Abstract
Active compounds and corresponding targets of the traditional Chinese herb, jiaweisinisan, were obtained from systems pharmacological database and placed into ClueGO for gene ontology analysis. The targets of depression were obtained from the Online Mendelian Inheritance in Man, the Therapeutic Target Database, and the Pharmacogenomics Knowledge Base. Compound-target and target-pathway networks were constructed using Cytoscape, and then their topological parameters were analyzed. The targets of jiaweisinisan and depression were mapped to pathways, thereby constructing antidepressant pathways of jiaweisinisan. It was found that jiaweisinisan has 82 different active compounds and 306 relevant potential targets. Also, 107 unrepeatable targets related to depression were found. In all, 26 common targets were found to be the direct anti-depression targets of jiaweisinisan and 9 pathways of jiaweisinisan related to depression were divided into three modules (synaptic transmission, cell apoptosis, and immune-inflammatory). The jiaweisinisan formula was found to have synergistic antidepressant effects due to aspects of its herb composition and the active compounds therein, giving rise to potential targets and signaling pathways related to depression. Its antidepressant mechanisms were found to mainly involve the regulation of synaptic transmission, cell apoptosis, and immune-mediated inflammation.
Highlights
Depression is a common chronic mental illness worldwide
Five compounds - kaempferol, beta-sitosterol, quercetin, mandenol, and stigmasterol - were shared by various herbs of JWSNS
The multi-component, multi-target, and multipathway features of the synergistic effects of JWSNS against depression were effectively elucidated with a systems pharmacology approach. 82 different bioactive ingredients and 306 targets were identified from JWSNS
Summary
Depression is a common chronic mental illness worldwide. Its core symptoms include low mood, diminished interest, loss of pleasure, feelings of guilt, worthlessness, low self-esteem, and lack of energy, along with other problematic changes such as disorders of sleep and appetite, and disturbance in body weight (Battle, 2013). According to the World Health Organization, depression is set to replace cardiovascular disorders as the leading cause of disability by the year 2030. It will account for 13% of the total burden of disease (Levav and Rutz, 2002). While several biomarkers have been identified in support of leading theories, current understanding suggests that depression is not a single disease. It seems to be related to multiple risk genes interacting with environmental risk factors, yielding a spectrum of outcomes ranging from depressive symptoms to full-blown major depressive disorder (Kennis et al, 2020; Serafini et al, 2015). Despite a variety of antidepressant drugs currently on the market, there remains around 50% of patients who fail to respond to a single target antidepressant clinically
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