Mathematical algorithm–based identification of the functional components and mechanisms in depression treatment: An example of Danggui-Shaoyao-San - Gong, Wenxia; Wang, Kexin; Wang, Xueyuan; Chen, Yupeng; Qin, Xuemei; Lu, Aiping; Guan, Daogang (Frontiers in Cell and Developmental Biology, 2022)
Depression, a complex epidemiological mental disorder, affects around 350 million people worldwide. Despite the availability of antidepressants based on monoamine hypothesis of depression, most patients suffer side effects from these drugs, including psychomotor impairment and dependence liability. Traditional Chinese medicine (TCM) is receiving more and more attention due to the advantages of high therapeutic performance and few side effects in depression treatment. However, complex multicomponents and multi-targets in TCM hinder our ability to identify the functional components and molecular mechanisms of its efficacy. In this study, we designed a novel strategy to capture the functional components and mechanisms of TCM based on a mathematical algorithm. To establish proof of principle, the TCM formula Danggui-Shaoyao-San (DSS), which possesses remarkable antidepressant effect but its functional components and mechanisms are unclear, is used as an example. According to the network motif detection algorithm, key core function motifs (CIM) of DSS in treating depression were captured, followed by a functional analysis and verification. The results demonstrated that 198 pathways were enriched by the target genes of the CIM, and 179 coincided with the enriched pathways of pathogenic genes, accounting for 90.40% of the gene enrichment pathway of the C-T network. Then the functional components group (FCG) comprising 40 components was traced from CIM based on the target coverage accumulation algorithm, after which the pathways enriched by the target genes of FCG were selected to elucidate the potential mechanisms of DSS in treating depression. Finally, the pivotal components in FCG of DSS and the related pathways were selected for experimental validation in vitro and in vivo. Our results indicated good accuracy of the proposed mathematical algorithm in sifting the FCG from the TCM formula, which provided a methodological reference for discovering functional components and interpreting molecular mechanisms of the TCM formula in treating complex diseases.