AUTHOR=Gong Wenxia , Wang Kexin , Wang Xueyuan , Chen Yupeng , Qin Xuemei , Lu Aiping , Guan Daogang 

TITLE=Mathematical algorithm–based identification of the functional components and mechanisms in depression treatment: An example of Danggui-Shaoyao-San

JOURNAL=Frontiers in Cell and Developmental Biology

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/cell-and-developmental-biology/articles/10.3389/fcell.2022.937621

DOI=10.3389/fcell.2022.937621

ISSN=2296-634X

ABSTRACT=Depression, a complex epidemiological mental disorder, affects around 350 million people worldwide in their lives. Despite of the availability of many 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) are receiving more and more attentions due to the advantages of high therapeutic performance and few side effects in depression treatment. However, the complex multi-components and multi-targets in TCM hinder our ability to identify the functional components and molecular mechanism of its efficacy. In this study, we designed a novel strategy to capture the functional components and mechanism from TCM based on mathematical algorithm. To establish proof of principle, TCM formula Danggui-Shaoyao-San (DSS), which possessed remarkable antidepressant effect but its functional components and mechanism were unclear, as an example. According to the network motif detection algorithm, the key core function motifs (CIM) of DSS in treating depression was captured, followed by the functional analysis and verification. The results demonstrated that 198 pathways were enriched by the target genes of the CIM, and 179 were coincided with the enriched pathways of pathogenic genes, accounting for 90.40% of the gene enrichment pathway of C-T network. Then, the functional components group (FCG) consisted of 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 mechanism of DSS in treating depression. Finally, the pivotal component in FCG of DSS and the related pathway was selected for experimental validation in vitro and in vivo. Our results indicated that the good accuracy of the proposed mathematical algorithm in sifting the FCG from TCM formula, which provides methodological reference for discovering functional components and interpreting molecular mechanism of TCM formula in treating complex diseases.