Title:Repurposing Phytochemicals against Breast Cancer (MCF-7) using Classical Structure-Based Drug Design
Volume: 22
Issue: 1
Author(s): Faten Essam Hussain Aldoghachi, Amjad Oraibi*, Noor Hamid Mohsen and Sara Salah Hassan
Affiliation:
- Department of Pharmacy, Al-Manara College for Medical
Sciences, Amarah, Iraq
Keywords:
Estrogen receptor alpha (ERα), MCF-7 cell line, breast cancer, quantitative structure-activity relationship (QSAR) model, molecular dynamics simulations, hydrogen bond.
Abstract:
Background: The significant public health effect of breast cancer is demonstrated by
its high global prevalence and the potential for severe health consequences. The suppression of the
proliferative effects facilitated by the estrogen receptor alpha (ERα) in the MCF-7 cell line is significant
for breast cancer therapy.
Objective: The current work involves in-silico techniques for identifying potential inhibitors of
ERα.
Methods: The method combines QSAR models based on machine learning with molecular docking
to identify potential binders for the ERα. Further, molecular dynamics simulation studied the
stability of the complexes, and ADMET analysis validated the compound’s properties.
Results: Two compounds (162412 and 443440) showed significant binding affinities with ERα,
with binding energies comparable to the established binder RL4. The ADMET qualities showed
advantageous characteristics resembling pharmaceutical drugs. The stable binding of these ligands
in the active region of ERα during dynamic conditions was confirmed by molecular dynamics simulations.
RMSD plots and conformational stability supported the ligands' persistent occupancy in
the protein's binding site. After simulation, two hydrogen bonds were found within the protein-ligand
complexes of 162412 and 443440, with binding free energy values of -27.32 kcal/mol and
-25.00 kcal/mol.
Conclusion: The study suggests that compounds 162412 and 443440 could be useful for developing
innovative anti-ERα medicines. However, more research is needed to prove the compounds'
breast cancer treatment efficacy. This will help develop new treatments for ERα-associated breast
cancer.
