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Network Pharmacology and Traditional Medicine

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Front. Pharmacol. | doi: 10.3389/fphar.2018.01472

Integrating network pharmacology and metabolomics study on anti-rheumatic mechanisms and antagonistic effects against methotrexate-induced toxicity of Qing-Luo-Yin

Jian Zuo1,  Xin Wang2, Yang Liu1, Jing Ye3, Qingfei Liu3, Yan Li1* and Shao Li2*
  • 1First Affiliated Hospital of Wannan Medical College, China
  • 2Department of Automation, Tsinghua University, China
  • 3School of Pharmaceutical Sciences, Tsinghua University, China

Qing-Luo-Yin (QLY) is a traditional Chinese medicine (TCM) formula used to treat hot syndrome-related rheumatoid arthritis (RA). Previously, we uncovered partial mechanisms involved in the therapeutic actions of QLY on RA. In this study, we further elucidated its anti-rheumatic mechanisms and investigated its possible interactions with methotrexate (MTX) in vivo using an integrating strategy coupled with network pharmacology and metabolomics techniques. Chemical composition of QLY was characterized by HPLC analysis. Collagen induced arthritis (CIA) was developed in male SD rats. The CIA rats were then assigned into different groups, and received QLY, MTX or QLY+MTX treatments according to the pre-arrangement. Therapeutic effects of QLY and its possible interactions with MTX in vivo were evaluated by clinical parameters, digital radiography assessment, histological/immunohistochemical examination, and serological biomarkers. Mechanisms underlying these actions were deciphered with network pharmacology methods, and further validated by metabolomics clues based on UPLC-Q-TOF/MS analysis of urines. Experimental evidences demonstrated that QLY notably alleviated the severity of CIA and protected joints from destruction. Re-balanced levels of hemoglobin and alanine transaminase in serum indicated reduced MTX-induced hepatic injury and myelosuppression under the co-treatment of QLY. Network-based target prediction found dozens of RA related proteins as potential targets of QLY. Upon the further biological function enrichment analysis, we found that a large amount of them were involved in nucleotide metabolism and immune functions. Metabolomics analysis showed that QLY restored amino acids, fatty acids, and energy metabolisms in CIA rats, which solidly supported its therapeutic effects on CIA. Consistently to findings from network pharmacology analysis, metabolomics study also found altered purine, pyrimidine, and pentose phosphate metabolisms in CIA rats receiving QLY treatment. All these clues suggested that inhibition on nucleic acid synthesis was essential to the immunosuppressive activity of QLY in vivo, and could contribute great importance to its therapeutic effects on CIA. Additionally, QLY induced significant antifolate resistance in rats, which would prevent folate from depletion during long-term MTX treatment, and should account for reduced side effects in combination regimen with MTX and QLY.

Keywords: Qing-Luo-Yin, Rheumatoid arthritis, Network Pharmacology, Metabolomics, nucleotide metabolism

Received: 13 Jul 2018; Accepted: 30 Nov 2018.

Edited by:

Yuanjia Hu, University of Macau, China

Reviewed by:

Cheng LU, Chinese Academy of Medical Sciences, China
Jianxin Chen, Beijing University of Chinese Medicine, China
Shi-Bing Su, Shanghai University of Traditional Chinese Medicine, China  

Copyright: © 2018 Zuo, Wang, Liu, Ye, Liu, Li and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Dr. Yan Li, First Affiliated Hospital of Wannan Medical College, Wuhu, 241001, Anhui Province, China, liyan.0301@163.com
Prof. Shao Li, Department of Automation, Tsinghua University, Beijing, China, shaoli@tsinghua.edu.cn