 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.Thirdly, the pathway-based functional enrichment analysis was manipulated using WebGestalt to identify the mostly significant pathways associated with AA.

View Article: PubMed Central - PubMed

Affiliation: Chongqing University Innovative Drug Research Centre, School of Chemistry and Chemical Engineering, Chongqing 401331, P.R. China.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus