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

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.

The Impact of p53 on Aristolochic Acid I-Induced Gene Expression In Vivo

“…Previous in vivo work showed that Nf-κb and members of its pathway are upregulated in AAI-exposed kidneys [29]. NF-κB also plays a role in the inflammatory response associated with AAN [63]. Overall, these findings may indicate that a Trp53(-/-) genotype confers a survival advantage to AAI-exposed renal cells and/or an inflammatory response is initiated in injured Trp53(-/-) kidneys.…”

“…AAN is characterised by fibrosis [62], thus it could be postulated that AAI contributes to this phenomenon by inducing EMT. In fact, previous studies showed that AAI-induced upregulation of transforming growth factor β (TGF-β), which acts on EMT pathways, contributes to the formation of renal fibrosis in AAN [63][64][65].…”

“…Whole-exome sequencing revealed BRCA2 mutations in urothelial cancers associated with AA exposure [83,84]. Furthermore, previous work showed that BRCA1 can interact with DNA repair and cell cycle genes modulated by AAI [63]. It may be that Brca genes drive DNA repair pathways in response to AAI treatment.…”

Endocrine disrupting chemicals and COVID-19 relationships: a computational systems biology approach

“…This integrative approach can be easily applied as a new approach methodology (NAM) ( Bopp et al 2019 ), which may offer support to methods alternative to animal testing or to identify biological pathways that require more focused laboratory study. Previous studies have demonstrated that systems chemical toxicology models combined with computational network biology may help in understanding chemical toxicity in humans ( Hartung et al 2017 ; Nie et al 2015 ; Taboureau and Audouze 2017 ). Our tripartite network supports the notion that exposure to EDCs may contribute to aggravation of COVID-19.…”

Systems pharmacology to investigate the interaction of berberine and other drugs in treating polycystic ovary syndrome

“…In contrast to previous methods, systems pharmacology provides an integrated “systems-level” approach to determi-ning mechanisms of action of drugs in animal models and in patients28. Systems pharmacology is widely used in drug discovery, target prediction and mechanism research, especially in traditional herbal medicine3132. This article applies systems pharmacology to investigate the mechanism of berberine and its interaction with other clinical drugs in treating PCOS at the target level.…”