Integrated Analysis of Drug-Induced Gene Expression Profiles Predicts Novel hERG Inhibitors

Joseph J. Babcock, Fang Du, Kaiping Xu, Sarah J. Wheelan, Min Li

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


Growing evidence suggests that drugs interact with diverse molecular targets mediating both therapeutic and toxic effects. Prediction of these complex interactions from chemical structures alone remains challenging, as compounds with different structures may possess similar toxicity profiles. In contrast, predictions based on systems-level measurements of drug effect may reveal pharmacologic similarities not evident from structure or known therapeutic indications. Here we utilized drug-induced transcriptional responses in the Connectivity Map (CMap) to discover such similarities among diverse antagonists of the human ether-à-go-go related (hERG) potassium channel, a common target of promiscuous inhibition by small molecules. Analysis of transcriptional profiles generated in three independent cell lines revealed clusters enriched for hERG inhibitors annotated using a database of experimental measurements (hERGcentral) and clinical indications. As a validation, we experimentally identified novel hERG inhibitors among the unannotated drugs in these enriched clusters, suggesting transcriptional responses may serve as predictive surrogates of cardiotoxicity complementing existing functional assays.

Original languageEnglish (US)
Article numbere69513
JournalPloS one
Issue number7
StatePublished - Jul 23 2013
Externally publishedYes

ASJC Scopus subject areas

  • General


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