A network pharmacology approach for investigating the multi-target mechanisms of Huangqi in the treatment of colorectal cancer

Chu, Xiangxiang; Zhang, Yiran; Zhou, Lin; Zhao, Zhanzheng; Huangfu, Shu-Chen; Qiu, Shenghui; Guo, Yi; Ding, Hui; Huang, Ting; Chu, Xiaoli; Pan, Jinghua; Pan, Yun-long

doi:10.21037/tcr-20-2596

Cited by 11 publications

(3 citation statements)

References 47 publications

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“…Among the enriched CCs, anchored component of plasma membrane [ 98 ] was associated with CA4. collagen-containing extracellular matrix [ 99 ] was associated with ZG16. Four CCs term bicellular tight junction [ 100 ] apical junction complex [ 101 ] and cell–cell junction [ 102 ] were associated with CLCA1.…”

Section: Discussionmentioning

confidence: 99%

Bioinformatics screening of colorectal-cancer causing molecular signatures through gene expression profiles to discover therapeutic targets and candidate agents

et al. 2023

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Background Detection of appropriate receptor proteins and drug agents are equally important in the case of drug discovery and development for any disease. In this study, an attempt was made to explore colorectal cancer (CRC) causing molecular signatures as receptors and drug agents as inhibitors by using integrated statistics and bioinformatics approaches. Methods To identify the important genes that are involved in the initiation and progression of CRC, four microarray datasets (GSE9348, GSE110224, GSE23878, and GSE35279) and an RNA_Seq profiles (GSE50760) were downloaded from the Gene Expression Omnibus database. The datasets were analyzed by a statistical r-package of LIMMA to identify common differentially expressed genes (cDEGs). The key genes (KGs) of cDEGs were detected by using the five topological measures in the protein–protein interaction network analysis. Then we performed in-silico validation for CRC-causing KGs by using different web-tools and independent databases. We also disclosed the transcriptional and post-transcriptional regulatory factors of KGs by interaction network analysis of KGs with transcription factors (TFs) and micro-RNAs. Finally, we suggested our proposed KGs-guided computationally more effective candidate drug molecules compared to other published drugs by cross-validation with the state-of-the-art alternatives of top-ranked independent receptor proteins. Results We identified 50 common differentially expressed genes (cDEGs) from five gene expression profile datasets, where 31 cDEGs were downregulated, and the rest 19 were up-regulated. Then we identified 11 cDEGs (CXCL8, CEMIP, MMP7, CA4, ADH1C, GUCA2A, GUCA2B, ZG16, CLCA4, MS4A12 and CLDN1) as the KGs. Different pertinent bioinformatic analyses (box plot, survival probability curves, DNA methylation, correlation with immune infiltration levels, diseases-KGs interaction, GO and KEGG pathways) based on independent databases directly or indirectly showed that these KGs are significantly associated with CRC progression. We also detected four TFs proteins (FOXC1, YY1, GATA2 and NFKB) and eight microRNAs (hsa-mir-16-5p, hsa-mir-195-5p, hsa-mir-203a-3p, hsa-mir-34a-5p, hsa-mir-107, hsa-mir-27a-3p, hsa-mir-429, and hsa-mir-335-5p) as the key transcriptional and post-transcriptional regulators of KGs. Finally, our proposed 15 molecular signatures including 11 KGs and 4 key TFs-proteins guided 9 small molecules (Cyclosporin A, Manzamine A, Cardidigin, Staurosporine, Benzo[A]Pyrene, Sitosterol, Nocardiopsis Sp, Troglitazone, and Riccardin D) were recommended as the top-ranked candidate therapeutic agents for the treatment against CRC. Conclusion The findings of this study recommended that our proposed target proteins and agents might be considered as the potential diagnostic, prognostic and therapeutic signatures for CRC.

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Section: Discussionmentioning

confidence: 99%

Bioinformatics screening of colorectal-cancer causing molecular signatures through gene expression profiles to discover therapeutic targets and candidate agents

et al. 2023

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“…The discipline of network pharmacology has successfully surmounted past challenges associated with single-target, single-drug investigations. It has garnered considerable momentum in the identification of active constituents and comprehension of efficacious approaches [22]. The organization of pharmacological and structural health networks is aligned with the complete qualities of Propolis, which contributes to the advancement of our comprehension of the intricate mechanisms encompassing many ingredients, targets, and pathways in herbal therapy [23][24].…”

Section: Introductionmentioning

confidence: 99%

Exploring Therapeutic Potential of Nutraceutical Compounds from Propolis on MAPK1 Protein Using Bioinformatics Approaches as Anti-Coronavirus Disease 2019 (COVID-19)

Siregar,

Kustiawan,

Sari

et al. 2024

BIO Web Conf.

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This study explores the potential of propolis, a natural substance, as a gene therapy for treating COVID-19. Despite the advent of COVID-19 vaccines, their side effects pose new health challenges. Utilizing network pharmacology, this research identifies propolis compounds through various databases and assesses their ability to target proteins associated with COVID-19. MAPK1 emerges as a potential therapeutic target, and molecular docking reveals Broussoflavonol F, Glyasperin A, and Sulabiroins as promising compounds with strong binding affinities, i.e.,- 9.0, -9.0, and -8.8 kcal/mol, respectively, exceeding the native ligand (-7.2 kcal/mol). Molecular Dynamics displays stable complex behavior, with backbone RMSD values consistently below 4 Angstroms and RMSF simulations showing minimal fluctuations within ±2 Angstroms error. Moreover, MM-PBSA analysis further supports the strong binding of Broussoflavonol F, Glyasperin A, and Sulabiroins A, with relative binding energies of -122.82±89.65, 131.48±95.39, and -155.97±111,37 kJ/mol, respectively. These results indicate that propolis has potential as an anti-COVID-19 agent, primarily through inhibiting the MAPK1 pathway. However, further research is needed to validate these results and develop practical applications for COVID-19 therapy. This study underscores the significance of network pharmacology and computational models in understanding propolis mechanisms, offering potential directions for future research and treatment strategies against COVID-19.

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“…There are four main factors in TCM syndrome of CRC: deficiency, dampness, stasis and toxin ( 13 ). At present, in the clinical treatment of various malignant tumors, drugs to promote blood circulation and remove blood stasis are often used in the prescription of syndrome differentiation, and a lot of treatment experience has been obtained ( 14 , 15 ). There is therefore a need to investigate the role of SV in CRC, and the potential mechanisms.…”

Section: Introductionmentioning

confidence: 99%

Network pharmacology prediction and molecular docking-based strategy to discover the potential pharmacological mechanism of action of Wang Bu Liu Xing (Semen vaccariae) for colorectal cancer

Shi¹,

Zhang²,

Liu³

et al. 2023

J Gastrointest Oncol

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Background: Colorectal cancer (CRC) is the leading cause of cancer-related death worldwide. Wang Bu Liu Xing [Semen vaccariae (SV)] is a traditional Chinese medicine (TCM) ingredient with anti-angiogenic and anti-tumor effects. However, little research has been done on the ingredients found in SV or the putative process by which SV fights CRC, and this paper aims to reveal the components of SV that are effective in treating CRC. Methods:The open database and online platform were used in this study, Symptom Mapping (SymMap) and Traditional Chinese Medicine Systems Pharmacology (TCMSP) for SV ingredient and targets, Gene Expression Omnibus (GEO) for differentially expressed genes (DEGs) of CRC, Database for Annotation Visualization and Integrated Discovery (DAVID) for Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, STRING-Cytoscape for protein-protein interaction (PPI), AutoDockTools for Molecular docking and others. were conducted to determine how SV affects CRC and what are the most important components, potential targets, and signaling pathways. Results:The findings of the network pharmacology study indicated that swerchirin and CDK2 potential target gene for SV was connected to anti-CRC actions. SV may inhibit CRC by interacting with crucial targets like BCL2L1, CDK2, and SERPINE1. Additionally, KEGG analysis revealed that the p53 signaling pathway may be a driver of the anti-CRC impact of SV. Molecular docking showed that swerchirin can bind with its target protein in a good bond by intermolecular force.Conclusions: In this study, the pharmacological effects of SV were examined, along with its potential therapeutic impact on CRC. These effects of SV appear to be mediated via a variety of substances, targets, and pathways. SV exerts pharmacological effects in CRC, p53 signaling pathway is great value. The main molecular docking is CDK2 and swerchirin. Moreover, our research offers a promising method for characterizing therapeutic pathways and identifying molecules in TCM.

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A network pharmacology approach for investigating the multi-target mechanisms of Huangqi in the treatment of colorectal cancer

Cited by 11 publications

References 47 publications

Bioinformatics screening of colorectal-cancer causing molecular signatures through gene expression profiles to discover therapeutic targets and candidate agents

Bioinformatics screening of colorectal-cancer causing molecular signatures through gene expression profiles to discover therapeutic targets and candidate agents

Exploring Therapeutic Potential of Nutraceutical Compounds from Propolis on MAPK1 Protein Using Bioinformatics Approaches as Anti-Coronavirus Disease 2019 (COVID-19)

Network pharmacology prediction and molecular docking-based strategy to discover the potential pharmacological mechanism of action of Wang Bu Liu Xing (Semen vaccariae) for colorectal cancer

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