De Novo Generation-Based Design of Potential Computational Hits Targeting the GluN1-GluN2A Receptor

基于从头生成的、针对 GluN1-GluN2A 受体的潜在计算先导化合物设计

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Abstract

Central nervous system (CNS) disorders such as depression severely impair human health. Targeted inhibition of the GluN1-GluN2A receptor is a promising therapeutic strategy, but current drugs often have adverse effects. To develop novel candidate drugs, this study utilized the (S)-ketamine and GluN1-GluN2A receptor complex as a structural template and conducted de novo drug design with the DrugFlow platform. An integrated strategy of molecular docking-based virtual screening combined with high-throughput binding free energy (∆G(binding)) calculations from large-scale molecular dynamics (MD) simulations identified three promising antagonists. The ∆G(binding) values of these compounds are all below -18.98 kcal/mol, indicating stronger binding affinity than (S)-ketamine, and they demonstrate promising drug-like properties and development potential. 200-ns MD simulations confirmed their stable receptor binding and mechanism consistent with (S)-ketamine. Electrophysiological recordings revealed that, at a concentration of 10 μM, Compounds A1, A2, and A3 produced concentration-dependent inhibition of GluN1-GluN2A receptor-mediated currents, with fractional inhibition values of 24.26%, 35.36%, and 41.76%, respectively. These findings demonstrate the compounds' potential as CNS disorder therapeutics, requiring further experiments to validate efficacy and advance development for conditions like depression.

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