Literature DB >> 21974780

Parsimonious discovery of synergistic drug combinations.

Bryan Severyn1, Robert A Liehr, Alex Wolicki, Kevin H Nguyen, Edward M Hudak, Marc Ferrer, Jeremy S Caldwell, Jeffrey D Hermes, Jing Li, Matthew Tudor.   

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: β-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.

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Year:  2011        PMID: 21974780     DOI: 10.1021/cb2003225

Source DB:  PubMed          Journal:  ACS Chem Biol        ISSN: 1554-8929            Impact factor:   5.100


  9 in total

1.  Combinatorial drug discovery in nanoliter droplets.

Authors:  Anthony Kulesa; Jared Kehe; Juan E Hurtado; Prianca Tawde; Paul C Blainey
Journal:  Proc Natl Acad Sci U S A       Date:  2018-06-13       Impact factor: 11.205

2.  Systems-level antimicrobial drug and drug synergy discovery.

Authors:  Terry Roemer; Charles Boone
Journal:  Nat Chem Biol       Date:  2013-04       Impact factor: 15.040

3.  Simulations suggest pharmacological methods for rescuing long-term potentiation.

Authors:  Paul Smolen; Douglas A Baxter; John H Byrne
Journal:  J Theor Biol       Date:  2014-07-15       Impact factor: 2.691

4.  Synergistic and antagonistic drug combinations depend on network topology.

Authors:  Ning Yin; Wenzhe Ma; Jianfeng Pei; Qi Ouyang; Chao Tang; Luhua Lai
Journal:  PLoS One       Date:  2014-04-08       Impact factor: 3.240

5.  Pooled screening for synergistic interactions subject to blocking and noise.

Authors:  Kyle Li; Doina Precup; Theodore J Perkins
Journal:  PLoS One       Date:  2014-01-16       Impact factor: 3.240

6.  Feedback activation of AMPK-mediated autophagy acceleration is a key resistance mechanism against SCD1 inhibitor-induced cell growth inhibition.

Authors:  Akito Ono; Osamu Sano; Ken-Ichi Kazetani; Takamichi Muraki; Keisuke Imamura; Hiroyuki Sumi; Junji Matsui; Hidehisa Iwata
Journal:  PLoS One       Date:  2017-07-13       Impact factor: 3.240

7.  Systematic identification of synergistic drug pairs targeting HIV.

Authors:  Xu Tan; Long Hu; Lovelace J Luquette; Geng Gao; Yifang Liu; Hongjing Qu; Ruibin Xi; Zhi John Lu; Peter J Park; Stephen J Elledge
Journal:  Nat Biotechnol       Date:  2012-10-14       Impact factor: 54.908

8.  Synergy Maps: exploring compound combinations using network-based visualization.

Authors:  Richard Lewis; Rajarshi Guha; Tamás Korcsmaros; Andreas Bender
Journal:  J Cheminform       Date:  2015-08-01       Impact factor: 5.514

9.  Modeling suggests combined-drug treatments for disorders impairing synaptic plasticity via shared signaling pathways.

Authors:  Paul Smolen; Marcelo A Wood; Douglas A Baxter; John H Byrne
Journal:  J Comput Neurosci       Date:  2020-11-11       Impact factor: 1.621

  9 in total

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