Next Article in Journal
Synthesis and Biological Evaluation of Herceptin-Conjugated Liposomes Loaded with Lipocalin-2 siRNA for the Treatment of Inflammatory Breast Cancer
Previous Article in Journal
Purine–Hydrazone Scaffolds as Potential Dual EGFR/HER2 Inhibitors
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Pharmaceuticals
Volume 18
Issue 7
10.3390/ph18071052
pharmaceuticals-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Integration of Untargeted Metabolomics, Network Pharmacology, Single-Cell RNA Sequencing, and Molecular Dynamics Simulation Reveals GOT1, CYP1A2, and CA2 as Potential Targets of Huang Qin Decoction Preventing Colorectal Cancer Liver Metastasis

by
Tiegang Li
1,2,
Zheng Yan
1,2,
Mingxuan Zhou
1,2,
Wenyi Zhao
1,2,
Fang Zhang
1,2,
Silin Lv
1,2,
Yufang Hou
1,2,
Zifan Zeng
1,2,
Liu Yang
1,2,
Yixin Zhou
1,2,
Zengni Zhu
1,2,
Xinyi Ren
1,2,3 and
Min Yang
1,2,*
1
State Key Laboratory of Digestive Health, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
2
State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
3
School of Pharmacy, Minzu University of China, Beijing 100081, China
*
Author to whom correspondence should be addressed.
Pharmaceuticals 2025, 18(7), 1052; https://doi.org/10.3390/ph18071052
Submission received: 20 June 2025 / Revised: 12 July 2025 / Accepted: 14 July 2025 / Published: 17 July 2025
(This article belongs to the Section Natural Products)
Browse Figures
Versions Notes

Abstract

Background: Huang Qin Decoction (HQD) is a well-established Traditional Chinese Medicine (TCM) formulation recognized for its application in the treatment of colorectal cancer (CRC). However, the precise therapeutic mechanisms remain inadequately defined. Methods: This study integrates metabolomics from a mouse model and network pharmacology to screen potential targets and bio-active ingredients of HQD. The pharmacological activity of HQD for CRC was evidenced via single-cell RNA sequencing (scRNA-seq), molecular docking, and molecular dynamics simulations. Atomic force microscopy (AFM) assays and cellular experimental validation were used to confirm the relative mechanisms. Results: The metabolite profile undergoes significant alterations, with metabolic reprogramming evident during the malignant progression of CRC liver metastasis. Network pharmacology analysis identified that HQD regulates several metabolic pathways, including arginine biosynthesis, alanine, aspartate, and glutamate metabolism, nitrogen metabolism, phenylalanine metabolism, and linoleic acid metabolism, by targeting key proteins such as aspartate aminotransferase (GOT1), cytochrome P450 1A2 (CYP1A2), and carbonic anhydrase 2 (CA2). ScRNA-seq analysis indicated that HQD may enhance the functionality of cytotoxic T cells, thereby reversing the immunosuppressive microenvironment. Virtual verification revealed a strong binding affinity between the identified hub targets and active constituents of HQD, a finding subsequently corroborated by AFM assays. Cellular experiments confirmed that naringenin treatment inhibits the proliferation, migration, and invasion of CRC cells by downregulating GOT1 expression and disrupting glutamine metabolism. Conclusions: Computational prediction and in vitro validation reveal the active ingredients, potential targets, and molecular mechanisms of HQD against CRC liver metastasis, thereby providing a scientific foundation for the application of TCM in CRC treatment.
Keywords: Huang Qin Decoction; colorectal cancer; metabolomics; network pharmacology; single-cell RNA sequencing; molecular dynamics simulation Huang Qin Decoction; colorectal cancer; metabolomics; network pharmacology; single-cell RNA sequencing; molecular dynamics simulation

Share and Cite

MDPI and ACS Style

Li, T.; Yan, Z.; Zhou, M.; Zhao, W.; Zhang, F.; Lv, S.; Hou, Y.; Zeng, Z.; Yang, L.; Zhou, Y.; et al. Integration of Untargeted Metabolomics, Network Pharmacology, Single-Cell RNA Sequencing, and Molecular Dynamics Simulation Reveals GOT1, CYP1A2, and CA2 as Potential Targets of Huang Qin Decoction Preventing Colorectal Cancer Liver Metastasis. Pharmaceuticals 2025, 18, 1052. https://doi.org/10.3390/ph18071052

AMA Style

Li T, Yan Z, Zhou M, Zhao W, Zhang F, Lv S, Hou Y, Zeng Z, Yang L, Zhou Y, et al. Integration of Untargeted Metabolomics, Network Pharmacology, Single-Cell RNA Sequencing, and Molecular Dynamics Simulation Reveals GOT1, CYP1A2, and CA2 as Potential Targets of Huang Qin Decoction Preventing Colorectal Cancer Liver Metastasis. Pharmaceuticals. 2025; 18(7):1052. https://doi.org/10.3390/ph18071052

Chicago/Turabian Style

Li, Tiegang, Zheng Yan, Mingxuan Zhou, Wenyi Zhao, Fang Zhang, Silin Lv, Yufang Hou, Zifan Zeng, Liu Yang, Yixin Zhou, and et al. 2025. "Integration of Untargeted Metabolomics, Network Pharmacology, Single-Cell RNA Sequencing, and Molecular Dynamics Simulation Reveals GOT1, CYP1A2, and CA2 as Potential Targets of Huang Qin Decoction Preventing Colorectal Cancer Liver Metastasis" Pharmaceuticals 18, no. 7: 1052. https://doi.org/10.3390/ph18071052

APA Style

Li, T., Yan, Z., Zhou, M., Zhao, W., Zhang, F., Lv, S., Hou, Y., Zeng, Z., Yang, L., Zhou, Y., Zhu, Z., Ren, X., & Yang, M. (2025). Integration of Untargeted Metabolomics, Network Pharmacology, Single-Cell RNA Sequencing, and Molecular Dynamics Simulation Reveals GOT1, CYP1A2, and CA2 as Potential Targets of Huang Qin Decoction Preventing Colorectal Cancer Liver Metastasis. Pharmaceuticals, 18(7), 1052. https://doi.org/10.3390/ph18071052

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop