Mechanistic Insights into the Anti-Constipation Potential of Zeng Ye Tang Compound: UHPLC-Q-TOF MS/MS, Network Pharmacology, and In vivo Experimental Validation.
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引用次数: 0
Abstract
Introduction: Zeng Ye Tang (ZYT) is used to treat constipation caused by various factors. However, the precise mechanism underlying its therapeutic effects remains unclear.
Methods: An integrative approach combining UHPLC-Q-TOF MS analysis, network pharmacology, and in vivo validation was employed to elucidate the therapeutic basis of ZYT against constipation systematically.
Results: The analysis identified 166 active ingredients in the ZYT formula, targeting 144 core constipation-related genes. ZYT modulated constipation progression primarily through the cAMP signaling pathway. Animal studies showed that ZYT treatment significantly increased defecation frequency and fecal water content. Additionally, ZYT alleviated histopathological damage in the colonic tissues of constipated mice, regulated serum levels of both excitatory and inhibitory neurotransmitters, and increased ET and VIP concentrations. ZYT also enhanced colonic protein expression of VIP, cAMP, PKA, and AQP3.
Discussion: By integrating network pharmacology with experimental verification, this study confirmed that ZYT exerts therapeutic effects against constipation by regulating the VIP-cAMPPKA- AQP3 signaling axis. This pathway influences gastrointestinal motility, modulates neurotransmitter release, and regulates intestinal fluid and electrolyte secretion.
Conclusions: ZYT demonstrates anti-constipation effects by modulating the VIP-cAMP-PKAAQP3 signaling pathway. These findings provide experimental support for its therapeutic potential and mechanism of action as a laxative, offering valuable guidance for clinical application.
期刊介绍:
Combinatorial Chemistry & High Throughput Screening (CCHTS) publishes full length original research articles and reviews/mini-reviews dealing with various topics related to chemical biology (High Throughput Screening, Combinatorial Chemistry, Chemoinformatics, Laboratory Automation and Compound management) in advancing drug discovery research. Original research articles and reviews in the following areas are of special interest to the readers of this journal:
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