Pyrazole-benzimidazole derivatives targeting MCF-7 breast cancer cells as potential anti-proliferative agents. 3D QSAR and In-silico investigations via molecular docking and molecular dynamics simulations

Breast cancer is a complicated type of cancer that mainly occurs in women and poses a global challenge due to its genetic diversity, making accurate diagnosis challenging. The accepted approaches are categorized based on cancer subtype and metastasis level. This study focuses on a predictive drug discovery strategy for compounds that may modulate interaction with HER-2 and EGFR, two important receptors in cancer treatment. We employed a 3D QSAR methodology, complemented by molecular docking, ADMET analysis, and molecular dynamics simulations, to evaluate the antiproliferative effects of pyrazole-benzimidazole derivatives on MCF-7 cells as targeted therapies. External validation confirmed the predictive accuracy of the generated models. The best CoMSIA (Comparative Molecular Similarity Indices Analysis) and CoMFA (Comparative Molecular Field Analysis) models exhibited significant $Q^2$, $R^2$, and $R_{Test}^2$ values, emphasizing the role of electrostatic and hydrophobic fields in inhibiting breast cancer cell growth. These findings provided a foundation for designing and predicting the biological effects of potent inhibitors. Additionally, ADMET analysis was conducted to evaluate the drug-likeness of the newly designed ligands, while the stability of the complexes was confirmed by molecular dynamics simulations, which validate the binding stability of the selected chemicals. MMPBSA, PCA, and FEL investigations provide further support for this assertion, reinforcing the robustness of our conclusions.