Structure-based elucidation of thiazine inhibitors targeting estrogen receptors alpha: pharmacophore modeling, virtual screening, molecular docking, MD, and DFT approach.

Abstract

Breast cancer (BC) is considered a highly prevalent cancer among women, with estrogen receptor alpha (ERα) playing a pivotal role in tumor growth and development. Even with existing medications such as tamoxifen, the rising resistance underscores the vital demand for novel ER-positive inhibitors. The present work focuses on identifying a thiazine derivative targeting ERα via pharmacophore model-based drug design. A ligand database of 62 bioactive thiazine derivatives in the MCF-7 cell line was generated and validated using the pharmacophore model (AHRRR_1). An additional 95,296 thiazine derivatives were downloaded and screened against the developed pharmacophore model. 10 HITs were identified via high-throughput virtual screening, standard precision, and extra precision molecular docking with the ERα protein (Protein Data Bank ID: 4XI3). Hence, HIT1 was selected as a potential lead candidate following analysis of the pharmacokinetic profile and binding free energies, as it meets the criteria and has a higher docking score than the reference drug tamoxifen. Beyond this, the stability and structural compactness of the HIT1 were confirmed by a 200 ns molecular dynamics simulation. Subsequently, a Density Functional Theory assessment highlighted the drug-likeness and reactivity of the HIT relative to tamoxifen. Collectively, this research developed a promising lead molecule (HIT1) as a therapeutic approach for ER-positive breast cancer.