For a billion years, proteins have evolved in nature as nanoscale building blocks with precisely controlled shapes and properties to carry out complex functions in living systems. Beyond their essential biological roles in nature, protein offers exceptional programmability in terms of length, conformation, and intermolecular interactions, making them ideal for creating nanoscale materials as well as biological tools. An abundant type of protein motifs that mediate highly controlled, specific protein-protein interactions includes coiled-coils protein motifs. These motifs form oligomers that mediate the assembly of diverse molecular complexes in nature. Their well-characterized sequence-to-structure relationships have enabled the de novo design of synthetic coiled-coil sequences with controllable binding affinity, specificity, orientation, and oligomeric states. Orthogonally interacting coiled-coil motifs can be modularly arranged to assemble well-defined protein nanostructures composed of interconnected coiled-coil helices, which is termed coiled-coil protein origami (CCPO). It is based on the modular recombination of coiled-coil motifs into fusion proteins that are folded and assembled into nanostructures through specific and orthogonal intra- or inter-strand oligomerization of the coiled-coil modules. In this study, we demonstrate a CCPO approach for designing protein nano-assemblies and predicting their structures at atomistic resolution using controlled molecular dynamics optimization. We further explored the application of CCPO nanostructures for nanoscale patterning and surface functionalization. In particular, we designed amphiphilic protein nano-bundles that form thin films with defined nanoscale topologies and functional properties, such as antifouling and antimicrobial activity. Lastly, we introduced a machine learning-based computational method to design highly specific and orthogonal helical protein modules, which can extend the scope and potential application of CCPO protein assemblies in nanomanufacturing and synthetic biology.
