Application of network composite module analysis and verification to explore the bidirectional immunomodulatory effect of Zukamu granules on Th1 / Th2 cytokines in lung injury.

Ethnopharmacological Relevance: Zukamu granules (ZKMG), as the preferred drug for the treatment of colds in Uygur medical theory, has been used for 1500 years. It is also widely used in China and included in the National Essential Drugs List (2018 edition). It has unique anti-inflammatory, antitussive and analgesic effects.
Aim of the Study: Aiming at the research of traditional Chinese medicine (TCM) with the characteristics of overall regulation of body diseases and the immune regulation mechanism with the concept of integrity, this paper put forward the integrated application of network composite module analysis and animal experiment verification to study the immune regulation mechanism of TCM.
Materials and Methods: The active components and targets of ZKMG were predicted, and network module analysis was performed to explore their potential immunomodulatory mechanisms. Then acute lung injury (ALI) mice and idiopathic pulmonary fibrosis (IPF) rats were used as pathological models to observe the effects of ZKMG on the pathological conditions of infected ALI and IPF rats, determine the contents of Th1, Th2 characteristic cytokines and immunoglobulins, and study the intervention of GATA3/STAT6 signal pathway.
Results: The results of network composite module analysis showed that ZKMG contained 173 pharmacodynamic components and 249 potential targets, and four key modules were obtained. The immunomodulatory effects of ZKMG were related to T cell receptor signaling pathway. The validation results of bioeffects that ZKMG could carry out bidirectional immune regulation on Th1/Th2 cytokines in the stage of ALI and IPF, so as to play the role of regulating immune homeostasis and organ protection.
Conclusions: The network composite module analysis and verification method is an exploration to study the immune regulation mechanism of TCM by combining the network module prediction analysis with animal experiments, which provides a reference for subsequent research.
Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:
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