Exploring the Neurotherapeutic Potential of Bacillus-derived Macrolactins as NMDAR Antagonists for Alzheimer's disease: Network Pharmacology and Molecular Modeling Insights.

BACKGROUND The N-methyl-D-aspartate receptor (NMDAR) plays a critical role in regulating excitatory glutamatergic neurotransmission and synaptic plasticity. However, ex-cessive NMDAR activation can lead to increased calcium ion influx, resulting in excitotoxi-city-a key contributor to neurodegenerative diseases. Although current NMDAR inhibitors exist, their clinical use is limited due to adverse effects.

METHODS This study employed computational screening of Bacillus-derived macrolactins to identify potential NMDAR antagonists. Molecular docking simulations were performed using AMDock v1.5.2 with the AutoDock Vina engine to assess binding affinities to NMDAR (PDB:7SAD). Docked complexes were analyzed for chemical interactions, including polar contacts, using PyMol v2 and Discovery Studio Visualizer v4.5. Pharmacokinetic properties of macrolactins were predicted using Deep-PK. Molecular dynamics simulations via GROMACS assessed complex stability through RMSD, RMSF, radius of gyration (Rg), hy-drogen bond count, and solvent-accessible surface area (SASA). Network pharmacology anal-ysis of macrolactins in Alzheimer's disease (AD) involved mapping target interactions in STRING, importing into Cytoscape, and identifying hub genes using CytoHubba for KEGG pathway enrichment.

RESULTS Macrolactin F emerged as a promising candidate, exhibiting strong binding affinity (-6.8 kcal/mol) and an estimated Ki of 10.37 μM, outperforming commercial memantine and other macrolactins. Molecular dynamics simulations confirmed the stability and conforma-tional integrity of the Macrolactin F-NMDAR complex. KEGG pathway enrichment analysis highlighted key hub pathways associated with AD, including hsa05010, hsa04725, hsa04722, hsa04071, hsa04068, hsa04150, and hsa04910.

DISCUSSION The findings suggest that Macrolactin F possesses superior antagonistic activity against NMDAR compared to memantine, supported by molecular docking and dynamic sim-ulations. Network pharmacology analyses indicate that Macrolactin F can modulate critical signaling pathways implicated in AD, including PI3K/Akt/mTOR and MAPK cascades.

CONCLUSION Computational analyses identify Macrolactin F as a promising preclinical candi-date for developing allosteric NMDAR inhibitors. This aligns with SDG 3 by contributing to potential therapeutics for neurodegenerative diseases such as Alzheimer's disease and supports SDG 10 by promoting accessible interventions to reduce global health disparities.