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

Alex Kang,Gira Bhabha,William Sheffler,Evelyn Tsai,Matthew J Bick,Damian Ekiert,Asim K Bera,David Baker,Una Nattermann,David Veesler,Rachel Redler ,Tj Brunette ,Rubul Mout,Alexis Courbet,Natasha I Edman,Yang Hsia,Young-Jun Park,Cameron M Chow,Ayesha Saleem,Ivan Vulovic

doi:10.1038/s41467-021-22276-z

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.

Highlights

A systematic and robust approach to generating complex protein nanomaterials would have broad utility
Attractive candidates for such an approach are de novo helical repeat proteins (DHRs)[17] consisting of a tandemly repeated structural unit, which provide a wide range of struts of different shape and curvature for building nanomaterials, and parametric helical bundles (HBs)[18,19,20,21] which provide a wide range of preformed protein–protein interfaces for locking together different protein subunits in a designed nanomaterial
We describe the development of methods for creating large and modular libraries of building blocks by fusing designed helical repeat proteins (DHRs) to helical bundle oligomers (HBs), and using them to generate symmetric assemblies by rapidly scanning through the combinatorially large number of possible rigid helix fusions for those generating the desired architecture

Summary

Introduction

A systematic and robust approach to generating complex protein nanomaterials would have broad utility. A potential solution to the issue of having smaller numbers of possible fusion positions for a given pair of building blocks in the rigid helix fusion method is to systematically generate large numbers of building blocks having properties ideal for helix fusion Attractive candidates for such an approach are de novo helical repeat proteins (DHRs)[17] consisting of a tandemly repeated structural unit, which provide a wide range of struts of different shape and curvature for building nanomaterials, and parametric helical bundles (HBs)[18,19,20,21] which provide a wide range of preformed protein–protein interfaces for locking together different protein subunits in a designed nanomaterial. We describe the use of geometric hashing of transforms to quickly and systematically identify the fusion positions in large sets of building blocks that generate any specified symmetric architecture, and the use of this approach to design a broad range of symmetric assemblies

Methods

Results

Conclusion