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Showing 1–17 of 17 results
Advanced filters: Author: William Sheffler Clear advanced filters

  • Deep learning-based generative tools are used to design protein building blocks with well-defined directional bonding interactions, allowing the generation of a variety of scalable protein assemblies from a small set of reusable subunits.

    • Shunzhi Wang
    • Andrew Favor
    • David Baker
    ResearchOpen Access
    Nature Materials
    Volume: 24, P: 1644-1652

  • A computational method is reported that can be used to design protein nanomaterials in which two distinct subunits co-assemble into a specific architecture; five 24-subunit cage-like protein nanomaterials are designed, and experiments show that their structures are in close agreement with the computational design models.

    • Neil P. King
    • Jacob B. Bale
    • David Baker
    Research
    Nature
    Volume: 510, P: 103-108

  • A computational method to design cyclic protein homo-oligomers has been developed. Using this approach, a series of idealized repeat proteins incorporating designed interfaces that direct their assembly into complexes possessing cyclic symmetry were fabricated. 15 out of 96 oligomers that were characterized experimentally were shown to be consistent with the computational model.

    • Jorge A. Fallas
    • George Ueda
    • David Baker
    Research
    Nature Chemistry
    Volume: 9, P: 353-360

  • Engineering the tunability of protein assembly in response to pH changes within a narrow range is challenging. Here the authors report the de novo computational design of pH-responsive protein filaments that exhibit rapid, precise, tunable and reversible assembly and disassembly triggered by small pH changes.

    • Hao Shen
    • Eric M. Lynch
    • David Baker
    ResearchOpen Access
    Nature Nanotechnology
    Volume: 19, P: 1016-1021

  • A design pipeline is presented whereby binding proteins can be designed de novo without the need for prior information on binding hotspots or fragments from structures of complexes with binding partners.

    • Longxing Cao
    • Brian Coventry
    • David Baker
    ResearchOpen Access
    Nature
    Volume: 605, P: 551-560

  • De novo design of self-assembling protein nanostructures and materials is of significant interest, however design of complex, multi-component assemblies is challenging. Here, the authors present a stepwise hierarchical approach to build such assemblies using helical repeat and helical bundle proteins as building blocks, and provide an in-depth structural characterization of the resulting assemblies.

    • Yang Hsia
    • Rubul Mout
    • David Baker
    ResearchOpen Access
    Nature Communications
    Volume: 12, P: 1-10

  • Fine-tuning the RoseTTAFold structure prediction network on protein structure denoising tasks yields a generative model for protein design that achieves outstanding performance on a wide range of protein structure and function design challenges.

    • Joseph L. Watson
    • David Juergens
    • David Baker
    ResearchOpen Access
    Nature
    Volume: 620, P: 1089-1100

  • The process of protein crystallization is poorly understood and difficult to program through the primary sequence. Here the authors develop a computational approach to designing three-dimensional protein crystals with prespecified lattice architectures with high accuracy.

    • Zhe Li
    • Shunzhi Wang
    • David Baker
    Research
    Nature Materials
    Volume: 22, P: 1556-1563

  • Nanoparticles are a promising approach to increase immunogenicity of protein antigens for vaccines. Here, Brouwer et al. design self-assembling, two-component protein NPs that present native-like SOSIP trimers of HIV envelope protein and determine immunogenicity in a small animal model.

    • Philip J. M. Brouwer
    • Aleksandar Antanasijevic
    • Rogier W. Sanders
    ResearchOpen Access
    Nature Communications
    Volume: 10, P: 1-17

  • The elucidation of general principles for designing β-barrels enables the de novo creation of fluorescent proteins.

    • Jiayi Dou
    • Anastassia A. Vorobieva
    • David Baker
    Research
    Nature
    Volume: 561, P: 485-491

  • The computational design of an extremely stable icosahedral self-assembling protein nanocage is presented; the icosahedron should be useful for applications ranging from calibrating fluorescence microscopy to drug delivery.

    • Yang Hsia
    • Jacob B. Bale
    • David Baker
    Research
    Nature
    Volume: 535, P: 136-139