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Large-Scale QSAR in Target Prediction and Phenotypic HTS Assessment

Authors

  • Jeremy L. Jenkins

    Corresponding author
    1. Developmental and Molecular Pathways, Quantitative Biology, Novartis Institutes for BioMedical Research, 220 Massachusetts Ave., Cambridge, MA 02139 phone: 617-871-7155
    • Developmental and Molecular Pathways, Quantitative Biology, Novartis Institutes for BioMedical Research, 220 Massachusetts Ave., Cambridge, MA 02139 phone: 617-871-7155
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Abstract

The advent of in silico compound target prediction offers a potential paradigm shift in how large compound collections are understood and used strategically in high-throughput screens (HTS). Specifically, phenotypic HTS hits may be annotated both with known targets and predicted targets using large-scale QSAR models, enabling a more sophisticated hit assessment. Efforts in massive bioactivity data integration and standardization is empowering such compound-target annotations. These approaches differ fundamentally from the traditional role of QSAR in lead optimization and binding affinity predictions to global, probabilistic target predictions for thousands of human proteins.

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