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Massively parallel de novo protein design for targeted therapeutics

Author

Listed:
  • Aaron Chevalier

    (University of Washington
    Institute for Protein Design, University of Washington)

  • Daniel-Adriano Silva

    (University of Washington
    Institute for Protein Design, University of Washington)

  • Gabriel J. Rocklin

    (University of Washington
    Institute for Protein Design, University of Washington)

  • Derrick R. Hicks

    (University of Washington
    Institute for Protein Design, University of Washington
    Molecular and Cellular Biology Program, University of Washington)

  • Renan Vergara

    (University of Washington
    Institute for Protein Design, University of Washington
    Facultad de Medicina, Universidad Nacional Autónoma de México (UNAM), Ciudad Universitaria)

  • Patience Murapa

    (University of Washington)

  • Steffen M. Bernard

    (The Scripps Research Institute
    The Skaggs Institute for Chemical Biology, The Scripps Research Institute)

  • Lu Zhang

    (State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences
    The Hong Kong University of Science and Technology)

  • Kwok-Ho Lam

    (University of California)

  • Guorui Yao

    (University of California)

  • Christopher D. Bahl

    (University of Washington
    Institute for Protein Design, University of Washington)

  • Shin-Ichiro Miyashita

    (Boston Children’s Hospital
    Harvard Medical School)

  • Inna Goreshnik

    (University of Washington)

  • James T. Fuller

    (University of Washington)

  • Merika T. Koday

    (University of Washington
    Virvio Inc.)

  • Cody M. Jenkins

    (University of Washington)

  • Tom Colvin

    (University of Washington)

  • Lauren Carter

    (University of Washington
    Institute for Protein Design, University of Washington)

  • Alan Bohn

    (University of Washington)

  • Cassie M. Bryan

    (University of Washington
    Institute for Protein Design, University of Washington)

  • D. Alejandro Fernández-Velasco

    (Facultad de Medicina, Universidad Nacional Autónoma de México (UNAM), Ciudad Universitaria)

  • Lance Stewart

    (Institute for Protein Design, University of Washington)

  • Min Dong

    (Boston Children’s Hospital
    Harvard Medical School)

  • Xuhui Huang

    (The Hong Kong University of Science and Technology)

  • Rongsheng Jin

    (University of California)

  • Ian A. Wilson

    (The Scripps Research Institute
    The Skaggs Institute for Chemical Biology, The Scripps Research Institute)

  • Deborah H. Fuller

    (University of Washington)

  • David Baker

    (University of Washington
    Institute for Protein Design, University of Washington)

Abstract

De novo protein design holds promise for creating small stable proteins with shapes customized to bind therapeutic targets. We describe a massively parallel approach for designing, manufacturing and screening mini-protein binders, integrating large-scale computational design, oligonucleotide synthesis, yeast display screening and next-generation sequencing. We designed and tested 22,660 mini-proteins of 37–43 residues that target influenza haemagglutinin and botulinum neurotoxin B, along with 6,286 control sequences to probe contributions to folding and binding, and identified 2,618 high-affinity binders. Comparison of the binding and non-binding design sets, which are two orders of magnitude larger than any previously investigated, enabled the evaluation and improvement of the computational model. Biophysical characterization of a subset of the binder designs showed that they are extremely stable and, unlike antibodies, do not lose activity after exposure to high temperatures. The designs elicit little or no immune response and provide potent prophylactic and therapeutic protection against influenza, even after extensive repeated dosing.

Suggested Citation

  • Aaron Chevalier & Daniel-Adriano Silva & Gabriel J. Rocklin & Derrick R. Hicks & Renan Vergara & Patience Murapa & Steffen M. Bernard & Lu Zhang & Kwok-Ho Lam & Guorui Yao & Christopher D. Bahl & Shin, 2017. "Massively parallel de novo protein design for targeted therapeutics," Nature, Nature, vol. 550(7674), pages 74-79, October.
  • Handle: RePEc:nat:nature:v:550:y:2017:i:7674:d:10.1038_nature23912
    DOI: 10.1038/nature23912
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    Citations

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    Cited by:

    1. Sasha B. Ebrahimi & Devleena Samanta, 2023. "Engineering protein-based therapeutics through structural and chemical design," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    2. Lucien F. Krapp & Fernando A. Meireles & Luciano A. Abriata & Jean Devillard & Sarah Vacle & Maria J. Marcaida & Matteo Dal Peraro, 2024. "Context-aware geometric deep learning for protein sequence design," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    3. Fabian Sesterhenn & Che Yang & Jaume Bonet & Johannes T. Cramer & Xiaolin Wen & Yimeng Wang & Chi I. Chiang & Luciano Andres Abriata & Iga Kucharska & Giacomo Castoro & Sabrina S. Vollers & Marie Gall, 2020. "De novo protein design enables the precise induction of RSV-neutralizing antibodies," Post-Print hal-02677103, HAL.
    4. Betz, Ulrich A.K. & Arora, Loukik & Assal, Reem A. & Azevedo, Hatylas & Baldwin, Jeremy & Becker, Michael S. & Bostock, Stefan & Cheng, Vinton & Egle, Tobias & Ferrari, Nicola & Schneider-Futschik, El, 2023. "Game changers in science and technology - now and beyond," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    5. Edin Muratspahić & Kristine Deibler & Jianming Han & Nataša Tomašević & Kirtikumar B. Jadhav & Aina-Leonor Olivé-Marti & Nadine Hochrainer & Roland Hellinger & Johannes Koehbach & Jonathan F. Fay & Mo, 2023. "Design and structural validation of peptide–drug conjugate ligands of the kappa-opioid receptor," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    6. Zengping Duan & Chuilian Kong & Shihui Fan & Chuanliu Wu, 2024. "Triscysteine disulfide-directing motifs enabling design and discovery of multicyclic peptide binders," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    7. Nathaniel R. Bennett & Brian Coventry & Inna Goreshnik & Buwei Huang & Aza Allen & Dionne Vafeados & Ying Po Peng & Justas Dauparas & Minkyung Baek & Lance Stewart & Frank DiMaio & Steven Munck & Savv, 2023. "Improving de novo protein binder design with deep learning," Nature Communications, Nature, vol. 14(1), pages 1-9, December.

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