Current topics in medicinal chemistry · 2025
Designing Novel NMDA Receptor Antagonists for Ischemic Stroke: A 3D-QSAR and Molecular Dynamics Simulation Approach.
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Wan Zhuangzhuang, Jiang Xiaolin, Fan Chenlon, Hou Boru
Аннотация
BACKGROUND: Strokes represent a significant global health concern, with ischemic stroke being the most prevalent and deadly form. The pathogenesis of ischemic stroke involves complex mechanisms, including excitotoxicity, oxidative stress, and cell death. This study presents a computational design of novel GluN2B-selective N-Methyl-D-Aspartate receptor antagonists with potential therapeutic applications in neurodegenerative disorders.
METHODS: 3D-Quantitative Structure-Activity Relationship (QSAR) model and molecular dynamics simulations were employed to design novel NMDA receptor antagonists. A dataset of 53 derivatives was analyzed using structure-based virtual screening, molecular docking, and pharmacophore modeling.
RESULTS: Molecular docking and dynamics simulations confirmed the binding affinity and dynamic behavior of the designed compounds, providing insights into their potential as therapeutic agents. We identified lead compound 75 with high predicted affinity and selectivity for GluN2Bcontaining receptors. Drug-likeness assessment, synthetic accessibility evaluation, and molecular dynamics simulations confirmed favorable pharmacokinetic properties and target engagement stability.
CONCLUSION: These findings provide a rational framework for the development of selective NMDA receptor antagonists with improved safety and efficacy profiles.
METHODS: 3D-Quantitative Structure-Activity Relationship (QSAR) model and molecular dynamics simulations were employed to design novel NMDA receptor antagonists. A dataset of 53 derivatives was analyzed using structure-based virtual screening, molecular docking, and pharmacophore modeling.
RESULTS: Molecular docking and dynamics simulations confirmed the binding affinity and dynamic behavior of the designed compounds, providing insights into their potential as therapeutic agents. We identified lead compound 75 with high predicted affinity and selectivity for GluN2Bcontaining receptors. Drug-likeness assessment, synthetic accessibility evaluation, and molecular dynamics simulations confirmed favorable pharmacokinetic properties and target engagement stability.
CONCLUSION: These findings provide a rational framework for the development of selective NMDA receptor antagonists with improved safety and efficacy profiles.