Computational design of genetically encoded self‐assembling proteins

@article{pmid26174163,

title = {Structure of a designed tetrahedral protein assembly variant engineered to have improved soluble expression},

author = {Jacob B Bale and Rachel U Park and Yuxi Liu and Shane Gonen and Tamir Gonen and Duilio Cascio and Neil P King and Todd O Yeates and David Baker},

url = {https://cryoem.ucla.edu/wp-content/uploads/2015_bale.pdf, Main text},

doi = {10.1002/pro.2748},

year  = {2015},

date = {2015-07-15},

journal = {Protein Sci.},

volume = {24},

number = {10},

pages = {1695--1701},

abstract = {We recently reported the development of a computational method for the design of coassembling multicomponent protein nanomaterials. While four such materials were validated at high-resolution by X-ray crystallography, low yield of soluble protein prevented X-ray structure determination of a fifth designed material, T33-09. Here we report the design and crystal structure of T33-31, a variant of T33-09 with improved soluble yield resulting from redesign efforts focused on mutating solvent-exposed side chains to charged amino acids. The structure is found to match the computational design model with atomic-level accuracy, providing further validation of the design approach and demonstrating a simple and potentially general means of improving the yield of designed protein nanomaterials.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid26089516,

title = {Design of ordered two-dimensional arrays mediated by noncovalent protein-protein interfaces},

author = {Shane Gonen and Frank DiMaio and Tamir Gonen and David Baker},

url = {https://cryoem.ucla.edu/wp-content/uploads/2015_gonen.pdf, Main text},

doi = {10.1126/science.aaa9897},

year  = {2015},

date = {2015-06-19},

journal = {Science},

volume = {348},

number = {6241},

pages = {1365--1368},

abstract = {We describe a general approach to designing two-dimensional (2D) protein arrays mediated by noncovalent protein-protein interfaces. Protein homo-oligomers are placed into one of the seventeen 2D layer groups, the degrees of freedom of the lattice are sampled to identify configurations with shape-complementary interacting surfaces, and the interaction energy is minimized using sequence design calculations. We used the method to design proteins that self-assemble into layer groups P 3 2 1, P 4 2(1) 2, and P 6. Projection maps of micrometer-scale arrays, assembled both in vitro and in vivo, are consistent with the design models and display the target layer group symmetry. Such programmable 2D protein lattices should enable new approaches to structure determination, sensing, and nanomaterial engineering.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid24870237,

title = {Accurate design of co-assembling multi-component protein nanomaterials},

author = {Neil P King and Jacob B Bale and William Sheffler and Dan E McNamara and Shane Gonen and Tamir Gonen and Todd O Yeates and David Baker},

url = {https://cryoem.ucla.edu/wp-content/uploads/2014_king.pdf, Main text},

doi = {10.1038/nature13404},

year  = {2014},

date = {2014-06-05},

journal = {Nature},

volume = {510},

number = {7503},

pages = {103--108},

abstract = {The self-assembly of proteins into highly ordered nanoscale architectures is a hallmark of biological systems. The sophisticated functions of these molecular machines have inspired the development of methods to engineer self-assembling protein nanostructures; however, the design of multi-component protein nanomaterials with high accuracy remains an outstanding challenge. Here we report a computational method for designing protein nanomaterials in which multiple copies of two distinct subunits co-assemble into a specific architecture. We use the method to design five 24-subunit cage-like protein nanomaterials in two distinct symmetric architectures and experimentally demonstrate that their structures are in close agreement with the computational design models. The accuracy of the method and the number and variety of two-component materials that it makes accessible suggest a route to the construction of functional protein nanomaterials tailored to specific applications.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid22654060,

title = {Computational Design of Self-Assembling Protein Nanomaterials with Atomic Level Accuracy},

author = {Neil P King and William Sheffler and Michael R Sawaya and Breanna S Vollmar and John P Sumida and Ingemar André and Tamir Gonen and Todd O Yeates and David Baker},

url = {https://cryoem.ucla.edu/wp-content/uploads/2012_king.pdf, Main text},

doi = {10.1126/science.1219364},

year  = {2012},

date = {2012-06-01},

journal = {Science},

volume = {336},

number = {6085},

pages = {1171--1174},

abstract = {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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}