Molecular docking, 3D structure-based pharmacophore modeling, and ADME prediction of alpha mangostin and its derivatives against estrogen receptor alpha

Abstract

Objective: The aims of this study are to identify the molecular interactions and the pharmacophore-fit of of α mangostin and its derivatives with estrogen receptor α (ERα) using computational simulation approaches to obtain new potent of anti-breast cancer. Materials and Methods: Molecular docking simulation and 3D structure-based pharmacophore models were employed to identify the molecular interactions of α-mangostin and its derivatives against estrogen receptor α (ERα) (PDB ID: 3ERT). Results: The results showed that the binding energy of α-mangostin and its best derivative (AMD10) were −9.05 kcal/mol and −11.89 kcal/mol, respectively. These compounds also interacted with Thr347, Asp351, Met388, Met528, Ile424, Arg394, and Glu353. The pharmacophore-fit scores of α-mangostin and AMD10 were 83.06% and 86.46%, respectively. In addition, the absorption, distribution, metabolism and excretion (ADME) properties were predicted. Conclusion: These results showed that α-mangostin and AMD10 are promising candidates of novel anti-breast-cancer agents with antagonistic activity to ERα.