article · Computational and Structural Biotechnology Reports
The main goal of this research is to identify natural products from ConMedNP and SANCDB libraries targeting overexpressed estrogen receptor alpha (ERα) in breast cancer using molecular docking and molecular dynamics (MD) methods. A protein (PDB ID: 1G50) was selected for its unique co-crystallized inhibitor 17β-estradiol and a specific binding pocket with amino acid residues conducive to inhibiting agonist activity. After validating the docking protocol, we performed structure-based virtual screening via molecular docking and Molecular Mechanics Generalized Born Surface Area (MM-GBSA) binding affinity calculations, resulting in the identification of 20 hits. We conducted a detailed analysis of the top-scoring molecules using docking and MD simulations. Five molecules (BNG_UY_488, SANC00320, BNG_UY_243, ZTF_UY_260, and SAO_0001_1) emerged as lead candidates, demonstrating better performance than the 17β-estradiol (E2) inhibitor in both docking and MD simulations. Furthermore, we assessed the synthetic feasibility of these five compounds using SwissADME, revealing their ease of synthesis compared to the co-crystallized inhibitor.
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DOI: 10.1016/j.csbr.2025.100033
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