Network pharmacology study to reveal underlying mechanisms, targets, and bioactives of Aralia cordata against obesity

AbstractAralia cordata (AC) has been used as anti-obesity herbal plants by Chinese, Japanese, and Korean, but its active chemical constituents, mechanism(s), and targets have not been documented completely. We aimed to investigate significant phytochemicals, pathways, and targets of AC against obesity via network pharmacology. The phytochemicals from AC were identified by Gas Chromatography –Mass Spectrometry (GC–MS) and were screened subsequently by Lipinski’s rule. The compound–target relationships were retrieved by analyzing SwissTargetPrediction, SEA search server. Then, obesity-related targets were identified by public bioinformatics and final overlapping targets were sele cted by Venn diagram. Next, we constructed and visualized protein-to-protein-interaction networks, bubble chart, and pathways–targets–compounds networks by RPackage. Furthermore, we utilized the Autodock Tools to perform molecular docking test on the bioactives and key targets to validate the ne twork pharmacological results. We confirmed a total of 43 compounds from AC via GC–MS and 40 final targets regarding obesity. The protein-to-protein-interaction networks analysis revealed IL6 as a key target, and a bubble chart showed that inactivation of Insulin resistance might be the uppermost pathway for anti-obesity. We identified that the AC phytochemicals was contributed to synergistic effects (multi-pathway, multi-target) to alleviate obesity through pathways–targets–compounds analysis...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - Category: Bioinformatics Source Type: research