Integrated Network Ethnopharmacology, Molecular Docking, and ADMET Analysis Strategy for Exploring the Anti-Breast Cancer Activity of Ayurvedic Botanicals Targeting the Progesterone Receptor

Abstract

Abstract Background: In women, breast cancer is currently among the most common cancers and the second major cause of cancer-related mortality. One therapeutic target for breast cancer is the progesterone receptor (PR), which can be inhibited by specific PR modulators. Methods: Current anti-cancer medications have notorious adverse effects. Consequently, an urgent need exists to identify less hazardous, more effective medicines with few to no adverse effects. One strategy uses ancient herbal remedies to create medications derived from nature. Herein, we used data from the Dr. Duke, IMPPAT, PubChem, Binding DB, UniProt, and DisGeNET databases to construct a network in Cytoscape 3.10.0. Through a polypharmacology approach, bioactives with similarity indices greater than 0.6 were screened and docked with the PR. The top ten ligands with good docking scores were further subjected to interaction analysis in AutoDock v.4.2 software. We additionally analyzed the ADMET properties of the phytochemicals. Results: Procurcumenol and alpha-turmerone exhibited superior interactions with PR, with binding affinities of −7.85 kcal/mol. All compounds met Lipinski’s rule of five and were effective ligands for the PR according to ADMET data analysis. Our findings suggest that procurcumenol and alpha-turmerone may serve as potential anti-breast cancer agents; specifically targeting the PR in breast cancer cells. Conclusion: Understanding of anti-breast cancer activity can be facilitated through experimental validation of network analysis and molecular docking findings.