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Virtual Screening and Dynamic Simulation of Baloxavir Derivatives for Multitarget Breast Cancer Treatment
Etibaria Belghalia1, Auwal Zakariya2, Abdelouahid Sbai1
1Department of Chemistry, Faculty of Science, Molecular Chemistry and Natural Substances Laboratory, University Moulay Ismail, Meknes, Morocco.
Background:
Breast cancer is a leading cause of mortality among women, emphasizing the need for novel therapeutic strategies. Targeting key receptors such as ERα, EGFR, and HER2 is critical for improving breast cancer treatments.
Objective:
This study aimed to identify potent Baloxavir derivatives with inhibitory potential against ERα, EGFR, and HER2 and evaluate their pharmacokinetic properties and stability through computational methods.
Methods:
A library of 72 Baloxavir derivatives was screened using molecular docking with AutoDock Vina. The top 32 compounds, ranked by binding affinity, were further assessed for ADMET properties. AutoDock 4.2 refined the docking analysis to identify potential inhibitors. The stability of the lead compound was validated through a 100 ns molecular dynamics simulation, evaluating RMSD, RMSF, Radius of Gyration, MolSA, SASA, and protein-ligand interactions.
Results:
Seven compounds exhibited favorable ADMET profiles. Of these, six demonstrated strong inhibitory potential against ERα and HER2, while three showed promising activity against EGFR. Molecular dynamics simulations confirmed the stability of the lead compound, supporting its potential as a candidate for further development.
Conclusion:
This computational study highlights Baloxavir derivatives as promising candidates for breast cancer therapy, providing a foundation for future preclinical investigations.
Insights
Novel Baloxavir derivatives show promise for breast cancer treatment. Computational analysis identified compounds with strong inhibitory potential against key receptors like estrogen receptor alpha (ERα), epidermal growth factor receptor (EGFR), and human epidermal growth factor receptor 2 (HER2).
Area of Science:
- Medicinal Chemistry
- Computational Drug Discovery
- Oncology
Background:
- Breast cancer remains a significant cause of mortality in women.
- Targeting key receptors such as estrogen receptor alpha (ERα), epidermal growth factor receptor (EGFR), and human epidermal growth factor receptor 2 (HER2) is crucial for effective treatment.
Purpose of the Study:
- To identify potent Baloxavir derivatives with inhibitory activity against ERα, EGFR, and HER2.
- To computationally evaluate the pharmacokinetic properties and stability of these derivatives.
Main Methods:
- Screening of 72 Baloxavir derivatives using molecular docking (AutoDock Vina).
- Assessment of ADMET properties and refinement of docking analysis with AutoDock 4.2.
- Validation of lead compound stability via 100 ns molecular dynamics simulations.
Main Results:
- Seven compounds displayed favorable ADMET profiles.
- Six compounds showed strong inhibition against ERα and HER2; three inhibited EGFR.
- Molecular dynamics confirmed the stability of the lead Baloxavir derivative.
Conclusions:
- Baloxavir derivatives represent promising candidates for breast cancer therapy.
- This computational study provides a basis for future preclinical research and development.
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