Abstract

Naturally occurring, pharmacologically active peptides constrained with covalent crosslinks generally have shapes that have evolved to fit precisely into binding pockets on their targets. Such peptides can have excellent pharmaceutical properties, combining the stability and tissue penetration of small-molecule drugs with the specificity of much larger protein therapeutics. The ability to design constrained peptides with precisely specified tertiary structures would enable the design of shape-complementary inhibitors of arbitrary targets. Here we describe the development of computational methods for accurate de novo design of conformationally restricted peptides, and the use of these methods to design 18–47 residue, disulfide-crosslinked peptides, a subset of which are heterochiral and/or N–C backbone-cyclized. Both genetically encodable and non-canonical peptides are exceptionally stable to thermal and chemical denaturation, and 12 experimentally determined X-ray and NMR structures are nearly identical to the computational design models. The computational design methods and stable scaffolds presented here provide the basis for development of a new generation of peptide-based drugs.

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Acknowledgements

Computer time was awarded by the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program. This research used resources of the Argonne Leadership Computing Facility, a Department of Energy (DOE) Office of Science User Facility supported under contract DE-AC02-06CH11357. We thank the University of Washington Hyak supercomputing network for computing and data storage resources, and Rosetta@Home volunteer participants on BOINC for additional computing resources. We are grateful for facility access at the Queensland NMR Network. We thank D. Alonso, J. Bardwell, G. Bhabha, T.J. Brunette, D. Ekiert, A. Ford, N. Hasle, B. Keir, N. Koga, Y. Liu, D. Madden, B. Mao, D. May, V. Ovchinnikov, S. Srivatsan, L. Stewart, R. van Deursen, and M. Williamson for help and advice, and R. Krishnamurty, P. Hosseinzadeh, and A. Vorobieva for critical comments and manuscript suggestions. This work was supported by NIH grant P50 AG005136 supporting the Alzheimer’s Disease Research Center, philanthropic gifts from the Three Dreamers and Washington Research Foundation, and funding from the Howard Hughes Medical Institute. The Australian Research Council funds D.J.C. as an Australian Laureate Fellow (FL150100146). C.D.B. was supported by NIH grant T32-H600035. T.S. acknowledges NIH support (GM094597), and S.V.S.R.K.P., A.E. and X.X. were supported with NESG funds. E.C. is funded by NIGMS GM090205. We thank P. Rupert and R.K. Strong at the Fred Hutchinson Cancer Research Center for aid in collecting and refining X-ray data for gEHEE_06. G.W.B. was funded by the National Institute of Allergy and Infectious Diseases, National Institute of Health, Department of Health and Human Services (Federal contract HHSN272201200025C). A portion of this research was performed using EMSL, a DOE Office of Science User Facility sponsored by the Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory.

Author information

Author notes

    • Gaurav Bhardwaj
    • , Vikram Khipple Mulligan
    •  & Christopher D. Bahl

    These authors contributed equally to this work.

Affiliations

  1. Department of Biochemistry, University of Washington, Seattle, Washington 98195, USA

    • Gaurav Bhardwaj
    • , Vikram Khipple Mulligan
    • , Christopher D. Bahl
    • , Jason M. Gilmore
    • , Po-Ssu Huang
    • , Per Jr Greisen
    • , Gabriel J. Rocklin
    • , Yifan Song
    • , Thomas W. Linsky
    •  & David Baker
  2. Institute for Protein Design, University of Washington, Seattle, Washington 98195, USA

    • Gaurav Bhardwaj
    • , Vikram Khipple Mulligan
    • , Christopher D. Bahl
    • , Jason M. Gilmore
    • , Po-Ssu Huang
    • , Per Jr Greisen
    • , Gabriel J. Rocklin
    • , Yifan Song
    • , Thomas W. Linsky
    • , Stephen A. Rettie
    • , Lauren P. Carter
    •  & David Baker
  3. Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia

    • Peta J. Harvey
    • , Olivier Cheneval
    • , Quentin Kaas
    •  & David J. Craik
  4. Seattle Structural Genomics Center for Infectious Diseases, Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA

    • Garry W. Buchko
  5. Department of Chemistry, State University of New York at Buffalo, Buffalo, New York 14260, USA

    • Surya V. S. R. K. Pulavarti
    • , Alexander Eletsky
    • , Xianzhong Xu
    •  & Thomas Szyperski
  6. Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA

    • William A. Johnsen
    • , James M. Olson
    •  & Colin E. Correnti
  7. Global Research, Novo Nordisk A/S, DK-2760 Måløv, Denmark

    • Per Jr Greisen
  8. Cyrus Biotechnology, Seattle, Washington 98109, USA

    • Yifan Song
  9. Department of Chemistry, New York University, New York, New York 10003, USA

    • Andrew Watkins
  10. Department of Biology, New York University, New York, New York 10003, USA

    • Richard Bonneau
  11. Center for Computational Biology, Simons Foundation, New York, New York 10010, USA

    • Richard Bonneau
  12. Applied Mathematics and Statistics and Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794, USA

    • Evangelos Coutsias
  13. Howard Hughes Medical Institute, University of Washington, Seattle, Washington 98195, USA

    • David Baker

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Contributions

C.D.B., G.B., V.K.M. and D.B. designed the study. V.K.M. developed algorithms with help from A.W., E.C., Y.S., G.B., R.B., C.D.B., G.J.R. and T.W.L. C.D.B. and J.M.G. designed canonical peptides with help from D.B., G.J.R. and T.W.L. G.B. designed heterochiral and backbone-cyclized peptides with help from V.K.M., D.B., P.G. and P.S.H. C.D.B. expressed and characterized designed canonical peptides from E. coli with help from J.M.G. and S.A.R. J.M.G. performed MS analysis. W.A.G. and C.E.C. purified canonical peptides via Daedalus and determined X-ray crystal structures. G.W.B., S.V.S.R.K.P., A.E. and T.S. determined NMR solution structures of canonical peptides, purified with isotopic labelling by C.D.B. O.C. and G.B. synthesized, purified and characterized designed non-canonical peptides. P.J.H. and D.J.C. determined NMR solution structures of non-canonical peptides. P.J.H., Q.K. and D.J.C. analysed data from structure determination of non-canonical peptides. C.D.B., G.B., V.K.M. and D.B. wrote the manuscript with help from all authors.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to David Baker.

Reviewer Information Nature thanks V. Nanda and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Extended data

Supplementary information

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  1. 1.

    Supplementary Information

    This file contains Supplementary Sections 1-4. Section 1 contains a detailed description of the computational methods development and example protocols for running the computational methods. Section 2 contains NMR spectra and structure determination statistics. Section 3 contains data from experimental screening of designs. Section 4 contains detailed experimental characterization and validation of reported designs. Collectively, this supplementary information contains details enabling the critical assessment and reproduction of the computational and experimental results described in the main text.

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  1. 1.

    Supplementary Data

    This tar archive contains the PDB output files from Rosetta for all designed peptides reported in the main text.

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DOI

https://doi.org/10.1038/nature19791

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