Abstract / Summary
Abstract Objective Alzheimer’s disease (AD) is an incurable neurodegenerative disease, and Bushen-Yizhi formula (BSYZ) has shown clinical potential for AD treatment, yet its bioactive components and pharmacological mechanisms remain unproven. To explore the therapeutic mechanism of BSYZ against AD-like cognitive impairment, a systems pharmacology framework was established via the integration of UPLC-Q-TOF-MS/MS, network analysis, machine learning and experimental validation. Materials and methods Chemical composition of BSYZ was characterized by UPLC-Q-TOF-MS/MS. A scopolamine (SCOP)-induced mouse model of AD-like cognitive impairment was used to evaluate neuroprotective effects via behavioral, histopathological, and biochemical assays. AD-associated targets were identified by differential expression analysis and WGCNA. Core targets were screened using 127 machine learning models with SHAP interpretation and validated by RT-qPCR. Stage-stratified transcriptomic analysis assessed gene expression across AD stages. Molecular docking and 100-ns MD simulations explored binding of core components to targets. Results One hundred five compounds were identified from BSYZ. In SCOP-treated mice, BSYZ ameliorated cognitive deficits, oxidative stress, cholinergic dysfunction, and neuroinflammation. Bioinformatics uncovered 81 potential AD targets, from which seven core genes (HIPK2, CXCR4, CCKBR, PTPN13, SFN, ALB, ALDH1A1) were refined. RT-qPCR confirmed differential mRNA expression, and stage-stratified analysis revealed dynamic changes during AD progression. Molecular docking and MD suggested that isoquercitrin and epicatechin gallate bind to CXCR4 and CCKBR, providing computational evidence. Conclusion These findings support the multi-component, multi-target neuroprotective effects of BSYZ against AD-like cognitive impairment, providing a basis for further preclinical development and mechanistic investigation.