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Updated: Jun 14, 2025

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation
Published on: August 21, 2019
Comparable clinical advantages identification of three formulae on rheumatic disease using a modular-based network
Wenjing Zong1, Siwei Tian1, Qikai Niu1
1Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China.
Ethnopharmacological Relevance:
Herbal formulae have been used in China for thousands of years but have unclear clinical positioning and unknown characteristic indications make it difficult to determine their specific application in various diseases, which seriously hamper their clinical value. Identifying the precise clinical positioning and clinical advantages of similar formulae for related diseases is a critical issue.
Aim Of This Study:
To develop a methodology based on modular pharmacology to determine the clinical advantages and precise clinical position of similar formulae.
Materials And Methods:
In this study, we proposed a modular-based network proximity approach to explore drug repositioning and clinical advantages of three formulae, Shirebi tablets (SRB), Yuxuebi capsules (YXB), and Wangbifukang granules (WBFK), for rheumatic disease. First, we constructed a rheumatology target network, and modules were obtained using the cluster tool molecular complex detection (MCODE). Based on the modular interaction map established by a quantitative approach for inter-module coordination and its transition (IMCC), using a targeting rate (TR) matrix to identify targeted modules of three formulae. Moreover, the network proximity Z-score and Jaccard similarity coefficient were used to identify potential optimal symptomatic indications and related diseases using three formulae. At the same time, the driver genes for SRB and gouty arthritis were identified by flow centrality and shortest distance, and the epresentative driver genes were validated by in vivo experiments.
Results:
32 modules were obtained using the MCODE method. 4, 4, and 14 characteristic targeted modules of SRB, YXB, and WBFK, respectively, were identified using a targeting rate (TR) matrix. Module 2, 16, and 19 were targeted by both SRB and WBFK. The common effects of SRB and WBFK focused on inflammatory response and innate immune response, YXB was found to be involved in the collagen catabolic process, transmembrane receptor protein serine/threonine kinase signaling pathway. Moreover, potential optimal symptomatic indications and representative related diseases were identified for three formulae: SRB was significantly associated with GA (Z = -20.26); YXB was significantly associated with AS (Z = -4.532), MI (Z = -29.11), RhFv (Z = -6.945), OA (Z = -39.97), and GA (Z = -13.03); and WBFK was significantly associated with MI (Z = -205.5), SLE (Z = -37.65), RhFv (Z = -42.45), and GA (Z = -17.24). Finally, 8 driver genes for SRB and gouty arthritis were identified,the representative driver genes TRAF6 and NFE2L1 were validated by in vivo experiments.
Conclusions:
The modular-based network proximity approach proposed in this study may provide a new perspective for the precise drug repositioning and clinical advantages of similar formulae in disease treatment.
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