Integrative in silico analysis to explore the potential of Zingiberaceae compounds to inhibit estrogen receptor alpha activity in breast cancer

Abstract

The estrogen receptor alpha (ERα) is a critical player in breast cancer progression, making it a key target for therapeutic development. This study employed an advanced computational method to discover potential inhibitors of ERα from a library of compounds from the Zingiberaceae family. The workflow includes virtual screening, re-docking, molecular dynamics (MD) simulations, radius of gyration (RG), and root mean-square deviation (RMSD)-based free energy landscape (FEL) analysis. This multifaceted strategy led to the selection of four compounds with superior docking scores compared to established control molecules. The MD simulation assessments confirmed that these selected compounds exhibited robust stability and favorable binding interactions within the ERα binding pocket. Notably, the pocket volume analysis of the minimum energy structures obtained from FEL analysis indicated a significant reduction in volume compared to the initial docking poses, suggesting a more compact and potentially more effective binding conformation. These findings highlight the potential of Zingiberaceae family-derived compounds as promising candidates for ERα inhibition. The stability of these interactions and the observed compactness of the binding pocket, as demonstrated by our comprehensive computational analysis, underscore the potential of these compounds for further preclinical evaluation.