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In silico fragment-based discovery of CIB1-directed anti-tumor agents by FRASE-bot

Author

Listed:
  • Yi An

    (University of North Carolina)

  • Jiwoong Lim

    (University of North Carolina)

  • Marta Glavatskikh

    (University of North Carolina)

  • Xiaowen Wang

    (University of North Carolina
    University of Missouri, Columbia)

  • Jacqueline Norris-Drouin

    (University of North Carolina)

  • P. Brian Hardy

    (University of North Carolina)

  • Tina M. Leisner

    (University of North Carolina)

  • Kenneth H. Pearce

    (University of North Carolina)

  • Dmitri Kireev

    (University of North Carolina
    University of Missouri, Columbia)

Abstract

Chemical probes are an indispensable tool for translating biological discoveries into new therapies, though are increasingly difficult to identify since novel therapeutic targets are often hard-to-drug proteins. We introduce FRASE-based hit-finding robot (FRASE-bot), to expedite drug discovery for unconventional therapeutic targets. FRASE-bot mines available 3D structures of ligand-protein complexes to create a database of FRAgments in Structural Environments (FRASE). The FRASE database can be screened to identify structural environments similar to those in the target protein and seed the target structure with relevant ligand fragments. A neural network model is used to retain fragments with the highest likelihood of being native binders. The seeded fragments then inform ultra-large-scale virtual screening of commercially available compounds. We apply FRASE-bot to identify ligands for Calcium and Integrin Binding protein 1 (CIB1), a promising drug target implicated in triple negative breast cancer. FRASE-based virtual screening identifies a small-molecule CIB1 ligand (with binding confirmed in a TR-FRET assay) showing specific cell-killing activity in CIB1-dependent cancer cells, but not in CIB1-depletion-insensitive cells.

Suggested Citation

  • Yi An & Jiwoong Lim & Marta Glavatskikh & Xiaowen Wang & Jacqueline Norris-Drouin & P. Brian Hardy & Tina M. Leisner & Kenneth H. Pearce & Dmitri Kireev, 2024. "In silico fragment-based discovery of CIB1-directed anti-tumor agents by FRASE-bot," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-49892-9
    DOI: 10.1038/s41467-024-49892-9
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    References listed on IDEAS

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    1. 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.
    2. 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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