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ABSTRACT A tetrameric coiled‐coil peptide,TetNL, is used herein as a building block for hierarchical assembly into higher order structures. Assembly within phosphate buffer (pH 7.4) led to the rapid formation of micron‐sized fibers and cuboid structures, a process that could be shifted toward cuboid formation with agitation during the assembly process. Investigation of the packing of the cuboid assemblies by TEM demonstrated a regular banding pattern (4.6 nm) within the structures that was perpendicular to the length of the cuboids, a value that supports an end‐to end organization of the tetrameric coiled coils along the blocks. SWAXS analysis supports that the internal packing of the tetrameric coiled coil building blocks is a close‐packed hexagonal structure. These data represent an interesting comparison with a trimeric coiled coil peptide,TriNL, that forms hollow nanotubes with the same internal hexagonal packing. ModifiedTriNLhas been used to generate numerous unique morphologies, and the data presented herein provide a distinct tetrameric building block that can also be exploited in this manner.
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Bond-centric modular design of protein assemblies
Abstract Directional interactions that generate regular coordination geometries are a powerful means of guiding molecular and colloidal self-assembly, but implementing such high-level interactions with proteins remains challenging due to their complex shapes and intricate interface properties. Here we describe a modular approach to protein nanomaterial design inspired by the rich chemical diversity that can be generated from the small number of atomic valencies. We design protein building blocks using deep learning-based generative tools, incorporating regular coordination geometries and tailorable bonding interactions that enable the assembly of diverse closed and open architectures guided by simple geometric principles. Experimental characterization confirms the successful formation of more than 20 multicomponent polyhedral protein cages, two-dimensional arrays and three-dimensional protein lattices, with a high (10%–50%) success rate and electron microscopy data closely matching the corresponding design models. Due to modularity, individual building blocks can assemble with different partners to generate distinct regular assemblies, resulting in an economy of parts and enabling the construction of reconfigurable networks for designer nanomaterials.
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- Award ID(s):
- 2308979
- PAR ID:
- 10662836
- Publisher / Repository:
- NATURE PORTFOLIO
- Date Published:
- Journal Name:
- Nature Materials
- Volume:
- 24
- Issue:
- 10
- ISSN:
- 1476-1122
- Page Range / eLocation ID:
- 1644 to 1652
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1038/s41563-025-02297-5
