Exploring the Antipyretic Activity of Enicostemma axillare (Nahi): A Computational Approach

This study aims to perform the insilico analysis of Enicostemma axillare (Nahi) which are well-known for its antipyretic properties and investigate for its active compounds by using computational results with traditional application. Using network pharmacology, pharmacokinetic properties i.e. ADME (Absorption, Distribution, Metabolism, Excretion), tools for toxicity prediction and analyze, through this it evaluates bioactive compounds against specific molecular targets which linked with pyrexia. The therapeutic efficacy and safety of selected compounds for additional investigation were validated by ADME and toxicity tests. Bioinformatics databases such as IMPPAT, PubChem, SwissADME, and pkCSM are used to identify Nahi bioactive compounds, as well as their structural and pharmacokinetic properties. The bioactive compounds were screened for drug-likeness properties using Limpki’s Rule of 5, followed by target prediction and pathway enrichment analysis by using Swiss Target Prediction and KEGG pathway. The important connections were identified using visualization and network design tools i.e. Cytoscape 3.10.2. The binding affinity between the target and the bioactive compounds are identified using Autodock vina. The application of network pharmacology will give an in depth understanding of the plant's medicinal potential, which corresponds with Ayurveda's multi-target technique. This study emphasizes the value of combining traditional medicine into modern healthcare systems, encouraging innovation, and expanding treatment alternatives by showcasing the potential of Ayurvedic plants in current drug development.