Computational analysis of Annona muricata phytochemicals for targeted modulation of endocrine networks in polycystic ovary syndrome

Abstract

Polycystic ovarian syndrome (PCOS) is a complex reproductive disorder involving dysfunction across multiple hormonal pathways. Current pharmaceutical treatments use a simplistic single-target approach and overlook molecular interactions. This study provides a novel computational perspective revealing the promising potential of the medicinal fruit Annona muricata to target multiple receptors and modulate interconnected hormonal pathways implicated in PCOS. Molecular modeling and evaluations were done on three protein receptors involved in hormonal imbalance. The proteins were taken from the RCSB Protein Data Bank with IDs 1A28, 2AM9, and 3RUK. Over 50% of phytochemicals from Annona muricata were predicted to have binding affinities comparable to reference compounds. Docking and multi-parameter modeling using AutoDock Tools ranked the ligands, identified multi-target active compounds across all three receptors, and analyzed ligand interactions for the multiplex selected two compounds. The ADMETox properties of these phytochemicals were also analyzed. The results demonstrated various ligands with remarkable binding affinities for progesterone, androgen, and abiraterone receptor architectures matching or exceeding native standards, implying possible efficacy for coordinately modulating these interconnected hormonal sites. Detailed structural mapping of emodin and coclaurin uncovered conserved non-covalent interaction patterns, notably hydrogen bonding networks, facilitating the ligands’ competitive receptivity and deep projection into dysfunctionally upregulated pockets. The in-silico modeling provides early proof of concept that the herbal remedy A. muricata could inspire advanced "green" therapeutics for PCOS through multiplex modulation of interconnected hormonal receptors.