@article{Yang2024,

title = {Computational design of non-porous pH-responsive antibody nanoparticles},

author = {Erin C. Yang and Robby Divine and Marcos C. Miranda and Andrew J. Borst and Will Sheffler and Jason Z. Zhang and Justin Decarreau and Amijai Saragovi and Mohamad Abedi and Nicolas Goldbach and Maggie Ahlrichs and Craig Dobbins and Alexis Hand and Suna Cheng and Mila Lamb and Paul M. Levine and Sidney Chan and Rebecca Skotheim and Jorge Fallas and George Ueda and Joshua Lubner and Masaharu Somiya and Alena Khmelinskaia and Neil P. King and David Baker},

url = {https://www.nature.com/articles/s41594-024-01288-5, NSMB [Open Access]

https://www.bakerlab.org/wp-content/uploads/2024/05/Yang-etal-NSMB2024-s41594-024-01288-5.pdf, PDF},

doi = {10.1038/s41594-024-01288-5},

year  = {2024},

date = {2024-05-09},

urldate = {2024-05-09},

journal = {Nature Structural & Molecular Biololgy},

publisher = {Springer Science and Business Media LLC},

abstract = {Programming protein nanomaterials to respond to changes in environmental conditions is a current challenge for protein design and is important for targeted delivery of biologics. Here we describe the design of octahedral non-porous nanoparticles with a targeting antibody on the two-fold symmetry axis, a designed trimer programmed to disassemble below a tunable pH transition point on the three-fold axis, and a designed tetramer on the four-fold symmetry axis. Designed non-covalent interfaces guide cooperative nanoparticle assembly from independently purified components, and a cryo-EM density map closely matches the computational design model. The designed nanoparticles can package protein and nucleic acid payloads, are endocytosed following antibody-mediated targeting of cell surface receptors, and undergo tunable pH-dependent disassembly at pH values ranging between 5.9 and 6.7. The ability to incorporate almost any antibody into a non-porous pH-dependent nanoparticle opens up new routes to antibody-directed targeted delivery.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Shen2024,

title = {De novo design of pH-responsive self-assembling helical protein filaments},

author = {Hao Shen and Eric M. Lynch and Susrut Akkineni and Joseph L. Watson and Justin Decarreau and Neville P. Bethel and Issa Benna and William Sheffler and Daniel Farrell and Frank DiMaio and Emmanuel Derivery and James J. De Yoreo and Justin Kollman and David Baker},

url = {https://link.springer.com/article/10.1038/s41565-024-01641-1, Nature Nanotechnology [Open Access]

https://www.bakerlab.org/wp-content/uploads/2024/04/s41565-024-01641-1.pdf, PDF},

doi = {10.1038/s41565-024-01641-1},

year  = {2024},

date = {2024-04-03},

urldate = {2024-04-03},

journal = {Nature Nanotechnology},

publisher = {Springer Science and Business Media LLC},

abstract = {Biological evolution has led to precise and dynamic nanostructures that reconfigure in response to pH and other environmental conditions. However, designing micrometre-scale protein nanostructures that are environmentally responsive remains a challenge. Here we describe the de novo design of pH-responsive protein filaments built from subunits containing six or nine buried histidine residues that assemble into micrometre-scale, well-ordered fibres at neutral pH. The cryogenic electron microscopy structure of an optimized design is nearly identical to the computational design model for both the subunit internal geometry and the subunit packing into the fibre. Electron, fluorescent and atomic force microscopy characterization reveal a sharp and reversible transition from assembled to disassembled fibres over 0.3 pH units, and rapid fibre disassembly in less than 1 s following a drop in pH. The midpoint of the transition can be tuned by modulating buried histidine-containing hydrogen bond networks. Computational protein design thus provides a route to creating unbound nanomaterials that rapidly respond to small pH changes.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Huddy2024,

title = {Blueprinting extendable nanomaterials with standardized protein blocks},

author = {Timothy F. Huddy and Yang Hsia and Ryan D. Kibler and Jinwei Xu and Neville Bethel and Deepesh Nagarajan and Rachel Redler and Philip J. Y. Leung and Connor Weidle and Alexis Courbet and Erin C. Yang and Asim K. Bera and Nicolas Coudray and S. John Calise and Fatima A. Davila-Hernandez and Hannah L. Han and Kenneth D. Carr and Zhe Li and Ryan McHugh and Gabriella Reggiano and Alex Kang and Banumathi Sankaran and Miles S. Dickinson and Brian Coventry and T. J. Brunette and Yulai Liu and Justas Dauparas and Andrew J. Borst and Damian Ekiert and Justin M. Kollman and Gira Bhabha and David Baker},

url = {https://www.nature.com/articles/s41586-024-07188-4, Nature [Open Access]},

doi = {10.1038/s41586-024-07188-4},

year  = {2024},

date = {2024-03-13},

urldate = {2024-03-13},

journal = {Nature},

publisher = {Springer Science and Business Media LLC},

abstract = {A wooden house frame consists of many different lumber pieces, but because of the regularity of these building blocks, the structure can be designed using straightforward geometrical principles. The design of multicomponent protein assemblies, in comparison, has been much more complex, largely owing to the irregular shapes of protein structures. Here we describe extendable linear, curved and angled protein building blocks, as well as inter-block interactions, that conform to specified geometric standards; assemblies designed using these blocks inherit their extendability and regular interaction surfaces, enabling them to be expanded or contracted by varying the number of modules, and reinforced with secondary struts. Using X-ray crystallography and electron microscopy, we validate nanomaterial designs ranging from simple polygonal and circular oligomers that can be concentrically nested, up to large polyhedral nanocages and unbounded straight ‘train track’ assemblies with reconfigurable sizes and geometries that can be readily blueprinted. Because of the complexity of protein structures and sequence–structure relationships, it has not previously been possible to build up large protein assemblies by deliberate placement of protein backbones onto a blank three-dimensional canvas; the simplicity and geometric regularity of our design platform now enables construction of protein nanomaterials according to ‘back of an envelope’ architectural blueprints.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Mout2024,

title = {De novo design of modular protein hydrogels with programmable intra- and extracellular viscoelasticity},

author = {Rubul Mout, Ross C. Bretherton, Justin Decarreau, Sangmin Lee, Nicole Gregorio, Natasha I. Edman, Maggie Ahlrichs, Yang Hsia, Danny D. Sahtoe, George Ueda, Alee Sharma, Rebecca Schulman, Cole A. DeForest, David Baker},

url = {https://www.pnas.org/doi/full/10.1073/pnas.2309457121, PNAS [Open Access]},

doi = {10.1073/pnas.2309457121},

year  = {2024},

date = {2024-01-30},

urldate = {2024-01-30},

journal = {Proceedings of the National Academy of Sciences},

abstract = {Relating the macroscopic properties of protein-based materials to their underlying component microstructure is an outstanding challenge. Here, we exploit computational design to specify the size, flexibility, and valency of de novo protein building blocks, as well as the interaction dynamics between them, to investigate how molecular parameters govern the macroscopic viscoelasticity of the resultant protein hydrogels. We construct gel systems from pairs of symmetric protein homo-oligomers, each comprising 2, 5, 24, or 120 individual protein components, that are crosslinked either physically or covalently into idealized step-growth biopolymer networks. Through rheological assessment, we find that the covalent linkage of multifunctional precursors yields hydrogels whose viscoelasticity depends on the crosslink length between the constituent building blocks. In contrast, reversibly crosslinking the homo-oligomeric components with a computationally designed heterodimer results in viscoelastic biomaterials exhibiting fluid-like properties under rest and low shear, but solid-like behavior at higher frequencies. Exploiting the unique genetic encodability of these materials, we demonstrate the assembly of protein networks within living mammalian cells and show via fluorescence recovery after photobleaching (FRAP) that mechanical properties can be tuned intracellularly in a manner similar to formulations formed extracellularly. We anticipate that the ability to modularly construct and systematically program the viscoelastic properties of designer protein-based materials could have broad utility in biomedicine, with applications in tissue engineering, therapeutic delivery, and synthetic biology.

},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Davila-Hernandez2023,

title = {Directing polymorph specific calcium carbonate formation with de novo protein templates},

author = {Fatima A Davila-Hernandez and Biao Jin and Harley Pyles and Shuai Zhang and Zheming Wang and Timothy F Huddy and Asim K Bera and Alex Kang and Chun-Long Chen and James J De Yoreo and David Baker},

url = {https://www.nature.com/articles/s41467-023-43608-1, Nature Communications (Open Access)},

doi = {10.1038/s41467-023-43608-1},

issn = {2041-1723},

year  = {2023},

date = {2023-12-01},

urldate = {2023-12-01},

journal = {Nature Communications},

volume = {14},

number = {1},

pages = {8191},

abstract = {Biomolecules modulate inorganic crystallization to generate hierarchically structured biominerals, but the atomic structure of the organic-inorganic interfaces that regulate mineralization remain largely unknown. We hypothesized that heterogeneous nucleation of calcium carbonate could be achieved by a structured flat molecular template that pre-organizes calcium ions on its surface. To test this hypothesis, we design helical repeat proteins (DHRs) displaying regularly spaced carboxylate arrays on their surfaces and find that both protein monomers and protein-Ca supramolecular assemblies directly nucleate nano-calcite with non-natural {110} or {202} faces while vaterite, which forms first in the absence of the proteins, is bypassed. These protein-stabilized nanocrystals then assemble by oriented attachment into calcite mesocrystals. We find further that nanocrystal size and polymorph can be tuned by varying the length and surface chemistry of the designed protein templates. Thus, bio-mineralization can be programmed using de novo protein design, providing a route to next-generation hybrid materials.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Li2023,

title = {Accurate computational design of three-dimensional protein  crystals},

author = {Zhe Li and Shunzhi Wang and Una Nattermann and Asim K Bera and Andrew J Borst and Muammer Y Yaman and Matthew J Bick and Erin C Yang and William Sheffler and Byeongdu Lee and Soenke Seifert and Greg L Hura and Hannah Nguyen and Alex Kang and Radhika Dalal and Joshua M Lubner and Yang Hsia and Hugh Haddox and Alexis Courbet and Quinton Dowling and Marcos Miranda and Andrew Favor and Ali Etemadi and Natasha I Edman and Wei Yang and Connor Weidle and Banumathi Sankaran and Babak Negahdari and Michael B Ross and David S Ginger and David Baker},

url = {https://rdcu.be/doHL5, Nature Methods},

doi = {10.1038/s41563-023-01683-1},

year  = {2023},

date = {2023-10-16},

urldate = {2023-10-01},

journal = {Nature Materials},

abstract = {Protein crystallization plays a central role in structural biology. Despite this, the process of crystallization remains poorly understood and highly empirical, with crystal contacts, lattice packing arrangements and space group preferences being largely unpredictable. Programming protein crystallization through precisely engineered side-chain–side-chain interactions across protein–protein interfaces is an outstanding challenge. Here we develop a general computational approach for designing three-dimensional protein crystals with prespecified lattice architectures at atomic accuracy that hierarchically constrains the overall number of degrees of freedom of the system. We design three pairs of oligomers that can be individually purified, and upon mixing, spontaneously self-assemble into >100 µm three-dimensional crystals. The structures of these crystals are nearly identical to the computational design models, closely corresponding in both overall architecture and the specific protein–protein interactions. The dimensions of the crystal unit cell can be systematically redesigned while retaining the space group symmetry and overall architecture, and the crystals are extremely porous and highly stable. Our approach enables the computational design of protein crystals with high accuracy, and the designed protein crystals, which have both structural and assembly information encoded in their primary sequences, provide a powerful platform for biological materials engineering.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Bethel2023,

title = {Precisely patterned nanofibres made from extendable protein multiplexes},

author = {Neville P. Bethel and Andrew J. Borst and Fabio Parmeggiani and Matthew J. Bick and TJ Brunette and Hannah Nguyen and Alex Kang and Asim K. Bera and Lauren Carter and Marcos C. Miranda and Ryan D. Kibler and Mila Lamb and Xinting Li and Banumathi Sankaran and David Baker},

url = {https://rdcu.be/dloEi, Nature Chemistry [Open Access]},

doi = {10.1038/s41557-023-01314-x},

year  = {2023},

date = {2023-09-04},

urldate = {2023-09-04},

journal = {Nature Chemistry},

publisher = {Springer Science and Business Media LLC},

abstract = {Molecular systems with coincident cyclic and superhelical symmetry axes have considerable advantages for materials design as they can be readily lengthened or shortened by changing the length of the constituent monomers. Among proteins, alpha-helical coiled coils have such symmetric, extendable architectures, but are limited by the relatively fixed geometry and flexibility of the helical protomers. Here we describe a systematic approach to generating modular and rigid repeat protein oligomers with coincident C2 to C8 and superhelical symmetry axes that can be readily extended by repeat propagation. From these building blocks, we demonstrate that a wide range of unbounded fibres can be systematically designed by introducing hydrophilic surface patches that force staggering of the monomers; the geometry of such fibres can be precisely tuned by varying the number of repeat units in the monomer and the placement of the hydrophilic patches.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Lutz2023,

title = {Top-down design of protein architectures with reinforcement learning},

author = {Lutz, Isaac D.

and Wang, Shunzhi

and Norn, Christoffer

and Courbet, Alexis

and Borst, Andrew J.

and Zhao, Yan Ting

and Dosey, Annie

and Cao, Longxing

and Xu, Jinwei

and Leaf, Elizabeth M.

and Treichel, Catherine

and Litvicov, Patrisia

and Li, Zhe

and Goodson, Alexander D.

and Rivera-Sánchez, Paula

and Bratovianu, Ana-Maria

and Baek, Minkyung

and King, Neil P.

and Ruohola-Baker, Hannele

and Baker, David},

url = {https://www.science.org/doi/10.1126/science.adf6591, Science

https://www.ipd.uw.edu/wp-content/uploads/2023/04/science.adf6591.pdf, PDF},

doi = {10.1126/science.adf6591},

year  = {2023},

date = {2023-04-20},

journal = {Science},

abstract = {As a result of evolutionary selection, the subunits of naturally occurring protein assemblies often fit together with substantial shape complementarity to generate architectures optimal for function in a manner not achievable by current design approaches. We describe a “top-down” reinforcement learning–based design approach that solves this problem using Monte Carlo tree search to sample protein conformers in the context of an overall architecture and specified functional constraints. Cryo–electron microscopy structures of the designed disk-shaped nanopores and ultracompact icosahedra are very close to the computational models. The icosohedra enable very-high-density display of immunogens and signaling molecules, which potentiates vaccine response and angiogenesis induction. Our approach enables the top-down design of complex protein nanomaterials with desired system properties and demonstrates the power of reinforcement learning in protein design.

},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Yang2023,

title = {Design of cell-type-specific hyperstable IL-4 mimetics via modular de novo scaffolds},

author = {Yang, Huilin

and Ulge, Umut Y.

and Quijano-Rubio, Alfredo

and Bernstein, Zachary J.

and Maestas, David R.

and Chun, Jung-Ho

and Wang, Wentao

and Lin, Jian-Xin

and Jude, Kevin M.

and Singh, Srujan

and Orcutt-Jahns, Brian T.

and Li, Peng

and Mou, Jody

and Chung, Liam

and Kuo, Yun-Huai

and Ali, Yasmin H.

and Meyer, Aaron S.

and Grayson, Warren L.

and Heller, Nicola M.

and Garcia, K. Christopher

and Leonard, Warren J.

and Silva, Daniel-Adriano

and Elisseeff, Jennifer H.

and Baker, David

and Spangler, Jamie B.},

url = {https://www.nature.com/articles/s41589-023-01313-6, Nature Chemical Biology

https://www.bakerlab.org/wp-content/uploads/2023/05/s41589-023-01313-6-1.pdf, PDF},

doi = {10.1038/s41589-023-01313-6},

year  = {2023},

date = {2023-04-06},

journal = {Nature Chemical Biology},

abstract = {The interleukin-4 (IL-4) cytokine plays a critical role in modulating immune homeostasis. Although there is great interest in harnessing this cytokine as a therapeutic in natural or engineered formats, the clinical potential of native IL-4 is limited by its instability and pleiotropic actions. Here, we design IL-4 cytokine mimetics (denoted Neo-4) based on a de novo engineered IL-2 mimetic scaffold and demonstrate that these cytokines can recapitulate physiological functions of IL-4 in cellular and animal models. In contrast with natural IL-4, Neo-4 is hyperstable and signals exclusively through the type I IL-4 receptor complex, providing previously inaccessible insights into differential IL-4 signaling through type I versus type II receptors. Because of their hyperstability, our computationally designed mimetics can directly incorporate into sophisticated biomaterials that require heat processing, such as three-dimensional-printed scaffolds. Neo-4 should be broadly useful for interrogating IL-4 biology, and the design workflow will inform targeted cytokine therapeutic development.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Said2022,

title = {Exploration of Structured Symmetric Cyclic Peptides as Ligands for Metal-Organic Frameworks},

author = {Said, Meerit Y. and Kang, Christine S. and Wang, Shunzhi and Sheffler, William and Salveson, Patrick J. and Bera, Asim K. and Kang, Alex and Nguyen, Hannah and Ballard, Ryanne and Li, Xinting and Bai, Hua and Stewart, Lance and Levine, Paul and Baker, David},

url = {https://pubs.acs.org/doi/10.1021/acs.chemmater.2c02597, Chem. Mater.

https://www.bakerlab.org/wp-content/uploads/2022/10/Said_etal_ChemMater2022_CyclicPeptideMOFs.pdf, PDF},

doi = {/10.1021/acs.chemmater.2c02597},

year  = {2022},

date = {2022-10-25},

urldate = {2022-10-25},

journal = {Chemistry of Materials},

abstract = {Despite remarkable advances in the assembly of highly structured coordination polymers and metal–organic frameworks, the rational design of such materials using more conformationally flexible organic ligands such as peptides remains challenging. In an effort to make the design of such materials fully programmable, we first developed a computational design method for generating metal-mediated 3D frameworks using rigid and symmetric peptide macrocycles with metal-coordinating sidechains. We solved the structures of six crystalline networks involving conformationally constrained 6 to 12 residue cyclic peptides with C2, C3, and S2 internal symmetry and three different types of metals (Zn2+, Co2+, or Cu2+) by single-crystal X-ray diffraction, which reveals how the peptide sequences, backbone symmetries, and metal coordination preferences drive the assembly of the resulting structures. In contrast to smaller ligands, these peptides associate through peptide–peptide interactions without full coordination of the metals, contrary to one of the assumptions underlying our computational design method. The cyclic peptides are the largest peptidic ligands reported to form crystalline coordination polymers with transition metals to date, and while more work is required to develop methods for fully programming their crystal structures, the combination of high chemical diversity with synthetic accessibility makes them attractive building blocks for engineering a broader set of new crystalline materials for use in applications such as sensing, asymmetric catalysis, and chiral separation.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Wicky2022,

title = {Hallucinating symmetric protein assemblies},

author = {B. I. M. Wicky and L. F. Milles and A. Courbet and R. J. Ragotte and J. Dauparas and E. Kinfu and S. Tipps and R. D. Kibler and M. Baek and F. DiMaio and X. Li and L. Carter and A. Kang and H. Nguyen and A. K. Bera and D. Baker},

url = {https://www.science.org/doi/abs/10.1126/science.add1964, Science

https://www.bakerlab.org/wp-content/uploads/2022/09/Wicky_etal_Science2022_Hallucinating_symmetric_protein_assemblies.pdf, PDF

},

doi = {10.1126/science.add1964},

year  = {2022},

date = {2022-09-15},

journal = {Science},

abstract = {Deep learning generative approaches provide an opportunity to broadly explore protein structure space beyond the sequences and structures of natural proteins. Here we use deep network hallucination to generate a wide range of symmetric protein homo-oligomers given only a specification of the number of protomers and the protomer length. Crystal structures of 7 designs are very close to the computational models (median RMSD: 0.6 Å), as are 3 cryoEM structures of giant 10 nanometer rings with up to 1550 residues and C33 symmetry; all differ considerably from previously solved structures. Our results highlight the rich diversity of new protein structures that can be generated using deep learning, and pave the way for the design of increasingly complex components for nanomachines and biomaterials.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Hsia2012,

title = {Design of multi-scale protein complexes by hierarchical building block fusion},

author = {Hsia, Yang

and Mout, Rubul

and Sheffler, William

and Edman, Natasha I.

and Vulovic, Ivan

and Park, Young-Jun

and Redler, Rachel L.

and Bick, Matthew J.

and Bera, Asim K.

and Courbet, Alexis

and Kang, Alex

and Brunette, T. J.

and Nattermann, Una

and Tsai, Evelyn

and Saleem, Ayesha

and Chow, Cameron M.

and Ekiert, Damian

and Bhabha, Gira

and Veesler, David

and Baker, David},

url = {https://www.nature.com/articles/s41467-021-22276-z, Nature Communications

https://www.bakerlab.org/wp-content/uploads/2021/04/Hsia_etal_NatComms_WORMS.pdf, Download PDF},

doi = {10.1038/s41467-021-22276-z},

year  = {2021},

date = {2021-04-16},

urldate = {2021-04-16},

journal = {Nature Communications},

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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Ben-Sasson2020,

title = {Design of biologically active binary protein 2D materials},

author = {Ben-Sasson, Ariel J. and Watson, Joseph L. and Sheffler, William and Johnson, Matthew Camp and Bittleston, Alice and Somasundaram, Logeshwaran and Decarreau, Justin and Jiao, Fang and Chen, Jiajun and Mela, Ioanna and Drabek, Andrew A. and Jarrett, Sanchez M. and Blacklow, Stephen C. and Kaminski, Clemens F. and Hura, Greg L. and De Yoreo, James J. and Kollman, Justin M. and Ruohola-Baker, Hannele and Derivery, Emmanuel and Baker, David},

url = {https://www.nature.com/articles/s41586-020-03120-8, Nature

https://www.bakerlab.org/wp-content/uploads/2021/02/Ben-Sasson_Nature2021_Binary_2D_arrays.pdf, Download PDF},

doi = {10.1038/s41586-020-03120-8},

year  = {2021},

date = {2021-01-06},

urldate = {2021-01-06},

journal = {Nature},

abstract = {Ordered two-dimensional arrays such as S-layers1,2 and designed analogues3–5 have intrigued bioengineers6,7, but with the exception of a single lattice formed with flexible linkers8, they are constituted from just one protein component. Materials composed of two components have considerable potential advantages for modulating assembly dynamics and incorporating more complex functionality9–12. Here we describe a computational method to generate co-assembling binary layers by designing rigid interfaces between pairs of dihedral protein building blocks, and use it to design a p6m lattice. The designed array components are soluble at millimolar concentrations, but when combined at nanomolar concentrations, they rapidly assemble into nearly crystalline micrometre-scale arrays nearly identical to the computational design model in vitro and in cells without the need for a two-dimensional support. Because the material is designed from the ground up, the components can be readily functionalized and their symmetry reconfigured, enabling formation of ligand arrays with distinguishable surfaces, which we demonstrate can drive extensive receptor clustering, downstream protein recruitment and signalling. Using atomic force microscopy on supported bilayers and quantitative microscopy on living cells, we show that arrays assembled on membranes have component stoichiometry and structure similar to arrays formed in vitro, and that our material can therefore impose order onto fundamentally disordered substrates such as cell membranes. In contrast to previously characterized cell surface receptor binding assemblies such as antibodies and nanocages, which are rapidly endocytosed, we find that large arrays assembled at the cell surface suppress endocytosis in a tunable manner, with potential therapeutic relevance for extending receptor engagement and immune evasion. Our work provides a foundation for a synthetic cell biology in which multi-protein macroscale materials are designed to modulate cell responses and reshape synthetic and living systems.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Pyles2019,

title = {Controlling protein assembly on inorganic crystals through designed protein interfaces},

author = {Harley Pyles and Shuai Zhang and James J. De Yoreo and David Baker },

url = {https://www.nature.com/articles/s41586-019-1361-6

https://www.bakerlab.org/wp-content/uploads/2019/07/2019_Pyles_MicaBinder.pdf},

doi = {10.1038/s41586-019-1361-6},

year  = {2019},

date = {2019-07-10},

journal = {Nature},

abstract = {The ability of proteins and other macromolecules to interact with inorganic surfaces is essential to biological function. The proteins involved in these interactions are highly charged and often rich in carboxylic acid side chains, but the structures of most protein–inorganic interfaces are unknown. We explored the possibility of systematically designing structured protein–mineral interfaces, guided by the example of ice-binding proteins, which present arrays of threonine residues (matched to the ice lattice) that order clathrate waters into an ice-like structure6. Here we design proteins displaying arrays of up to 54 carboxylate residues geometrically matched to the potassium ion (K+) sublattice on muscovite mica (001). At low K+ concentration, individual molecules bind independently to mica in the designed orientations, whereas at high K+ concentration, the designs form two-dimensional liquid-crystal phases, which accentuate the inherent structural bias in the muscovite lattice to produce protein arrays ordered over tens of millimetres. Incorporation of designed protein–protein interactions preserving the match between the proteins and the K+ lattice led to extended self-assembled structures on mica: designed end-to-end interactions produced micrometre-long single-protein-diameter wires and a designed trimeric interface yielded extensive honeycomb arrays. The nearest-neighbour distances in these hexagonal arrays could be set digitally between 7.5 and 15.9 nanometres with 2.1-nanometre selectivity by changing the number of repeat units in the monomer. These results demonstrate that protein–inorganic lattice interactions can be systematically programmed and set the stage for designing protein–inorganic hybrid materials.



},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Shen2018,

title = {De novo design of self-assembling helical protein filaments},

author = {Shen, Hao and Fallas, Jorge A. and Lynch, Eric and Sheffler, William and Parry, Bradley and Jannetty, Nicholas and Decarreau, Justin and Wagenbach, Michael and Vicente, Juan Jesus and Chen, Jiajun and Wang, Lei and Dowling, Quinton and Oberdorfer, Gustav and Stewart, Lance and Wordeman, Linda and De Yoreo, James and Jacobs-Wagner, Christine and Kollman, Justin and Baker, David},

url = {http://science.sciencemag.org/content/362/6415/705

https://www.bakerlab.org/wp-content/uploads/2018/12/Shen2018_filaments.pdf},

doi = {10.1126/science.aau3775},

issn = {0036-8075},

year  = {2018},

date = {2018-11-09},

journal = {Science},

volume = {362},

number = {6415},

pages = {705–709},

abstract = {There has been some success in designing stable peptide filaments; however, mimicking the reversible assembly of many natural protein filaments is challenging. Dynamic filaments usually comprise independently folded and asymmetric proteins and using such building blocks requires the design of multiple intermonomer interfaces. Shen et al. report the design of self-assembling helical filaments based on previously designed stable repeat proteins. The filaments are micron scale, and their diameter can be tuned by varying the number of repeats in the monomer. Anchor and capping units, built from monomers that lack an interaction interface, can be used to control assembly and disassembly.Science, this issue p. 705We describe a general computational approach to designing self-assembling helical filaments from monomeric proteins and use this approach to design proteins that assemble into micrometer-scale filaments with a wide range of geometries in vivo and in vitro. Cryo{textendash}electron microscopy structures of six designs are close to the computational design models. The filament building blocks are idealized repeat proteins, and thus the diameter of the filaments can be systematically tuned by varying the number of repeat units. The assembly and disassembly of the filaments can be controlled by engineered anchor and capping units built from monomers lacking one of the interaction surfaces. The ability to generate dynamic, highly ordered structures that span micrometers from protein monomers opens up possibilities for the fabrication of new multiscale metamaterials.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Butterfield2017,

title = {Evolution of a designed protein assembly encapsulating its own RNA genome},

author = {Butterfield, Gabriel L.*

and Lajoie, Marc J.*

and Gustafson, Heather H.

and Sellers, Drew L.

and Nattermann, Una

and Ellis, Daniel

and Bale, Jacob B.

and Ke, Sharon

and Lenz, Garreck H.

and Yehdego, Angelica

and Ravichandran, Rashmi

and Pun, Suzie H.

and King, Neil P.

and Baker, David},

url = {http://dx.doi.org/10.1038/nature25157

https://www.bakerlab.org/wp-content/uploads/2017/12/Nature_Butterfield_et_al_2017.pdf},

doi = {10.1038/nature25157},

issn = {1476-4687},

year  = {2017},

date = {2017-12-13},

journal = {Nature},

abstract = {The challenges of evolution in a complex biochemical environment, coupling genotype to phenotype and protecting the genetic material, are solved elegantly in biological systems by the encapsulation of nucleic acids. In the simplest examples, viruses use capsids to surround their genomes. Although these naturally occurring systems have been modified to change their tropism and to display proteins or peptides, billions of years of evolution have favoured efficiency at the expense of modularity, making viral capsids difficult to engineer. Synthetic systems composed of non-viral proteins could provide a ‘blank slate’ to evolve desired properties for drug delivery and other biomedical applications, while avoiding the safety risks and engineering challenges associated with viruses. Here we create synthetic nucleocapsids, which are computationally designed icosahedral protein assemblies with positively charged inner surfaces that can package their own full-length mRNA genomes. We explore the ability of these nucleocapsids to evolve virus-like properties by generating diversified populations using Escherichia coli as an expression host. Several generations of evolution resulted in markedly improved genome packaging (more than 133-fold), stability in blood (from less than 3.7% to 71% of packaged RNA protected after 6hours of treatment), and in vivo circulation time (from less than 5minutes to approximately 4.5hours). The resulting synthetic nucleocapsids package one full length RNA genome for every 11 icosahedral assemblies, similar to the best recombinant adeno-associated virus vectors. Our results show that there are simple evolutionary paths through which protein assemblies can acquire virus-like genome packaging and protection. Considerable effort has been directed at ‘top-down’ modification of viruses to be safe and effective for drug delivery and vaccine applications; the ability to design synthetic nanomaterials computationally and to optimize them through evolution now enables a complementary ‘bottom-up’ approach with considerable advantages in programmability and control.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Bale2016,

title = {Accurate design of megadalton-scale two-component icosahedral protein complexes},

author = {Jacob B. Bale and Shane Gonen and Yuxi Liu and William Sheffler and Daniel Ellis and Chantz Thomas and Duilio Cascio and Todd O. Yeates and Tamir Gonen and Neil P. King and David Baker},

url = {https://www.bakerlab.org/wp-content/uploads/2016/07/Bale_Science_2016.pdf},

doi = {10.1126/science.aaf8818},

year  = {2016},

date = {2016-07-22},

journal = {Science},

volume = {353},

number = {6297},

pages = {389-394},

abstract = {Nature provides many examples of self- and co-assembling protein-based molecular machines, including icosahedral protein cages that serve as scaffolds, enzymes, and compartments for essential biochemical reactions and icosahedral virus capsids, which encapsidate and protect viral genomes and mediate entry into host cells. Inspired by these natural materials, we report the computational design and experimental characterization of co-assembling, two-component, 120-subunit icosahedral protein nanostructures with molecular weights (1.8 to 2.8 megadaltons) and dimensions (24 to 40 nanometers in diameter) comparable to those of small viral capsids. Electron microscopy, small-angle x-ray scattering, and x-ray crystallography show that 10 designs spanning three distinct icosahedral architectures form materials closely matching the design models. In vitro assembly of icosahedral complexes from independently purified components occurs rapidly, at rates comparable to those of viral capsids, and enables controlled packaging of molecular cargo through charge complementarity. The ability to design megadalton-scale materials with atomic-level accuracy and controllable assembly opens the door to a new generation of genetically programmable protein-based molecular machines.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Boyken680,

title = {De novo design of protein homo-oligomers with modular hydrogen-bond network–mediated specificity},

author = { Scott E. Boyken and Zibo Chen and Benjamin Groves and Robert A. Langan and Gustav Oberdorfer and Alex Ford and Jason M. Gilmore and Chunfu Xu and Frank DiMaio and Jose Henrique Pereira and Banumathi Sankaran and Georg Seelig and Peter H. Zwart and David Baker},

url = {http://science.sciencemag.org/content/352/6286/680

https://www.bakerlab.org/wp-content/uploads/2016/05/680.full_.pdf},

doi = {10.1126/science.aad8865},

issn = {0036-8075},

year  = {2016},

date = {2016-01-01},

journal = {Science},

volume = {352},

number = {6286},

pages = {680--687},

publisher = {American Association for the Advancement of Science},

abstract = {General design principles for protein interaction specificity are challenging to extract. DNA nanotechnology, on the other hand, has harnessed the limited set of hydrogen-bonding interactions from Watson-Crick base-pairing to design and build a wide range of shapes. Protein-based materials have the potential for even greater geometric and chemical diversity, including additional functionality. Boyken et al. designed a class of protein oligomers that have interaction specificity determined by modular arrays of extensive hydrogen bond networks (see the Perspective by Netzer and Fleishman). They use the approach, which could one day become programmable, to build novel topologies with two concentric rings of helices.Science, this issue p. 680; see also p. 657In nature, structural specificity in DNA and proteins is encoded differently: In DNA, specificity arises from modular hydrogen bonds in the core of the double helix, whereas in proteins, specificity arises largely from buried hydrophobic packing complemented by irregular peripheral polar interactions. Here, we describe a general approach for designing a wide range of protein homo-oligomers with specificity determined by modular arrays of central hydrogen-bond networks. We use the approach to design dimers, trimers, and tetramers consisting of two concentric rings of helices, including previously not seen triangular, square, and supercoiled topologies. X-ray crystallography confirms that the structures overall, and the hydrogen-bond networks in particular, are nearly identical to the design models, and the networks confer interaction specificity in vivo. The ability to design extensive hydrogen-bond networks with atomic accuracy enables the programming of protein interaction specificity for a broad range of synthetic biology applications; more generally, our results demonstrate that, even with the tremendous diversity observed in nature, there are fundamentally new modes of interaction to be discovered in proteins.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{L2015,

title = {Rational design of α-helical tandem repeat proteins with closed architectures},

author = {L Doyle and J Hallinan and J Bolduc and F Parmeggiani and D Baker and BL Stoddard and P Bradley},

url = {https://www.bakerlab.org/wp-content/uploads/2015/12/Doyle_Nature_2015.pdf},

doi = {10.1038/nature16191},

year  = {2015},

date = {2015-12-24},

journal = {Nature},

volume = {528(7583)},

pages = {585-8},

abstract = {Tandem repeat proteins, which are formed by repetition of modular units of protein sequence and structure, play important biological roles as macromolecular binding and scaffolding domains, enzymes, and building blocks for the assembly of fibrous materials. The modular nature of repeat proteins enables the rapid construction and diversification of extended binding surfaces by duplication and recombination of simple building blocks. The overall architecture of tandem repeat protein structures--which is dictated by the internal geometry and local packing of the repeat building blocks--is highly diverse, ranging from extended, super-helical folds that bind peptide, DNA, and RNA partners, to closed and compact conformations with internal cavities suitable for small molecule binding and catalysis. Here we report the development and validation of computational methods for de novo design of tandem repeat protein architectures driven purely by geometric criteria defining the inter-repeat geometry, without reference to the sequences and structures of existing repeat protein families. We have applied these methods to design a series of closed α-solenoid repeat structures (α-toroids) in which the inter-repeat packing geometry is constrained so as to juxtapose the amino (N) and carboxy (C) termini; several of these designed structures have been validated by X-ray crystallography. Unlike previous approaches to tandem repeat protein engineering, our design procedure does not rely on template sequence or structural information taken from natural repeat proteins and hence can produce structures unlike those seen in nature. As an example, we have successfully designed and validated closed α-solenoid repeats with a left-handed helical architecture that--to our knowledge--is not yet present in the protein structure database.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{616,

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 = {http://www.bakerlab.org/wp-content/uploads/2015/12/Bale_designed_tetrahedral_ProteinSci2015.pdf},

doi = {10.1002/pro.2748},

issn = {1469-896X},

year  = {2015},

date = {2015-07-01},

journal = {Protein science : a publication of the Protein Society},

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}

}