Integrated multi-omics and deep learning analysis reveals neurotransmitter metabolism regulatory mechanisms of Tianwang Buxin Dan.

Background: Tianwang Buxin Dan is a classical Traditional Chinese Medicine formula with documented clinical use in treating neuropsychiatric disorders, yet its molecular mechanisms remain incompletely understood. Methods: We developed an integrated analytical framework combining transcriptomic and metabolomic profiling with deep learning to investigate the neurotransmitter metabolism regulatory mechanisms of Tianwang Buxin Dan. Data were collected from a para-chlorophenylalanine (PCPA)- induced insomnia rat model following formula intervention. A multi-omics feature fusion strategy incorporating autoencoder-based dimensionality reduction and cross-modal attention mechanisms was implemented to address data heterogeneity. Results: A total of 1,847 differentially expressed genes and 286 differential metabolites were identified. The constructed deep neural network achieved 91.2% classification accuracy with an AUC of 0.956 in five-fold cross-validation, and permutation testing confirmed that performance was significantly above chance ( Discussion: Tianwang Buxin Dan may modulate neurotransmitter metabolism through coordinated regulation of biosynthetic and catabolic pathways. A component-target-pathway regulatory network identified 47 key molecular targets interconnected through 156 functional associations. This work provides a computational framework applicable to mechanism studies of other compound TCM formulations.