| Popis: |
Estrogen receptor alpha (ERα), a nuclear receptor protein encoded by the estrogen receptor1 (ESR1) gene, is an important biomarker in breast cancer diagnosis. Any dysregulation in its expression can actively implicate the development and progression of the disease. ERα is abnormally expressed in around 60% of the active cases, making it an important therapeutic target. In this study, we report the application of computational approaches to identify suitable drug-like molecules, which share similar ligand binding dynamics with ERα. Structure-based virtual screening(SBVS), docking, and inhibitor dynamics are used to study the ligand binding and interaction profiling of the anticipated ligand molecule, at the active site of the 4-hydroxytamoxifen (OHT) protein (PDB Id: 3ERT). SBVS analysis follows HTVS, SP, and XP protocol in comparison to the ZINC and NCI, to retrieve 20bestligandhits as effective inhibitors; All the compounds have shown significant interaction with active site residues (Leu346, Thr347, Asp351, Glu353, Trp383, Leu387, and Arg394) of the 4-hydroxytamoxifen. Moreover, the docking study was used to screen the top 5 compounds: ZINC13377936, NCI35753, ZINC35465238, ZINC14726791, and NCI663569. We also, employed molecular dynamics simulations to explore the binding dynamics present at the atomic level. Our MDS results have revealed the compounds (ZINC13377936 and NCI35753) with outstanding binding stability and lesser fluctuations. Both above hits possess a high potential as future therapeutic agents, acting by the mechanism of competitive inhibition against the ERα protein in breast cancer. |
