Diseases such as chronic pain with complex etiologies are unlikely to respond to single, target-specific therapeutics but rather require intervention at multiple points within a perturbed disease system. Such approaches are being enabled by the rise of computational methods to identify key points of intervention and by new screening techniques that focus on a relevant condition or phenotype, rather than a specific target. Here we apply an in silico network pharmacology approach to identify small-molecule compounds with the potential to selectively disrupt the structure of a chronic-pain specific disease network, which we validate using a novel phenotypic screen that recapitulates key aspects of neuronal and pain biology by measuring changes in neuronal excitability in native sensory neurons. The combination of network pharmacology with a phenotypic screen is a powerful approach; we show that hit rates increase from 26% to 42%. This represents a rational approach to the discovery of compounds with a poly-pharmacology based therapeutic value, which will be vital for the discovery of treatments for complex disease.
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http://dx.doi.org/10.1016/j.jmb.2018.07.016 | DOI Listing |
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