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ACS Chem Biol ; 6(12): 1391-8, 2011 Dec 16.
Article in English | MEDLINE | ID: mdl-21974780

ABSTRACT

Combination therapies that enhance efficacy or permit reduced dosages to be administered have seen great success in a variety of therapeutic applications. More fundamentally, the discovery of epistatic pathway interactions not only informs pharmacologic intervention but can be used to better understand the underlying biological system. There is, however, no systematic and efficient method to identify interacting activities as candidates for combination therapy and, in particular, to identify those with synergistic activities. We devised a pooled, self-deconvoluting screening paradigm for the efficient comprehensive interrogation of all pairs of compounds in 1000-compound libraries. We demonstrate the power of the method to recover established synergistic interactions between compounds. We then applied this approach to a cell-based screen for anti-inflammatory activities using an assay for lipopolysaccharide/interferon-induced acute phase response of a monocytic cell line. The described method, which is >20 times as efficient as a naïve approach, was used to test all pairs of 1027 bioactive compounds for interleukin-6 suppression, yielding 11 pairs of compounds that show synergy. These 11 pairs all represent the same two activities: ß-adrenergic receptor agonists and phosphodiesterase-4 inhibitors. These activities both act through cyclic AMP elevation and are known to be anti-inflammatory alone and to synergize in combination. Thus we show proof of concept for a robust, efficient technique for the identification of synergistic combinations. Such a tool can enable qualitatively new scales of pharmacological research and chemical genetics.


Subject(s)
Adrenergic beta-Agonists/pharmacology , Drug Discovery/methods , Drug Synergism , Interleukin-6/antagonists & inhibitors , Phosphodiesterase 4 Inhibitors/pharmacology , Small Molecule Libraries/analysis , Cell Survival/drug effects , Combinatorial Chemistry Techniques , Drug Combinations , Drug Evaluation, Preclinical/methods , Drug Interactions , Epistasis, Genetic , HCT116 Cells , Humans
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