Pharmacophore-Based 3D-QSAR Studies of Aromatase Inhibitors

Abstract

In the present study, a ligand-based 3D-QSAR pharmacophore model have been developed by considering 73 structurally diverse classes of heterocyclic compounds (IC₅₀ = 0.0077-100 μM) such as 2-phenylpyrroloquinolin-4-ones, 7-phenyl-3H-pyrrolo[3,2-f]quinolinones, 5,4'-diamino-6,8,3'-trifluoroflavones, plumbagin and N¹-(flavon-7-yl)amidrazone derivatives which were found to have potent cytotoxic activity against MCF-7 cell lines (breast cancer cell lines) to understand the structural requirements for effective binding with the aromatase enzyme to design a series of new potent and selective aromatase inhibitors (AIs). The 3D-QSAR pharmacophore hypotheses AADRR.22 with survival score = 3.774 was found to be statistically most significant (SD = 0.4396, R² = 0.8679, F = 60.4 RMSE = 0.5038, Q² = 0.8042, Pearson-R = 0.9044) and could successfully identify known aromatase inhibitors and differentiate between active and inactive inhibitors. The potential of this model can be effectively used to design new potent aromatase inhibitors for breast cancer treatment.