L-theanine is a bioactive non-protein amino acid predominantly derived from tea plants (Camellia sinensis), widely recognized for its potential benefits in mood regulation and psychological health. Despite its promising neuropsychological profile, the specific molecular targets and mechanisms underlying its antidepressant activity remain incompletely understood. In the present study, an integrated network pharmacology strategy, combined with molecular docking and molecular dynamics (MD) simulations, was employed to systematically elucidate the potential antidepressant mechanisms of L-theanine. By intersecting predicted drug targets with depression-related genes, 40 potential targets were identified. Protein–protein interaction (PPI) network analysis subsequently pinpointed five hub targets: PRKACA, GRIA2, GRIN1, GRIA1, and HTR1A. Functional enrichment analyses (KEGG and GO) indicated that these targets are primarily implicated in critical pathological processes of depression, including neurotransmitter regulation, glutamatergic synaptic transmission, stress response signaling, and neurotrophin-related pathways. Molecular docking revealed favorable binding affinities between L-theanine and the key targets. Furthermore, MD simulations and binding free energy calculations corroborated the structural stability and thermodynamic favorability of these protein–ligand complexes. Overall, this study provides hypothesis-generating insights into the antidepressant mechanisms of L-theanine from a multi-target perspective, offering a theoretical foundation to guide future experimental validation in depression research.

Tea polysaccharide preparations obtained from five successive leaf positions (L1–L5) and stem tissue (S) of Camellia sinensis cv. Rougui were compared to characterize developmental variation in their physicochemical and functional properties. Extraction yield increased from L1 to L4 and then declined, while neutral sugar content generally increased with leaf maturity. Monosaccharide composition and apparent molecular weight distribution also varied markedly, with peak molecular weight increasing from 70.5 kDa in L1 to approximately 804 kDa in L4 and L5. Antioxidant activities differed among assays and were associated more consistently with protein and tea polyphenol contents than with individual carbohydrate traits, indicating that the measured activities reflected the composite composition of the crude polysaccharide preparations. Phytohormone profiling and transcriptomic analysis of four representative tissues (L2, L3, L4, and S) showed tissue-dependent variation in endogenous hormone profiles and in genes related to carbohydrate metabolism, nucleotide-sugar interconversion, galacturonan-related biosynthesis, and pectin-related modification. Exploratory tissue-level correlations were used to prioritize 14 candidate genes associated with representative polysaccharide traits. Given the limited number of shared tissue types included in the integrated analyses, these associations remain exploratory and do not provide evidence for direct hormonal or transcriptional regulation. Overall, tea polysaccharide characteristics varied substantially with leaf developmental position and tissue type, supporting the selection of tea raw materials according to targeted polysaccharide properties.