Synergy Maps: Exploring compound combinations using network-based visualization

Richard Lewis, Rajarshi Guha, Tamás Korcsmaros, Andreas Bender

Research output: Contribution to journalArticle

17 Citations (Scopus)


Background: The phenomenon of super-additivity of biological response to compounds applied jointly, termed synergy, has the potential to provide many therapeutic benefits. Therefore, high throughput screening of compound combinations has recently received a great deal of attention. Large compound libraries and the feasibility of all-pairs screening can easily generate large, information-rich datasets. Previously, these datasets have been visualized using either a heat-map or a network approach - however these visualizations only partially represent the information encoded in the dataset. Results: A new visualization technique for pairwise combination screening data, termed "Synergy Maps", is presented. In a Synergy Map, information about the synergistic interactions of compounds is integrated with information about their properties (chemical structure, physicochemical properties, bioactivity profiles) to produce a single visualization. As a result the relationships between compound and combination properties may be investigated simultaneously, and thus may afford insight into the synergy observed in the screen. An interactive web app implementation, available at, has been developed for public use, which may find use in navigating and filtering larger scale combination datasets. This tool is applied to a recent all-pairs dataset of anti-malarials, tested against Plasmodium falciparum, and a preliminary analysis is given as an example, illustrating the disproportionate synergism of histone deacetylase inhibitors previously described in literature, as well as suggesting new hypotheses for future investigation. Conclusions: Synergy Maps improve the state of the art in compound combination visualization, by simultaneously representing individual compound properties and their interactions. The web-based tool allows straightforward exploration of combination data, and easier identification of correlations between compound properties and interactions.

Original languageEnglish
Article number36
JournalJournal of Cheminformatics
Issue number1
Publication statusPublished - Aug 1 2015



  • Compound combinations
  • Dimensionality reduction
  • Mixtures
  • Network
  • Synergy
  • Visualization

ASJC Scopus subject areas

  • Computer Science Applications
  • Physical and Theoretical Chemistry
  • Computer Graphics and Computer-Aided Design
  • Library and Information Sciences

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