Background: Breast cancer is one of the most commonly diagnosed cancer types among women worldwide. Cytochrome P450 aromatase (CYP19A1) is an enzyme in vertebrates that selectively catalyzes the biosynthesis of estrogens from androgenic precursors. Researchers have increasingly focused on developing non-steroidal aromatase inhibitors (NSAIs) for their potential clinical use, avoiding steroidal side effects.
Objectives: The objective of the present work is to search for potential lead compounds from the ZINC database through various in silico approaches.
Methods: In the present study, compounds from the ZINC database were initially screened through receptor independent-based pharmacophore virtual screening. These screened molecules were subjected to several assessments, such as Lipinski rule of 5, SMART filtration, ADME prediction using SwissADME and lead optimization. Molecular docking was further applied to study the interaction of the filtered compounds with the active site of aromatase. Finally, the obtained hit compounds, consequently represented to be ideal lead candidates, were escalated to the MD simulations.
Results: The results indicated that the lead compounds might be potential anti-aromatase drug candidate.
Conclusion: The findings provided a valuable approach in developing novel anti-aromatase inhibitors for the treatment of ER+ breast cancer.
Keywords: Aromatase; NSAIs; docking; molecular dynamics simulation; pharmacophore; virtual screening.
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