Systems biology approaches for advancing the discovery of effective drug combinations

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• 作者：Karen A Ryall (1)
  Aik Choon Tan (1) (2) (3)
  
  1. Translational Bioinformatics and Cancer Systems Biology Laboratory ; Division of Medical Oncology ; Department of Medicine ; School of Medicine ; University of Colorado Anschutz Medical Campus ; 12801 E.17th Ave. ; L18-8116 ; Aurora ; CO ; 80045 ; USA
  2. Department of Biostatistics and Informatics ; Colorado School of Public Health ; University of Colorado Anschutz Medical Campus ; Aurora ; CO ; USA
  3. Department of Computer Science and Engineering ; Korea University ; Seoul ; South Korea
  
• 关键词：Drug combinations ; Systems biology ; Computational modeling ; Cancer ; Drug discovery
• 刊名：Journal of Cheminformatics
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：7
• 期：1
• 全文大小：1,157 KB
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• 刊物类别：Physics and Astronomy
• 刊物主题：Computer Applications in Chemistry
  Theoretical and Computational Chemistry
  Computational Biology/Bioinformatics
  Documentation and Information in Chemistry
  
• 出版者：Chemistry Central Ltd
• ISSN：1758-2946

文摘

Complex diseases like cancer are regulated by large, interconnected networks with many pathways affecting cell proliferation, invasion, and drug resistance. However, current cancer therapy predominantly relies on the reductionist approach of one gene-one disease. Combinations of drugs may overcome drug resistance by limiting mutations and induction of escape pathways, but given the enormous number of possible drug combinations, strategies to reduce the search space and prioritize experiments are needed. In this review, we focus on the use of computational modeling, bioinformatics and high-throughput experimental methods for discovery of drug combinations. We highlight cutting-edge systems approaches, including large-scale modeling of cell signaling networks, network motif analysis, statistical association-based models, identifying correlations in gene signatures, functional genomics, and high-throughput combination screens. We also present a list of publicly available data and resources to aid in discovery of drug combinations. Integration of these systems approaches will enable faster discovery and translation of clinically relevant drug combinations. Graphical abstract Spectrum of Systems Biology Approaches for Drug Combinations.