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1.
Nat Biotechnol ; 27(7): 659-66, 2009 Jul.
Article in English | MEDLINE | ID: mdl-19581876

ABSTRACT

Drug combinations are a promising strategy to overcome the compensatory mechanisms and unwanted off-target effects that limit the utility of many potential drugs. However, enthusiasm for this approach is tempered by concerns that the therapeutic synergy of a combination will be accompanied by synergistic side effects. Using large scale simulations of bacterial metabolism and 94,110 multi-dose experiments relevant to diverse diseases, we provide evidence that synergistic drug combinations are generally more specific to particular cellular contexts than are single agent activities. We highlight six combinations whose selective synergy depends on multitarget drug activity. For one anti-inflammatory example, we show how such selectivity is achieved through differential expression of the drugs' targets in cell types associated with therapeutic, but not toxic, effects and validate its therapeutic relevance in a rat model of asthma. The context specificity of synergistic combinations creates many opportunities for therapeutically relevant selectivity and enables improved control of complex biological systems.


Subject(s)
Drug Synergism , Drug Therapy, Combination , Pharmaceutical Preparations/administration & dosage , Pharmacology , Animals , Cell Line, Tumor , Disease Models, Animal , Drug Discovery , Drug-Related Side Effects and Adverse Reactions , Escherichia coli/drug effects , Escherichia coli/growth & development , Humans , Male , Models, Biological , Rats , Rats, Sprague-Dawley , Reproducibility of Results
2.
Mol Syst Biol ; 3: 80, 2007.
Article in English | MEDLINE | ID: mdl-17332758

ABSTRACT

Efforts to construct therapeutically useful models of biological systems require large and diverse sets of data on functional connections between their components. Here we show that cellular responses to combinations of chemicals reveal how their biological targets are connected. Simulations of pathways with pairs of inhibitors at varying doses predict distinct response surface shapes that are reproduced in a yeast experiment, with further support from a larger screen using human tumour cells. The response morphology yields detailed connectivity constraints between nearby targets, and synergy profiles across many combinations show relatedness between targets in the whole network. Constraints from chemical combinations complement genetic studies, because they probe different cellular components and can be applied to disease models that are not amenable to mutagenesis. Chemical probes also offer increased flexibility, as they can be continuously dosed, temporally controlled, and readily combined. After extending this initial study to cover a wider range of combination effects and pathway topologies, chemical combinations may be used to refine network models or to identify novel targets. This response surface methodology may even apply to non-biological systems where responses to targeted perturbations can be measured.


Subject(s)
Drug Combinations , Metabolic Networks and Pathways/drug effects , Models, Statistical , Systems Biology , Computer Simulation , Drug Synergism , Gene Expression Regulation, Fungal/drug effects , HCT116 Cells , Humans , Models, Biological , Saccharomyces cerevisiae/drug effects , Sterols/biosynthesis
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