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首页> 外文期刊>Combinatorial chemistry & high throughput screening >Integrated Transcriptomics and Reverse Pharmacophore Mapping-based Network Pharmacology to Explore the Mechanisms of Natural Compounds against Doxorubicin-induced Cardiotoxicity
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Integrated Transcriptomics and Reverse Pharmacophore Mapping-based Network Pharmacology to Explore the Mechanisms of Natural Compounds against Doxorubicin-induced Cardiotoxicity

机译：Integrated Transcriptomics and Reverse Pharmacophore Mapping-based Network Pharmacology to Explore the Mechanisms of Natural Compounds against Doxorubicin-induced Cardiotoxicity

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Background: Doxorubicin-Induced Cardiotoxicity (DIC) has greatly limited the clinical benefits of this frontline drug in oncotherapy. Drug combination with Natural Compounds (NCs) that possess potency against DIC is considered as a promising intervention strategy. However, the Mechanisms of Action (MoAs) underlying such drug interactions remain poorly understood. The aim of this study was to systematically pursuit of the molecular mechanisms of NCs against DIC. Methods: First, the gene expression signatures of DIC were characterized from transcriptomics datasets with doxorubicin-treated and untreated cardiomyocytes using differentially expressed gene identification, functional enrichment analysis, and protein-protein interaction network analysis. Secondly, reverse pharmacophore mapping-based network pharmacology was employed to illustrate the MoAs of 82 publicly reported NCs with anti-DIC potency. Cluster analysis based on their enriched pathways was performed to gain systematic insights into the anti-DIC mechanisms of the NCs. Finally, the typical compounds were validated using Gene Set Enrichment Analysis (GSEA) of the relevant gene expression profiles from a public gene expression database. Results: Based on their anti-DIC MoAs, the 82 NCs could be divided into four groups, which corresponded to ten MoA clusters. GSEA and literature evidence on these compounds were provided to validate the MoAs identified through this bioinformatics analysis. The results suggested that NCs exerted potency against DIC through both common and different MoAs. Conclusion: This strategy integrating different types of bioinformatics approaches is expected to create new insights for elucidating the MoAs of NCs against DIC.

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