抑郁症是一种高致死的情感性精神障碍类疾病，其现有治疗药物存在效率低、副作用明显的问题。中药甘草由于其低毒和良好的抗抑郁效果备受关注，但其有效成分以及作用机制尚不十分明确。为此，本项目拟构建一套符合中药多靶点协同作用特色的研究方法，以阐明甘草的有效成分及作用机制。包括：1）运用计算药代动力学评价方法快速筛选甘草中潜在的抗抑郁活性成分；2）联合自主开发的高通量靶点信息识别技术和低通量实验验证方法，确定甘草多靶点作用网络以及关键活性成分；3）建立大鼠慢性温和不可预知刺激抑郁模型，确定关键活性成分药效；4）整合模型动物转录组和抑郁病人尸检转录组数据，借助自主开发的基元动力学技术，突破靶点结合力评价药效的限制，阐明甘草活性成分在通路水平上潜在的弱结合、多靶点协同整合作用机制。项目的开展以期确定甘草抗抑郁关键活性物质和作用机制，为抗抑郁药物研究提供新思路和新方法。

Depression is a kind of psychological disorder with high mortality, and its existing therapeutic drugs generally have low efficacy and obvious side effects. As a traditional Chinese medicine (TCM), Glycyrrhiza uralensis (Gly) has drawn much attention due to its good antidepressant effect and low toxicity. However, the active components and mechanisms of action of Gly are not well clear. To this end, this project intends to build a set of research methods that are in line with the synergistic effects of multiple targets of TCM to elucidate the active ingredients and mechanism of action of Gly. Including: 1) rapid screening of potential antidepressant components in Gly using computational pharmacokinetic evaluation methods; 2) combining self-developed high- throughput target identification techniques and low- throughput experimental validation methods to determine multiple networks between targets and the key active ingredients of Gly; 3) the establishment of rat model of chronic mild unpredictable stimulation of depression, to determine the efficacy of key active ingredients; 4) integrating transcriptome data of rat model and depression patients with self- developed elementary subgraph dynamics analysis (ESDA), to clarify the potential synergistic mechanism of weak binding to multiple targets by the active ingredients. In summary, the project is carried out to determine the key anti-depressant active substances and mechanisms of action of Gly, providing new ideas and new methods for antidepressant research.