High-throughput screening normalized to biological response: Application to antiviral drug discovery

Dhara A. Patel, Anand C. Patel, William C. Nolan, Guangming Huang, Arthur G. Romero, Nichole Charlton, Eugene Agapov, Yong Zhang, Michael J. Holtzman

Research output: Contribution to journalArticle

11 Scopus citations

Abstract

The process of conducting cell-based phenotypic screens can result in data sets from small libraries or portions of large libraries, making accurate hit picking from multiple data sets important for efficient drug discovery. Here, we describe a screen design and data analysis approach that allow for normalization not only between quadrants and plates but also between screens or batches in a robust, quantitative fashion, enabling hit selection from multiple data sets. We independently screened the MicroSource Spectrum and NCI Diversity Set II libraries using a cell-based phenotypic high-throughput screening (HTS) assay that uses an interferon-stimulated response element (ISRE)-driven luciferase-reporter assay to identify interferon (IFN) signal enhancers. Inclusion of a per-plate, per-quadrant IFN dose-response standard curve enabled conversion of ISRE activity to effective IFN concentrations. We identified 45 hits based on a combined z score ≥2.5 from the two libraries, and 25 of 35 available hits were validated in a compound concentration-response assay when tested using fresh compound. The results provide a basis for further analysis of chemical structure in relation to biological function. Together, the results establish an HTS method that can be extended to screening for any class of compounds that influence a quantifiable biological response for which a standard is available.

Original languageEnglish
Pages (from-to)119-130
Number of pages12
JournalJournal of Biomolecular Screening
Volume19
Issue number1
DOIs
StatePublished - Jan 1 2014

Keywords

  • cell-based assay
  • interferon signal enhancer
  • phenotypic drug discovery
  • quantitative HTS
  • statin

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