A Network Pharmacology-Based Strategy for Predicting Active Ingredients and Potential Targets of Talinum portulacifolium in Treating Diabetes
Abstract
Diabetes was a significant healthcare burden that severely impacts patients' quality of life. Its complex pathophysiological mechanisms, combined with limited available data, made effective management challenging and placed a substantial economic strain on healthcare systems. As researchers explored alternative treatment options, plant-based remedies gained attention for their potential therapeutic benefits. Among them, Talinum portulacifolium emerged as a promising candidate, with several in vitro studies demonstrating its effectiveness against diabetes. In the present study, the mechanism of action and anti-diabetic activity of T. portulacifolium were explored through network pharmacology. Phytoconstituents were sourced from literature and databases, including SwissADME and ADMET lab 3.0. Disease genes and targets of phytoconstituents were collected from GeneCards and SwissTargetPrediction, respectively. Common targets were determined through the application of a bioinformatic Venn as well as biological pathways, functional enrichment evaluations. Additionally, network construction was created in the form of a PPI network. The certain compounds performed a crucial role in diabetes development by influencing important genes. Through the application of network pharmacology analysis, Talinum portulacifolium was determined to display a potential preventive effect on diabetes by regulating diabetes-related signalling pathways. These results gave important information about the inherent mechanisms behind its anti-diabetic effect as well as supporting its potential as an herbal therapeutic drug for the treatment of diabetes
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