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Enabling the hypothesis-driven prioritization of ligand candidates in big databases: Screenlamp and its application to GPCR inhibitor discovery for invasive species control

View ORCID ProfileSebastian Raschka, Anne M. Scott, Nan Liu, Santosh Gunturu, Mar Huertas, Weiming Li, Leslie A. Kuhn
doi: https://doi.org/10.1101/249151
Sebastian Raschka
1Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA
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  • ORCID record for Sebastian Raschka
Anne M. Scott
2Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA
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Nan Liu
1Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA
3Department of Chemistry, Michigan State University, East Lansing, MI 48824, USA
4Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48824, USA
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Santosh Gunturu
1Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA
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Mar Huertas
2Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA
5Current address: Department of Biology, Texas State University, San Marcos, TX 78666, USA
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Weiming Li
2Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA
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Leslie A. Kuhn
1Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA
2Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA
4Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48824, USA
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  • For correspondence: KuhnL@msu.edu
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Abstract

While the advantage of screening vast databases of molecules to cover greater molecular diversity is often mentioned, in reality, only a few studies have been published demonstrating inhibitor discovery by screening more than a million compounds for features that mimic a known three-dimensional ligand. Two factors contribute: the general difficulty of discovering potent inhibitors, and the lack of free, user-friendly software to incorporate project-specific knowledge and user hypotheses into 3D ligand-based screening. The Screenlamp modular toolkit presented here was developed with these needs in mind. We show Screenlamp’s ability to screen more than 12 million commercially available molecules and identify potent in vivo inhibitors of a G protein-coupled bile acid receptor within the first year of a discovery project. This pheromone receptor governs sea lamprey reproductive behavior, and to our knowledge, this project is the first to establish the efficacy of computational screening in discovering lead compounds for aquatic invasive species control. Significant enhancement in activity came from selecting compounds based on one of the hypotheses: that matching two distal oxygen groups in the three-dimensional structure of the pheromone is crucial for activity. Six of the 15 most active compounds met these criteria. A second hypothesis – that presence of an alkyl sulfate side chain results in high activity – identified another 6 compounds in the top 10, demonstrating the significant benefits of hypothesis-driven screening.

Footnotes

  • Abbreviations
    2D
    two-dimensional
    3D
    three-dimensional
    3kPZS
    3-keto petromyzonol sulfate
    3sPZS
    trisulfated petromyzonol sulfate
    GLL
    GPCR Ligand Library
    GPCR
    G-protein-coupled receptor
    Mgβ1AR
    β1-adrenergic receptor from Meleagris gallopavo;
    PAIN
    pan-assay interference compound
    PZS
    petromyzonol sulfate
    SQL
    Structured Query Language
    SLOR1
    sea lamprey olfactory receptor 1
    TFM
    trifluoromethyl nitrophenol
    EOG
    electro-olfactogram

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Posted January 17, 2018.
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Enabling the hypothesis-driven prioritization of ligand candidates in big databases: Screenlamp and its application to GPCR inhibitor discovery for invasive species control
Sebastian Raschka, Anne M. Scott, Nan Liu, Santosh Gunturu, Mar Huertas, Weiming Li, Leslie A. Kuhn
bioRxiv 249151; doi: https://doi.org/10.1101/249151
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Enabling the hypothesis-driven prioritization of ligand candidates in big databases: Screenlamp and its application to GPCR inhibitor discovery for invasive species control
Sebastian Raschka, Anne M. Scott, Nan Liu, Santosh Gunturu, Mar Huertas, Weiming Li, Leslie A. Kuhn
bioRxiv 249151; doi: https://doi.org/10.1101/249151

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