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Liu Q, Li X, Li Y, Luo Q, Fan Q, Lu A, Guan D, Li J. A novel network pharmacology strategy to decode mechanism of Wuling Powder in treating liver cirrhosis. Chin Med 2024; 19:36. [PMID: 38429802 PMCID: PMC10905787 DOI: 10.1186/s13020-024-00896-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 01/26/2024] [Indexed: 03/03/2024] Open
Abstract
BACKGROUND Liver cirrhosis is a chronic liver disease with hepatocyte necrosis and lesion. As one of the TCM formulas Wuling Powder (WLP) is widely used in the treatment of liver cirrhosis. However, it's key functional components and action mechanism still remain unclear. We attempted to explore the Key Group of Effective Components (KGEC) of WLP in the treatment of Liver cirrhosis through integrative pharmacology combined with experiments. METHODS The components and potential target genes of WLP were extracted from published databases. A novel node importance calculation model considering both node control force and node bridging force is designed to construct the Function Response Space (FRS) and obtain key effector proteins. The genetic knapsack algorithm was employed to select KGEC. The effectiveness and reliability of KGEC were evaluated at the functional level by using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Finally, the effectiveness and potential mechanism of KGEC were confirmed by CCK-8, qPCR and Western blot. RESULTS 940 effective proteins were obtained in FRS. KEGG pathways and GO terms enrichments analysis suggested that effective proteins well reflect liver cirrhosis characteristics at the functional level. 29 components of WLP were defined as KGEC, which covered 100% of the targets of the effective proteins. Additionally, the pathways enriched for the KGEC targets accounted for 83.33% of the shared genes between the targets and the pathogenic genes enrichment pathways. Three components scopoletin, caryophyllene oxide, and hydroxyzinamic acid from KGEC were selected for in vivo verification. The qPCR results demonstrated that all three components significantly reduced the mRNA levels of COL1A1 in TGF-β1-induced liver cirrhosis model. Furthermore, the Western blot assay indicated that these components acted synergistically to target the NF-κB, AMPK/p38, cAMP, and PI3K/AKT pathways, thus inhibiting the progression of liver cirrhosis. CONCLUSION In summary, we have developed a new model that reveals the key components and potential mechanisms of WLP for the treatment of liver cirrhosis. This model provides a reference for the secondary development of WLP and offers a methodological strategy for studying TCM formulas.
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Affiliation(s)
- Qinwen Liu
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Southern Medical University, Guangzhou, China
| | - Xiaowei Li
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Southern Medical University, Guangzhou, China
| | - Yi Li
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Southern Medical University, Guangzhou, China
| | - Qian Luo
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Southern Medical University, Guangzhou, China
| | - Qiling Fan
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Southern Medical University, Guangzhou, China
| | - Aiping Lu
- Institute of Integrated Bioinformedicine and Translational Science, Hong Kong Baptist University, Hong Kong, China.
- Guangdong-Hong Kong-Macau Joint Lab On Chinese Medicine and Immune Disease Research, Guangzhou, China.
| | - Daogang Guan
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China.
- Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Southern Medical University, Guangzhou, China.
| | - Jiahui Li
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China.
- Center for Genetics and Developmental Systems Biology, Department of Obstetrics and Gynecology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China.
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Liu Q, Luo Q, Fan Q, Li Y, Lu A, Guan D. Screening of the key response component groups and mechanism verification of Huangqi-Guizhi-Wuwu-Decoction in treating rheumatoid arthritis based on a novel computational pharmacological model. BMC Complement Med Ther 2024; 24:4. [PMID: 38166916 PMCID: PMC10759359 DOI: 10.1186/s12906-023-04315-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 12/14/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by the destruction of synovial tissue and articular cartilage. Huangqi-Guizhi-Wuwu-Decoction (HGWD), a formula of Traditional Chinese Medicine (TCM), has shown promising clinical efficacy in the treatment of RA. However, the synergistic effects of key response components group (KRCG) in the treatment of RA have not been well studied. METHODS The components and potential targets of HGWD were extracted from published databases. A novel node influence calculation model that considers both the node control force and node bridging force was designed to construct the core response space (CRS) and obtain key effector proteins. An increasing coverage coefficient (ICC) model was employed to select the KRCG. The effectiveness and potential mechanism of action of KRCG were confirmed using CCK-8, qPCR, and western blotting. RESULTS A total of 796 key effector proteins were identified in CRS. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses confirmed their effectiveness and reliability. In addition, 59 components were defined as KRCG, which contributed to 85.05% of the target coverage of effective proteins. Of these, 677 targets were considered key reaction proteins, and their enriched KEGG pathways accounted for 84.89% of the pathogenic genes and 87.94% of the target genes. Finally, four components (moupinamide, 6-Paradol, hydrocinnamic acid, and protocatechuic acid) were shown to inhibit the inflammatory response in RA by synergistically targeting the cAMP, PI3K-Akt, and HIF-1α pathways. CONCLUSIONS We have introduced a novel model that aims to optimize and analyze the mechanisms behind herbal formulas. The model revealed the KRCG of HGWD for the treatment of RA and proposed that KRCG inhibits the inflammatory response by synergistically targeting cAMP, PI3K-Akt, and HIF-1α pathways. Overall, the novel model is plausible and reliable, offering a valuable reference for the secondary development of herbal formulas.
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Affiliation(s)
- Qinwen Liu
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Southern Medical University, Guangzhou, China
| | - Qian Luo
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Southern Medical University, Guangzhou, China
| | - Qiling Fan
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Southern Medical University, Guangzhou, China
| | - Yi Li
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Southern Medical University, Guangzhou, China
| | - Aiping Lu
- Institute of Integrated Bioinformedicine and Translational Science, Hong Kong Baptist University, Hong Kong, China.
- Guangdong-Hong Kong-Macau Joint Lab on Chinese Medicine and Immune Disease Research, Guangzhou, China.
| | - Daogang Guan
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China.
- Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Southern Medical University, Guangzhou, China.
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Wu MY, Ge YJ, Wang EJ, Liao QW, Ren ZY, Yu Y, Zhu G, Liu CP, Zhang MN, Su H, Shen HM, Chen Y, Wang L, Wang YT, Li M, Bian Z, Chai J, Ye RD, Lu JH. Enhancement of efferocytosis through biased FPR2 signaling attenuates intestinal inflammation. EMBO Mol Med 2023; 15:e17815. [PMID: 37994307 DOI: 10.15252/emmm.202317815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 10/20/2023] [Accepted: 10/24/2023] [Indexed: 11/24/2023] Open
Abstract
Efficient clearance of dying cells (efferocytosis) is an evolutionarily conserved process for tissue homeostasis. Genetic enhancement of efferocytosis exhibits therapeutic potential for inflammation resolution and tissue repair. However, pharmacological approaches to enhance efferocytosis remain sparse due to a lack of targets for modulation. Here, we report the identification of columbamine (COL) which enhances macrophage-mediated efferocytosis and attenuates intestinal inflammation in a murine colitis model. COL enhances efferocytosis by promoting LC3-associated phagocytosis (LAP), a non-canonical form of autophagy. Transcriptome analysis and pharmacological characterization revealed that COL is a biased agonist that occupies a part of the ligand binding pocket of formyl peptide receptor 2 (FPR2), a G-protein coupled receptor involved in inflammation regulation. Genetic ablation of the Fpr2 gene or treatment with an FPR2 antagonist abolishes COL-induced efferocytosis, anti-colitis activity and LAP. Taken together, our study identifies FPR2 as a potential target for modulating LC3-associated efferocytosis to alleviate intestinal inflammation and highlights the therapeutic value of COL, a natural and biased agonist of FPR2, in the treatment of inflammatory bowel disease.
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Affiliation(s)
- Ming-Yue Wu
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau SAR, China
- Department of Gastroenterology, The First Affiliated Hospital (Southwest Hospital), Third Military Medical University (Army Medical University), Chongqing, China
| | - Yun-Jun Ge
- Kobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong, Shenzhen, China
- Department of Basic Medical Science, Wuxi School of Medicine, Jiangnan University, Wuxi, China
| | - Er-Jin Wang
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau SAR, China
| | - Qi-Wen Liao
- Kobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong, Shenzhen, China
| | - Zheng-Yu Ren
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau SAR, China
| | - Yang Yu
- Engineering Research Center of Cell and Therapeutic Antibody Medicine, Ministry of Education, School of Pharmacy, Shanghai Jiao Tong University, Shanghai, China
| | - Guoyuan Zhu
- State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Macau SAR, China
| | - Chun-Ping Liu
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau SAR, China
- Department of Cardiovascular Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
- Guangdong-Hong Kong-Macau Joint Lab on Chinese Medicine and Immune Disease Research, University of Macau, Macau SAR, China
| | - Meng-Ni Zhang
- Department of Gastroenterology, The First Affiliated Hospital (Southwest Hospital), Third Military Medical University (Army Medical University), Chongqing, China
| | - Huanxing Su
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau SAR, China
| | - Han-Ming Shen
- Faculty of Health Sciences, University of Macau, Macau SAR, China
| | - Ye Chen
- Integrative Microecology Center, Department of Gastroenterology, Shenzhen Hospital, Southern Medical University, Shenzhen, Guangzhou, China
| | - Lei Wang
- Department of Cardiovascular Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yi-Tao Wang
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau SAR, China
| | - Min Li
- School of Chinese Medicine, Hong Kong Baptist University, Hongkong SAR, China
| | - Zhaoxiang Bian
- School of Chinese Medicine, Hong Kong Baptist University, Hongkong SAR, China
| | - Jin Chai
- Department of Gastroenterology, The First Affiliated Hospital (Southwest Hospital), Third Military Medical University (Army Medical University), Chongqing, China
| | - Richard D Ye
- Kobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong, Shenzhen, China
- The Second Affiliated Hospital, School of Medicine, The Chinese University of Hong Kong, Shenzhen, China
| | - Jia-Hong Lu
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau SAR, China
- Guangdong-Hong Kong-Macau Joint Lab on Chinese Medicine and Immune Disease Research, University of Macau, Macau SAR, China
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Ji KY, Liu C, Liu ZQ, Deng YF, Hou TJ, Cao DS. Comprehensive assessment of nine target prediction web services: which should we choose for target fishing? Brief Bioinform 2023; 24:6995377. [PMID: 36681902 DOI: 10.1093/bib/bbad014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 12/29/2022] [Accepted: 01/03/2023] [Indexed: 01/23/2023] Open
Abstract
Identification of potential targets for known bioactive compounds and novel synthetic analogs is of considerable significance. In silico target fishing (TF) has become an alternative strategy because of the expensive and laborious wet-lab experiments, explosive growth of bioactivity data and rapid development of high-throughput technologies. However, these TF methods are based on different algorithms, molecular representations and training datasets, which may lead to different results when predicting the same query molecules. This can be confusing for practitioners in practical applications. Therefore, this study systematically evaluated nine popular ligand-based TF methods based on target and ligand-target pair statistical strategies, which will help practitioners make choices among multiple TF methods. The evaluation results showed that SwissTargetPrediction was the best method to produce the most reliable predictions while enriching more targets. High-recall similarity ensemble approach (SEA) was able to find real targets for more compounds compared with other TF methods. Therefore, SwissTargetPrediction and SEA can be considered as primary selection methods in future studies. In addition, the results showed that k = 5 was the optimal number of experimental candidate targets. Finally, a novel ensemble TF method based on consensus voting is proposed to improve the prediction performance. The precision of the ensemble TF method outperforms the individual TF method, indicating that the ensemble TF method can more effectively identify real targets within a given top-k threshold. The results of this study can be used as a reference to guide practitioners in selecting the most effective methods in computational drug discovery.
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Affiliation(s)
- Kai-Yue Ji
- Xiangya School of Pharmaceutical Sciences, Central South University, Changsha 410013, Hunan, P. R. China
| | - Chong Liu
- Xiangya School of Pharmaceutical Sciences, Central South University, Changsha 410013, Hunan, P. R. China
| | - Zhao-Qian Liu
- Xiangya School of Pharmaceutical Sciences, Central South University, Changsha 410013, Hunan, P. R. China
| | - Ya-Feng Deng
- CarbonSilicon AI Technology Co., Ltd, Hangzhou, Zhejiang 310018, China
| | - Ting-Jun Hou
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Dong-Sheng Cao
- Xiangya School of Pharmaceutical Sciences, Central South University, Changsha 410013, Hunan, P. R. China
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