Exploring the Therapeutic Potential of Virtual Screened Novel HER2 Inhibitors via QSAR, Molecular Docking and Dynamics Simulations.
Khurram Rehman, Zoya Iqbal, Zhiqin Deng, Hina Ayub, Naseem Saba, Rida Asghar, Maryam Shabbir, Wencui Li
Abstract
Open AccessObjectives: HER2 overexpression is almost invariably associated with advanced breast cancer disease and poor prognosis, hence its extensive review. This study therefore aims to discover and analyze potential HER2 inhibitors through computational methods to advance drug discovery and optimization. Methodology: A ligand-based virtual screening (LBVS) approach was employed to screen compounds from the ChEMBL database. From 8900 initial matches, 39 candidate compounds were selected based on structural similarity and ADME properties. Molecular docking was performed to assess binding affinity with HER2, followed by molecular dynamics (MD) simulations to evaluate complex stability. Additionally, a QSAR (quantitative structure-activity relationship) model was established to elucidate key structural features influencing inhibitory activity. Results: Five lead compounds were prioritized based on strong docking scores (<-8.4 kcal/mol). Among them, compound 2048788 (-11.0 kcal/mol, predicted pIC50 ≈ 8.6) and compound 3956509 (pIC50 ≈ 8.4) showed superior binding affinity and pharmacokinetic properties compared to FDA-approved drugs (doxorubicin, letrozole, lanatuzumab). MD simulations confirmed complex stability. The initial QSAR model showed low predictive power (R2 = 0.18, RMSE = 1.19), but after feature selection, performance improved significantly (RMSE = 0.57). Key positive contributors included hydrogen bond donor count (r = 0.63), lipophilicity (LogP, r = 0.60), and sp3 carbon fraction (r =0.60), while excessive polarity and aromaticity reduced activity. Compounds within the 450-500 Da molecular weight range exhibited the highest activity (pIC50 = 8.0-8.6). Conclusion: This study integrated virtual screening, docking, MD simulations, and QSAR modeling to identify compound 2048788 as a highly promising HER2 inhibitor. These findings provide a strong foundation for further optimization and the preclinical development of targeted HER2 therapies.