A network pharmacology approach to decipher the mechanisms of anti-depression of Xiaoyaosan formula

Objective: Depression is one of the prevalent and prominent complex psychiatric diseases, and the number of depressed patients has been on the rise globally during the recent decades. Xiaoyaosan, as a famous Chinese herbal formula, has been widely used in depression patients for a long time. However, the therapeutic mechanisms remain uncertain because of the difficulty of depression pathophysiology and the lack of bioinformatic approach to understand the molecular connection. Materials and Methods: In this thesis, we applied a network pharmacology approach to explain the potential mechanisms between Xiaoyaosan and depression involved in oral bioavailability screening, drug-likeness assessment, caco-2 permeability, blood–brain barrier target recognition, and network analysis. Results: Sixty-six active compounds in Xiaoyaosan formula with favorable pharmacokinetic profiles are predicted as active compounds for antidepression treatment. Network analyses showed that these 66 compounds target 40 depression-associated proteins including especially HTR2A, NR 3C1, monoamine oxidase inhibitor B, XDH, and CNR2. These proteins are mainly involved in the neuroactive ligand–receptor interaction, serotonergic synapse, cAMP signaling pathways, and calcium signaling pathways. Conclusion: The integrated network pharmacology method can provide a new approach for understanding the pathogenesis of depression and uncovering the molecular mechanisms of Xiaoyansan, which will also facilitate the application of traditional Chinese herbs in modern medicine