
Targeting Breast Cancer: A Journey from Design to Dynamics
Targeting Breast Cancer Through Computational Drug Discovery
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This book explores the contribution of computational methods in the search for targeted breast cancer therapies. It focuses on three key receptors: estrogen receptor alpha (ER ), human epidermal growth factor receptor 2 (HER2), and epidermal growth factor receptor (EGFR). Two chemical families, pyrazole-benzimidazole derivatives and Baloxavir analogs, were evaluated through QSAR modeling, molecular docking, ADMET predictions, and molecular dynamics simulations. The first study identified two compounds with strong binding affinity and favorable pharmacokinetic properties. The second revealed se...
This book explores the contribution of computational methods in the search for targeted breast cancer therapies. It focuses on three key receptors: estrogen receptor alpha (ER ), human epidermal growth factor receptor 2 (HER2), and epidermal growth factor receptor (EGFR). Two chemical families, pyrazole-benzimidazole derivatives and Baloxavir analogs, were evaluated through QSAR modeling, molecular docking, ADMET predictions, and molecular dynamics simulations. The first study identified two compounds with strong binding affinity and favorable pharmacokinetic properties. The second revealed several Baloxavir derivatives with promising multi-target activity, including one lead compound showing stable interactions with all three receptors. These results highlight the potential of in silico techniques in early-stage drug discovery and provide a foundation for further biological validation, supporting the development of more effective and personalized treatments for breast cancer.