Computational Design of Self-Assembling Protein Nanomaterials with Atomic Level Accuracy

King, Neil P.; Sheffler, William; Sawaya, M.R.; Vollmar, Breanna S.; Sumida, John P.; André, Ingemar; Gonen, Tamir; Yeates, Todd O.; Baker, David

doi:10.1126/science.1219364

Cited by 604 publications

(599 citation statements)

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“…Internal repeats were constrained to adopt the same primary sequence, side-chain, and backbone conformations by using symmetric sequence design and conformation sampling during all modeling moves. Symmetric structure prediction [18] and design has been used extensively in Rosetta [11] yielding atomic-accuracy predictions for large homomeric oligomers, designed cage-like assemblies or repeat proteins [12][13][14][15][19][20][21]. Our calculations were restricted to three internal repeats and two capping repeats.…”

Section: In Silico Designmentioning

confidence: 99%

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Computationally Designed Armadillo Repeat Proteins for Modular Peptide Recognition

Reichen

Hansen

Forzani

et al. 2016

Journal of Molecular Biology

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Armadillo repeat proteins (ArmRP) recognize their target peptide in extended conformation and bind, in a first approximation, two residues per repeat. They may thus form the basis for building a modular system, in which each repeat is complementary to a piece of the target peptide. Accordingly, preselected repeats could be assembled into specific binding proteins on demand and thereby avoid the traditional generation of every new binding molecule by an independent selection from a library.Stacked armadillo repeats, each consisting of 42 amino acids arranged in three α-helices, build an elongated superhelical structure. Here, we analyzed curvature variations in natural ArmRPs, and identified a repeat pair from yeast importin-α as having the optimal curvature geometry to be complementary to a peptide over its whole length. We employed a symmetric in silico design to obtain a uniform sequence for a stackable repeat while maintaining the desired curvature geometry.Computationally designed armadillo repeat proteins (dArmRPs) had to be stabilized by mutations to remove regions of higher flexibility, which were identified by molecular dynamics (MD) simulations in explicit solvent. Using an N-capping repeat from the consensus-design approach, two different crystal structures of dArmRP were determined. Although the experimental structures of dArmRP deviated from the designed curvature, the insertion of the most conserved binding pockets of natural ArmRPs onto the surface of dArmRPs resulted in binders against the expected peptide with low nanomolar affinities, similar to the binders from the consensus-design series.

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Section: In Silico Designmentioning

confidence: 99%

“…In the N-cap, Trp 19 was introduced for practical reasons, to determine the protein concentration by UV absorbance at 280 nm. F 38 was preserved in the C-cap as observed in natural armadillo repeat proteins, while the neighboring residues were redesigned using Rosetta.…”

Section: In Silico Designmentioning

confidence: 99%

Computationally Designed Armadillo Repeat Proteins for Modular Peptide Recognition

Reichen

Hansen

Forzani

et al. 2016

Journal of Molecular Biology

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“…de novo design | protein design | ideal protein | control protein shape P rotein design holds promise for applications ranging from therapeutics to biomaterials, with recent progress in designing small molecule binding proteins (1,2), inhibitors of protein-protein interactions (3,4), and self-assembling nanomaterials (5)(6)(7). Most of these efforts have repurposed naturally occurring scaffolds, which are likely not optimal starting points for creating new functions because they generally contain sequence and structural idiosyncrasies that arose during evolutionary optimization for their natural functions (8).…”

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confidence: 99%

Control over overall shape and size in de novo designed proteins

Lin

Koga

Tatsumi-Koga

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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148

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We recently described general principles for designing ideal protein structures stabilized by completely consistent local and nonlocal interactions. The principles relate secondary structure patterns to tertiary packing motifs and enable design of different protein topologies. To achieve fine control over protein shape and size within a particular topology, we have extended the design rules by systematically analyzing the codependencies between the lengths and packing geometry of successive secondary structure elements and the backbone torsion angles of the loop linking them. We demonstrate the control afforded by the resulting extended rule set by designing a series of proteins with the same fold but considerable variation in secondary structure length, loop geometry, β-strand registry, and overall shape. Solution NMR structures of four designed proteins for two different folds show that protein shape and size can be precisely controlled within a given protein fold. These extended design principles provide the foundation for custom design of protein structures performing desired functions.de novo design | protein design | ideal protein | control protein shape P rotein design holds promise for applications ranging from therapeutics to biomaterials, with recent progress in designing small molecule binding proteins (1, 2), inhibitors of protein-protein interactions (3, 4), and self-assembling nanomaterials (5-7). Most of these efforts have repurposed naturally occurring scaffolds, which are likely not optimal starting points for creating new functions because they generally contain sequence and structural idiosyncrasies that arose during evolutionary optimization for their natural functions (8). Robust design of new functional proteins would be considerably enabled by the capability of precisely designing from scratch arbitrary protein structures.We previously described general principles that allowed the de novo design of ideal protein structures with five different folds (9). In this paper, we focus on the "variations on a theme" problem of precisely controlling structural variation within the same fold. To achieve such control, we begin by characterizing the coupling between loop backbone geometry and the packing of the flanking secondary elements. We then use the resulting extended set of design principles to systematically vary structure for two different folds and describe the experimental characterization of five of these de novo designed proteins. ResultsLocal Structure Building Blocks. The design rules described in our previous paper relate the packing orientation of ββ-, βα-, and αβ-units to the length of the loop connecting them (9). Here, we begin by extending these rules to the level of specific loop conformations to allow more detailed control over local geometry and overall protein topology.It is convenient to describe protein local geometry by using the ABEGO (10) alphabet illustrated in Fig. 1A. "A" indicates the alpha region of the Ramachandran plot (11); "B," the beta region; "G" and "E", the po...

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“…38 More recently, selfassembling single-and multi-component protein complexes have successfully been computationally designed and experimentally realized, based on detailed analysis of the interfaces between the proteins. 39,40 In the latter work, the interactions were manipulated by altering the amino acid sequence of real proteins to optimize the interfaces that would be required in the desired target.…”

Section: Modelmentioning

confidence: 99%

Design strategies for self-assembly of discrete targets

Madge

Miller

2015

The Journal of Chemical Physics

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Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. Both biological and artificial self-assembly processes can take place by a range of different schemes, from the successive addition of identical building blocks to hierarchical sequences of intermediates, all the way to the fully addressable limit in which each component is unique. In this paper, we introduce an idealized model of cubic particles with patterned faces that allows self-assembly strategies to be compared and tested. We consider a simple octameric target, starting with the minimal requirements for successful self-assembly and comparing the benefits and limitations of more sophisticated hierarchical and addressable schemes. Simulations are performed using a hybrid dynamical Monte Carlo protocol that allows self-assembling clusters to rearrange internally while still providing Stokes-Einstein-like diffusion of aggregates of different sizes. Our simulations explicitly capture the thermodynamic, dynamic, and steric challenges typically faced by self-assembly processes, including competition between multiple partially completed structures. Self-assembly pathways are extracted from the simulation trajectories by a fully extendable scheme for identifying structural fragments, which are then assembled into history diagrams for successfully completed target structures. For the simple target, a one-component assembly scheme is most efficient and robust overall, but hierarchical and addressable strategies can have an advantage under some conditions if high yield is a priority. C 2015 AIP Publishing LLC.[http://dx

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Computational Design of Self-Assembling Protein Nanomaterials with Atomic Level Accuracy

Cited by 604 publications

References 60 publications

Computationally Designed Armadillo Repeat Proteins for Modular Peptide Recognition

Computationally Designed Armadillo Repeat Proteins for Modular Peptide Recognition

Control over overall shape and size in de novo designed proteins

Design strategies for self-assembly of discrete targets

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