Design of multi-scale protein complexes by hierarchical building block fusion

Yang Hsia, Rubul Mout, William Sheffler, Natasha I. Edman, Ivan Vulovic, Young-Jun Park, Rachel L. Redler, Matthew J. Bick, Asim K. Bera, Alexis Courbet, Alex Kang, T. J. Brunette, Una Nattermann, Evelyn Tsai, Ayesha Saleem, Cameron M. Chow, Damian Ekiert, Gira Bhabha, David Veesler and David Baker ()
Additional contact information
Yang Hsia: University of Washington
Rubul Mout: University of Washington
William Sheffler: University of Washington
Natasha I. Edman: University of Washington
Ivan Vulovic: University of Washington
Young-Jun Park: University of Washington
Rachel L. Redler: New York University School of Medicine
Matthew J. Bick: University of Washington
Asim K. Bera: University of Washington
Alexis Courbet: University of Washington
Alex Kang: University of Washington
T. J. Brunette: University of Washington
Una Nattermann: University of Washington
Evelyn Tsai: University of Washington
Ayesha Saleem: University of Washington
Cameron M. Chow: University of Washington
Damian Ekiert: New York University School of Medicine
Gira Bhabha: New York University School of Medicine
David Veesler: University of Washington
David Baker: University of Washington

Nature Communications, 2021, vol. 12, issue 1, 1-10

Abstract: Abstract A systematic and robust approach to generating complex protein nanomaterials would have broad utility. We develop a hierarchical approach to designing multi-component protein assemblies from two classes of modular building blocks: designed helical repeat proteins (DHRs) and helical bundle oligomers (HBs). We first rigidly fuse DHRs to HBs to generate a large library of oligomeric building blocks. We then generate assemblies with cyclic, dihedral, and point group symmetries from these building blocks using architecture guided rigid helical fusion with new software named WORMS. X-ray crystallography and cryo-electron microscopy characterization show that the hierarchical design approach can accurately generate a wide range of assemblies, including a 43 nm diameter icosahedral nanocage. The computational methods and building block sets described here provide a very general route to de novo designed protein nanomaterials.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-22276-z

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DOI: 10.1038/s41467-021-22276-z

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