Metabolomics and integrated network pharmacology analysis reveal Tricin as the active anti-cancer component of Weijing decoction by suppression of PRKCA and sphingolipid signaling

AbstractXuan-bai-cheng-qi decoction (XCD), a traditional Chinese medicine (TCM) prescription, has been widely used to treat a variety of respiratory diseases in China, especially to seriously infectious diseases such as acute lung injury (ALI). Due to the complexity of the chemical constituent, however, the underlying pharmacological mechanism of action of XCD is still unclear. To explore its protective mechanism on ALI, firstly, a network pharmacology experiment was conducted to construct a component-target network of XCD, which identified 46 active components and 280 predicted target genes. Then, RNA sequencing (RNA-seq) was used to screen differentially expressed genes (DEGs) between ALI model rats treated with and without XCD and 753 DEGs were found. By overlapping the target genes identified using network pharmacology and DEGs using RNA-seq, and subsequent protein–protein interaction (PPI) network analysis, 6 kernel targets such as vascular epidermal growth factor (VEGF), mammalian target of rapamycin (mTOR), AKT1, hypoxia-inducible factor-1α (HIF-1α), and phosphoinositide 3-kinase (PI3K) and gene of phosphate and tension homology deleted on chromsome ten (PTEN) were screened out to be closely relevant to ALI treatment. Verification experiments in the LPS-induced ALI model rats showed that XCD could alleviate lung tissue pathological injury through attenuating proinflammatory cytokines release such as tumor necrosis factor (TNF)-α, interleukin (IL)-6, and IL-1β. Meanwhile, both the mRNA and protein expression levels of PI3K, mTOR, HIF-1α, and VEGF in the lung tissues were down-regulated with XCD treatment. Therefore, the regulations of XCD on PI3K/mTOR/HIF-1α/VEGF signaling pathway was probably a crucial mechanism involved in the protective mechanism of XCD on ALI treatment.

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A Network Pharmacology-Based Study on Pharmacological Activities and Mechanisms of Essential Oil in Leaves of C. Grandis ‘Tomentosa’

10.21203/rs.3.rs-509976/v1 ◽

2021 ◽

Author(s):

Jieshu You ◽

Sheng-cai He ◽

Liang Chen ◽

Zhen-hui Guo ◽

Fei Gao ◽

...

Keyword(s):

Essential Oil ◽

Function Analysis ◽

Network Pharmacology ◽

Chemical Components ◽

Pathway Enrichment Analysis ◽

Health Food ◽

Disease Network ◽

Pharmacological Activities ◽

Integrated Network ◽

Target Disease

Abstract Background and Objective: Citrus grandis ‘Tomentosa’, as the fruit epicarp of C. grandis ‘Tomentosa’ or C. grandis (L.) Osbeck, is widely used in health food and medicine. Actually, based on our survey results, there are also rich essential oils with bioativities in leaves, but the chemical compounds in this part and relevant pharmacological activities have never been studied systematically yet. Therefore, this study was to preliminarily decipher the pharmacological activities and mechanisms of the essential oil in leaves of C. grandis ‘Tomentosa’ by an integrated network pharmacology approach. Methods: Essential oil compositions from leaves of C. grandis ‘Tomentosa’ were identified using GC-MS/MS. And then the targets of these oil compositions were predicted and screened from TCMSP, SwissTargetPrediction, STITCH and SEA databases. STRING database was used to construct the protein-protein interaction networks, and the eligible protein targets were input into WebGestalt 2019 to carry out GO enrichment and KEGG pathway enrichment analysis. Based on the potential targets, disease enrichment information was obtained by TTD databases. Cytoscape software was used to construct the component-target-disease network diagrams. Results: Finally, 61 essential oil chemical components were identified by GC-MS/MS, which correspond to 679 potential targets. Biological function analysis showed that there were 12, 19, and 12 GO entries related to biological processes, cell components and molecular functions, respectively. 43 KEGG pathways were identified, of which the most significant categories were terpenoid backbone biosynthesis, TNF signaling pathway and leishmaniasis. The component-target-disease network diagram revealed that the essential oil compositions in leaves of C. grandis ‘Tomentosa’ could treat tumors, immune diseases, neurodegenerative diseases and respiratory diseases, which were highly related to CHRM1, PTGS2, CASP3, MAP2K1 and CDC25B.Conclusion: This study may provide a new insight into C. grandis ‘Tomentosa’ or C. grandis (L.) Osbeck and may provide useful information for future utilization and development.

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Study on the mechanism of anti-cancer action of rosa roxbughii tratt based on network pharmacology

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/914/1/012010 ◽

2020 ◽

Vol 914 ◽

pp. 012010

Author(s):

Ying Mei ◽

Xiang Pu ◽

Xiangling Qu

Keyword(s):

Network Pharmacology ◽

Anti Cancer

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Uncovering the anti-proliferation mechanism and bioactive compounds in red kidney bean coat against B16-F10 melanoma cells by metabolomics and network pharmacology analysis

Food & Function ◽

10.1039/c8fo01738g ◽

2019 ◽

Vol 10 (2) ◽

pp. 912-924 ◽

Cited By ~ 2

Author(s):

Jia-Hui Nie ◽

Jian-Xiang Huang ◽

Qing-Rong Wu ◽

Xue-Mei Qin ◽

Zhen-Yu Li

Keyword(s):

Bioactive Compounds ◽

Melanoma Cells ◽

Kidney Bean ◽

Network Pharmacology ◽

Chemical Compositions ◽

Anti Cancer ◽

Red Kidney Bean ◽

Cancer Activity

In this study, coat (RKBC) and kernel (RKBK) extracts of red kidney bean were prepared, and their chemical compositions and potential anti-cancer activity against B16-F10 cells were evaluated.

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Network pharmacology-based virtual screening of natural products from Clerodendrum species for identification of novel anti-cancer therapeutics

Molecular BioSystems ◽

10.1039/c6mb00807k ◽

2017 ◽

Vol 13 (2) ◽

pp. 406-416 ◽

Cited By ~ 18

Author(s):

Barbi Gogoi ◽

Dhrubajyoti Gogoi ◽

Yumnam Silla ◽

Bibhuti Bhushan Kakoti ◽

Brijmohan Singh Bhau

Keyword(s):

Natural Products ◽

Virtual Screening ◽

Cancer Therapeutics ◽

Network Pharmacology ◽

Anticancer Compounds ◽

Pharmacological Approach ◽

Anti Cancer

In the present work, latest network pharmacological approach has been used for the screening of natural anticancer compounds from Clerodendrum species.

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Molecular mechanism of the anti-lung cancer effect of Jin Ning Fang based on network pharmacology and experimental verification

10.1101/2021.07.26.453881 ◽

2021 ◽

Author(s):

Chunxiao Wu ◽

Qiquan Yu ◽

Weizhen Shou ◽

Kun Zhang ◽

Yang Li ◽

...

Keyword(s):

Lung Cancer ◽

Molecular Mechanism ◽

Mrna Level ◽

A549 Cells ◽

Functional Enrichment ◽

Network Pharmacology ◽

Apoptosis Pathway ◽

Protein Protein Interaction ◽

Anti Cancer

Background: Jin Ning Fang (JNF) is widely used as an adjuvant therapy for lung cancer. However, its molecular mechanism against lung cancer is still unclear. Methods: The chemical compounds JNF were screened from the TCMSP database and its target proteins were then predicted. The genes related to lung cancer were collected from the CTD and DisGeNET databases. Next, targets were integrated with disease-related genes to obtain candidate genes. Functional enrichment and protein-protein interaction (PPI) analysis were also performed, followed by construction of pharmacological network. Meanwhile, Autodock was used to assess the affinity between targets and compound. Finally, the anti-cancer effect of JNF on lung cancer cells was detected and some predicted key genes was validated by using real-time PCR. Results: Twenty-five overlapping targets were obtained, and pathway analysis showed that JNF might exert its anti-cancer function by regulating some biological pathways, such as apoptosis pathway. PPI and pharmacological network revealed several core targets (such as AKT1, AR, and ESR1) and three compounds (quercetin, calcium carbonate, and beta-sitosterol). Then, beta-sitosterol had a high affinity with AKT1, AR, and ESR1. Further in vitro experiments confirmed that JNF could inhibit proliferation and promote apoptosis of A549 cells. The expression of FDPS, PIM1, VCAM1, SLC29A1, NQO1, and ESR1 were significantly decreased, while mRNA level of AR and ANPEP were markedly increased after JNF treatment. Conclusion: JNF may exert anti-lung cancer effect through multiple targets and pathways, and identified genes may be used as potential biomarkers for diagnosis and treatment of lung cancer.

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