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Chemical space docking enables large-scale structure-based virtual screening to discover ROCK1 kinase inhibitors

Author

Listed:
  • Paul Beroza

    (Genentech)

  • James J. Crawford

    (Genentech)

  • Oleg Ganichkin

    (Proteros Biostructures GmbH)

  • Leo Gendelev

    (Genentech)

  • Seth F. Harris

    (Genentech)

  • Raphael Klein

    (BioSolveIT GmbH)

  • Anh Miu

    (Genentech)

  • Stefan Steinbacher

    (Proteros Biostructures GmbH)

  • Franca-Maria Klingler

    (BioSolveIT GmbH
    MSD)

  • Christian Lemmen

    (BioSolveIT GmbH)

Abstract

With the ever-increasing number of synthesis-on-demand compounds for drug lead discovery, there is a great need for efficient search technologies. We present the successful application of a virtual screening method that combines two advances: (1) it avoids full library enumeration (2) products are evaluated by molecular docking, leveraging protein structural information. Crucially, these advances enable a structure-based technique that can efficiently explore libraries with billions of molecules and beyond. We apply this method to identify inhibitors of ROCK1 from almost one billion commercially available compounds. Out of 69 purchased compounds, 27 (39%) have Ki values

Suggested Citation

  • Paul Beroza & James J. Crawford & Oleg Ganichkin & Leo Gendelev & Seth F. Harris & Raphael Klein & Anh Miu & Stefan Steinbacher & Franca-Maria Klingler & Christian Lemmen, 2022. "Chemical space docking enables large-scale structure-based virtual screening to discover ROCK1 kinase inhibitors," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-33981-8
    DOI: 10.1038/s41467-022-33981-8
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    References listed on IDEAS

    as
    1. Reed M. Stein & Hye Jin Kang & John D. McCorvy & Grant C. Glatfelter & Anthony J. Jones & Tao Che & Samuel Slocum & Xi-Ping Huang & Olena Savych & Yurii S. Moroz & Benjamin Stauch & Linda C. Johansson, 2020. "Virtual discovery of melatonin receptor ligands to modulate circadian rhythms," Nature, Nature, vol. 579(7800), pages 609-614, March.
    2. Jiankun Lyu & Sheng Wang & Trent E. Balius & Isha Singh & Anat Levit & Yurii S. Moroz & Matthew J. O’Meara & Tao Che & Enkhjargal Algaa & Kateryna Tolmachova & Andrey A. Tolmachev & Brian K. Shoichet , 2019. "Ultra-large library docking for discovering new chemotypes," Nature, Nature, vol. 566(7743), pages 224-229, February.
    3. David E. Gloriam, 2019. "Bigger is better in virtual drug screens," Nature, Nature, vol. 566(7743), pages 193-194, February.
    4. Christoph Gorgulla & Andras Boeszoermenyi & Zi-Fu Wang & Patrick D. Fischer & Paul W. Coote & Krishna M. Padmanabha Das & Yehor S. Malets & Dmytro S. Radchenko & Yurii S. Moroz & David A. Scott & Kons, 2020. "An open-source drug discovery platform enables ultra-large virtual screens," Nature, Nature, vol. 580(7805), pages 663-668, April.
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