Abstract

Nyctanthes arbor-tristis, commonly known as Parijat, is recognized for its significant antioxidant properties and various therapeutic applications. Recent studies have leveraged network pharmacology techniques to discover the main phytoconstituents in Nyctanthes arbor-tristis that may be able to alter the activity of important therapeutic targets implicated in oxidative stress and associated pathological processes. With an emphasis on its antiproliferative and antioxidant properties, this study combines computational methods to identify putative bioactive compounds and their relationships with important antioxidant enzymes and pathways, offering insights into the plant's potential to fight diseases brought on by oxidative stress. Using a variety of internet databases and software tools, the phytoconstituents of Nyctanthes arbor-tristis and their oxidative stress-related therapeutic targets were found. To determine if the found phytoconstituents were suitable as possible therapeutic agents, they underwent a drug-likeness study and were assessed for a number of pharmacokinetic characteristics. Targets exhibiting superior topological parameters and phytoconstituents with favorable pharmacokinetic profiles and drug-likeness properties were further examined using molecular docking studies and MMGBSA calculation to assess their binding affinities and interaction stability. In this investigation, 144 phytoconstituents were found in Nyctanthes arbor-tristis. Pharmacokinetic and drug-likeness tests were successfully completed by 103 of the 144 phytoconstituents that were discovered. For these chosen phytoconstituents, a total of 2192 therapeutic targets were discovered, along with 1823 oxidative stress-related disease-associated targets. Forty-four common targets were found when phytoconstituent targets and disease-associated targets intersected. The Cytoscape 3.9.1 program was used to assess topological metrics, including degree centrality and betweenness centrality, which led to the identification of five important proteins as top targets: SOD1, CAT, GPx1, Nrf2, and COX-2. Based on MMGBSA analysis and molecular docking experiments, beta-sitosterol is the most promising candidate since it has the best docking scores (-9.1 kcal/mol) and binding free energy across antioxidant (SOD1, CAT, GPx1, Nrf2) and antiproliferative (COX-2) targets.