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Barcode-free hit discovery from massive libraries enabled by automated small molecule structure annotation

Author

Listed:
  • Edith Nol

    (Leiden University
    Oncode Institute)

  • Nils Alexander Haupt

    (Friedrich Schiller University Jena)

  • Qing Qing Gao

    (Leiden University)

  • Benthe A. M. Smit

    (Leiden University)

  • Martin Andre Hoffmann

    (Bright Giant GmbH)

  • Martin Engler-Lukajewski

    (Bright Giant GmbH)

  • Marcus Ludwig

    (Bright Giant GmbH)

  • Sean McKenna

    (Leiden University
    Oncode Institute)

  • J. Miguel Mata

    (Leiden University
    Oncode Institute)

  • Olivier J. M. Béquignon

    (Leiden University)

  • Gerard Westen

    (Leiden University)

  • Tiemen J. Wendel

    (Oncode Institute
    Leiden University Medical Center)

  • Sylvie M. Noordermeer

    (Oncode Institute
    Leiden University Medical Center)

  • Sebastian Böcker

    (Friedrich Schiller University Jena)

  • Sebastian Pomplun

    (Leiden University
    Oncode Institute)

Abstract

Affinity-selection platforms are powerful tools in early drug discovery, but current technologies – most notably DNA-encoded libraries (DELs) – are limited by synthesis complexity and incompatibility with nucleic acid-binding targets. We present a barcode-free self-encoded library (SEL) platform that enables direct screening of over half a million small molecules in a single experiment. SELs combine tandem mass spectrometry with custom software for automated structure annotation, eliminating the need for external tags for the identification of screening hits. We develop efficient, high-diversity synthesis protocols for a broad range of chemical scaffolds and benchmark the platform in affinity selections against carbonic anhydrase IX, identifying multiple nanomolar binders. We further apply SELs to flap endonuclease 1 (FEN1) – a disease related DNA-processing enzyme inaccessible to DELs – and discover potent inhibitors. Taken together, screening barcode-free libraries of this scale all at once represents an important development, enables access to novel target classes, and promises substantial impact on both academic and industrial early drug discovery.

Suggested Citation

  • Edith Nol & Nils Alexander Haupt & Qing Qing Gao & Benthe A. M. Smit & Martin Andre Hoffmann & Martin Engler-Lukajewski & Marcus Ludwig & Sean McKenna & J. Miguel Mata & Olivier J. M. Béquignon & Gera, 2025. "Barcode-free hit discovery from massive libraries enabled by automated small molecule structure annotation," Nature Communications, Nature, vol. 16(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-65282-1
    DOI: 10.1038/s41467-025-65282-1
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    References listed on IDEAS

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    1. Anthony J. Quartararo & Zachary P. Gates & Bente A. Somsen & Nina Hartrampf & Xiyun Ye & Arisa Shimada & Yasuhiro Kajihara & Christian Ottmann & Bradley L. Pentelute, 2020. "Ultra-large chemical libraries for the discovery of high-affinity peptide binders," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
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