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Breast cancer (Bc a ) causes the highest rate of mortality in females owing to the out-of-control cell division in breast cells. In this work, we perform an in-silico screening based on molecular docking and molecular dynamic of curcumin derivatives against ERα. In this study, we carry out, molecular docking of fifty (50) curcumin derivatives having anticancer potential by using virtual screening tools. Ten (10) ligands were selected based on binding energy ranged from (-7.4 kcal/mol to -9 kcal/mol), lower values of inhibition constant (0.23 µ mol to 3.59 µ mol), and visualisation of intermolecular interactions. Additionally, we also assess ADMET properties of selected ligands for prediction of their toxicity and drug-likeness. The molecular dynamic simulations (MD) including RMSD, RMSF, Rg, SASA, number of H-bonds and MM-PBSA binding free energy results showed that ligand  L2  and  L8  bind to estrogen protein  ERα  more proficiently with good stability over 120 ns. These results suggest lead anticancer compounds  L2  ( Salicylidenecurcumin ) and  L8  ( Curcumin difluorinated ) are the most promising inhibitor against ERα of Bc a  with ∆Gbindvalues of (-2.939 and -4.369) kcal/mol. we expect that our findings will evoke the scientific community to further do in-vitro and in-vivo investigations for screened curcumin derivatives against ERα of Bc a.

Virtual screening of potential inhibitor against breast cancer-causing estrogen receptor alpha (ERα): molecular docking and dynamic simulations