Integrating systematic biological and proteomics strategies to explore the pharmacological mechanism of danshen yin modified on atherosclerosis

• Published in: Journal of cellular and molecular medicine 2020-12, Vol.24 (23), p.13876-13898
• Main Authors: Yang, Kailin, Zeng, Liuting, Ge, Anqi, Pan, Xiaoping, Bao, Tingting, Long, Zhiyong, Tong, Qiaozhen, Yuan, Mengxia, Zhu, Xiaofei, Ge, Jinwen, Huang, Zhengde
• Format: Article
• Language: English
• Subjects: Angina pectoris; Animal research; Animals; ApoE‐/‐ mouse; Apolipoprotein E; Apolipoproteins E - deficiency; Arteriosclerosis; Atherosclerosis; Atherosclerosis - blood; Atherosclerosis - etiology; Atherosclerosis - metabolism; Biomarkers; Cardiovascular disease; Chinese medicine; Computational Biology - methods; Computer programs; Danshen Yin Modified; Disease Models, Animal; Drugs; Drugs, Chinese Herbal - pharmacology; Endothelial Cells - metabolism; Endothelial Cells - ultrastructure; Enzymes; Gene Expression Profiling; Gene Ontology; Genes; Heart; High-performance liquid chromatography; Immunohistochemistry; Ischemia; Laboratory animals; Medical research; Medicine, Chinese Traditional; Mice; Mice, Knockout; Original; Pharmacokinetics; Protein interaction; Protein Interaction Mapping; Protein Interaction Maps; Proteins; Proteome - drug effects; Proteomics; Proteomics - methods; reverse transcription‐PCR; Signal transduction; Software; systematic biology; Systems Biology - methods; Traditional Chinese medicine
• ISSN: 1582-1838; 1582-4934
• DOI: 10.1111/jcmm.15979

This research utilized the systematic biological and proteomics strategies to explore the regulatory mechanism of Danshen Yin Modified (DSYM) on atherosclerosis (AS) biological network. The traditional Chinese medicine database and HPLC was used to find the active compounds of DSYM, Pharmmapper database was used to predict potential targets, and OMIM database and GeneCards database were used to collect AS targets. String database was utilized to obtain the other protein of proteomics proteins and the protein‐protein interaction (PPI) data of DSYM targets, AS genes, proteomics proteins and other proteins. The Cytoscape 3.7.1 software was utilized to construct and analyse the network. The DAVID database is used to discover the biological processes and signalling pathways that these proteins aggregate. Finally, animal experiments and proteomics analysis were used to further verify the prediction results. The results showed that 140 active compounds, 405 DSYM targets and 590 AS genes were obtained, and 51 differentially expressed proteins were identified in the DSYM‐treated ApoE‐/‐ mouse AS model. A total of 4 major networks and a number of their derivative networks were constructed and analysed. The prediction results showed that DSYM can regulate AS‐related biological processes and signalling pathways. Animal experiments have also shown that DSYM has a therapeutic effect on ApoE‐/‐mouse AS model (P