Computational design of self-assembling protein nanomaterials with atomic level accuracy

By Neil P. King, W. Sheffler, M. Sawaya, B. Vollmar, J. Sumida, Ingemar André, Tamir Gonen, Todd O. Yeates, David Baker. 2012

628 citations recorded by the source corpus.

Design and Build Self-assembling biomolecules are attractive building blocks in the development of functional materials. Sophisticated DNA-based materials have been developed; however, progress in designing protein-based materials has been slower. King et al. (p. 1171) describe a general computational method in which protein building blocks are first symmetrically docked onto a target architecture, and then binding interfaces that drive self-assembly of the building blocks are designed. As a proof of principle, trimeric building blocks were used to design self-assembling 12-subunit complexes with tetrahedral symmetry and 24-subunit complexes with octahedral symmetry. Lai et al. (p. 1129) were able to build a 12-subunit tetrahedral protein cage from fused oligomeric protein domains. A general computational method is used to design protein building blocks that self-assemble into target architectures. We describe a general computational method for designing proteins that self-assemble to a desired symmetric architecture. Protein building blocks are docked together symmetrically to identify complementary packing arrangements, and low-energy protein-protein interfaces are then designed between the building blocks in order to drive self-assembly. We used trimeric protein building blocks to design a 24-subunit, 13-nm diameter complex with octahedral symmetry and a 12-subunit, 11-nm diameter complex with tetrahedral symmetry. The designed proteins assembled to the desired oligomeric states in solution, and the crystal structures of the complexes revealed that the resulting materials closely match the design models. The method can be used to design a wide variety of self-assembling protein nanomaterials.

Subfields: Ecology, Molecular Biology, Computational Chemistry & Drug Discovery

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Citations in the corpus

Elicitation of Potent Neutralizing Antibody Responses by Designed Protein Nanoparticle Vaccines for SARS-CoV-2 (2020, positive): “A new development in this area has been the emergence of computationally designed protein nanoparticles as a robust and versatile platform for multivalent antigen presentation (Bale et al., 2016; Hsia et al., 2016; King et al., 2012; Ueda et al., 2020).”
High resolution comparative modeling with RosettaCM (2013, background): “…realistic all atom energy function to achieve atomic accuracy in many challenging structural biology problems, including structure determination with sparse experimental data and the design of new protein structures and interfaces(Fleishman et al., 2011; King et al., 2012; Raman et al., 2010).”
Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem (2022, neutral): “The motif-scaffolding problem has applications ranging from medicine to material science (King et al., 2012), but remains unsolved for many functional motifs.”
Computational design of a protein-based enzyme inhibitor. (2013, positive): “Most successful interface designs have placed critical side chains on rigid secondary structural elements [6,11,33], and a connectivity metric for assessing how well the binding residues are “connected” to the protein core fared favorably in a communitywide challenge to discriminate verified designe”
De novo protein design, a retrospective (2020, methodology): “This method has been used to create novel cages with varying symmetries including icosahedral assemblies (King et al., 2012; Bale et al., 2016; Hsia et al., 2016).”
Design of a hyperstable 60-subunit protein icosahedron (2016, positive): “…coupled with computational protein-protein interface design has accurately generated protein assemblies with tetrahedral and octahedral symmetry 18,19 , but these relatively small ( 16 nm diameter) nanocages have limited use for packaging or delivery applications as they have little internal…”
Using AlphaFold for Rapid and Accurate Fixed Backbone Protein Design (2021, background): “, 2017), nanomaterials (King et al., 2012), and enzymology (Studer et al.”
The coming of age of de novo protein design (2016, background): “78 and J. Fallas and G. Ueda, personal communication), tetrahedra 79,80 , octahedra 79 and open two-dimensional assemblies 81 (Fig.”