Systems pharmacology strategies for drug discovery and combination with applications to cardiovascular diseases

被引:62
作者
Li, Peng [1 ,2 ]
Chen, Jianxin [3 ]
Wang, Jinan [1 ,2 ]
Zhou, Wei [2 ]
Wang, Xia [1 ,2 ]
Li, Bohui [1 ,2 ]
Tao, Weiyang [1 ,2 ]
Wang, Wei [3 ]
Wang, Yonghua [1 ,2 ]
Yang, Ling [4 ]
机构
[1] Northwest A&F Univ, Ctr Bioinformat, Yangling 712100, Shaanxi, Peoples R China
[2] Northwest A&F Univ, Coll Life Sci, Yangling 712100, Shaanxi, Peoples R China
[3] Beijing Univ Chinese Med, Beijing 100029, Peoples R China
[4] Chinese Acad Sci, Dalian Inst Chem Phys, Lab Pharmaceut Resource Discovery, Dalian, Liaoning, Peoples R China
基金
中国国家自然科学基金;
关键词
Cardiovascular diseases; Drug discovery and combination; Systems pharmacology; Systems biology; SIGNALING PATHWAYS; NETWORK MEDICINE; ABSORPTION; TARGET; MECHANISMS; BIOLOGY; PHARMACOKINETICS; METABOLISM; APOPTOSIS; THERAPY;
D O I
10.1016/j.jep.2013.07.001
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
Ethnopharmacological relevance: Multi-target therapeutics is a promising paradigm for drug discovery which is expected to produce greater levels of efficacy with fewer adverse effects and toxicity than monotherapies. Medical herbs featuring multi-components and multi-targets may serve as valuable resources for network-based multi-target drug discovery. Materials and methods: In this study, we report an integrated systems pharmacology platform for drug discovery and combination, with a typical example applied to herbal medicines in the treatment of cardiovascular diseases. Results: First, a disease-specific drug-target network was constructed and examined at systems level to capture the key disease-relevant biology for discovery of multi-targeted agents. Second, considering an integration of disease complexity and multilevel connectivity, a comprehensive database of literature-reported associations, chemicals and pharmacology for herbal medicines was designed. Third, a large-scale systematic analysis combining pharmacokinetics, chemogenomics, pharmacology and systems biology data through computational methods was performed and validated experimentally, which results in a superior output of information for systematic drug design strategies for complex diseases. Conclusions: This strategy integrating different types of technologies is expected to help create new opportunities for drug discovery and combination. (C) 2013 Published by Elsevier Ireland Ltd.
引用
收藏
页码:93 / 107
页数:15
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