Purpose: Depression is a sickening psychiatric condition that is prevalent worldwide. To manage depression, the underlying modes of antidepressant effect of herbals are important to be explored for the development of natural drugs. Tiansi Liquid is a traditional Chinese medicine (TCM) that is prescribed for the management of depression, however its underlying mechanism of action is still uncertain. The purpose of this study was to systematically investigate the pharmacological mode of action of a herbal formula used in TCM for the treatment of depression. Methods: Based on literature search, an ingredients-targets database was developed for Tiansi Liquid, followed by the identification of targets related to depression. The interaction between these targets was evaluated on the basis of protein-protein interaction network constructed by STITCH and gene ontology (GO) enrichment analysis using ClueGO plugin. Results: As a result of literature search, 57 components in Tiansi Liquid formula and 106 potential targets of these ingredients were retrieved. A careful screening of these targets led to the identification of 42 potential targets associated with depression. Ultimately, 327 GO terms were found by analysis of gene functional annotation clusters and abundance value of these targets. Most of these terms were found to be closely related to depression. A significant number of protein targets such as IL10, MAPK1, PTGS2, AKT1, APOE, PPARA, MAPK1, MIF, NOS3 and TNF-α were found to be involved in the functioning of Tiansi Liquid against depression. Conclusions: The findings elaborate that Tiansi Liquid can be utilized to manage depression, however, multiple molecular mechanisms of action could be proposed for this effect. The observed core mechanisms could be the sensory perception of pain, regulation of lipid transport and lipopolysaccharide-mediated signaling pathway.

Liu et al.: Discovering TCM herbs for neurodegenerative disorders In this investigation, candidate traditional Chinese medicinal herbs for 3 neurodegenerative disorders, late-onset Alzheimer's disease, late-onset Parkinson's disease and Huntington disease were evaluated. The susceptibility genes were integrated to reconstruct traditional Chinese medicine-modern medicine network to discover the candidate herbs. For the 3 neurodegenerative disorders, the number of diseaserelated genes were increased from 2 to 16, which are directly associated with ingredients. Many traditional Chinese medicinal herbs associated with the 3 neurodegenerative disorders were identified (false discovery rate Benjamini-Hochberg<0.05). Four herbs for late-onset Alzheimer's disease are related to β-amyloid 1-42 measurement-associated genes BCAM and APOE by ingredients resveratrol and kainic acid. There are 3 herbs correlated to late-onset Parkinson's disease by both ingredient support and modern medicine symptom association evidence. Four traditional Chinese medicinal herbs are related to Huntington disease by ingredients. Available animal experiments in rats indicated that resveratrol could help to clean β-amyloid in brain to treat Alzheimer's disease, probably through targeting LRP1 protein. This study provided a novel way to utilize genetic data to explore traditional Chinese medicinal herbs and a new insight into drug discovery of neurodegenerative disorders.