Network pharmacological evaluation of L.- an integrated approach of modern and ancient pharmacology.

L. is immensely valuable in pharmacology. Computational approach through network pharmacology has been attempted to understand lead molecules of Cressa and their interactions with multiple targets. The phytochemical components of methanolic extracts of Cressa leaves were identified using GC-MS analysis, revealing 16 compounds. Using the identified lead molecules, target proteins were predicted using SWISS-target prediction and were analyzed using Cytoscape. This led to the identification of 56 candidate protein targets, which were used to construct a network using CytoHubba, Centiscape, MCODE, and KEGG pathways. The STRING network was created using Cytoscape for analyzing protein-protein interactions, and the top 5 genes were chosen from a total of 12 algorithms in CytoHubba. The antioxidant effects of were investigated using 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity, which showed an increase in the trend activity of the plant extract with an inhibition percentage of 51.53 ± 0.003%. This was further validated by ferric reducing antioxidant power (FRAP) assay that resulted in an antioxidant activity of 6.64 µg/mL at a high concentration of 500 µg/mL. Molecular docking and simulation were performed to study the interaction of human cyclooxygenase-2 (PDB ID: 5KIR) with Cressa metabolites. 5KIR exhibited a higher interaction with methyl stearate, forming two H-bond interactions with Arg 120 and Tyr 355. Molecular dynamics simulation analysis confirmed the stability of the protein-ligand complex. The network pharmacology analysis of putative proteins obtained from revealed that the peroxisome proliferator-activated receptor gamma (PPARG) gene is found in numerous cancer pathways and can be inhibited.