A general-purpose protein design framework based on mining sequence–structure relationships in known protein structures

Zhou, Jianfu; Panaitiu, Alexandra E.; Grigoryan, Gevorg

doi:10.1073/pnas.1908723117

Cited by 92 publications

(117 citation statements)

References 84 publications

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“…This outcome led us to speculate whether structural motifs other than RxxxR could mediate the lateral interaction between helical stacks and promote nanotube formation. The 36-31-3 filament was employed as the starting point for a computational optimization using the design engine dTERMen 74 , 75 . A solubility constraint was applied in which the occupancy of the solvent-contacting b/e/g residues within the heptad repeats was constrained to polar residues.…”

Section: Resultsmentioning

confidence: 99%

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Structural analysis of cross α-helical nanotubes provides insight into the designability of filamentous peptide nanomaterials

et al. 2021

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The exquisite structure-function correlations observed in filamentous protein assemblies provide a paradigm for the design of synthetic peptide-based nanomaterials. However, the plasticity of quaternary structure in sequence-space and the lability of helical symmetry present significant challenges to the de novo design and structural analysis of such filaments. Here, we describe a rational approach to design self-assembling peptide nanotubes based on controlling lateral interactions between protofilaments having an unusual cross-α supramolecular architecture. Near-atomic resolution cryo-EM structural analysis of seven designed nanotubes provides insight into the designability of interfaces within these synthetic peptide assemblies and identifies a non-native structural interaction based on a pair of arginine residues. This arginine clasp motif can robustly mediate cohesive interactions between protofilaments within the cross-α nanotubes. The structure of the resultant assemblies can be controlled through the sequence and length of the peptide subunits, which generates synthetic peptide filaments of similar dimensions to flagella and pili.

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Section: Resultsmentioning

confidence: 99%

“…dTERMen 74 , 75 was used to perform design. dTERMen is a general-purpose method for computational protein design that is based on the concept of structural degeneracy of proteins.…”

Section: Methodsmentioning

confidence: 99%

Structural analysis of cross α-helical nanotubes provides insight into the designability of filamentous peptide nanomaterials

et al. 2021

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“…In practice, the generation of diverse sequences with Rosetta often requires manually manipulating amino acid identities at key positions [7,9], adjusting the energy function [43,44], or explicitly modeling perturbations of the protein backbone [45,46,47,48]. Design methods that account for flexibility of the protein backbone often use "softer" potentials [44,49], such as statistical potentials that are derived from data [50,51,50,52,53,54], but these methods often do not perform as favorably as well-parameterized "hard" molecular mechanics force fields.…”

Section: Introductionmentioning

confidence: 99%

Protein Sequence Design with a Learned Potential

Anand

Eguchi

Mathews

et al. 2020

Preprint

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The primary challenge of fixed-backbone protein sequence design is to find a distribution of sequences that fold to the backbone of interest. In practice, state-of-the-art protocols often find viable but highly convergent solutions. In this study, we propose a novel method for fixed-backbone protein sequence design using a learned deep neural network potential. We train a convolutional neural network (CNN) to predict a distribution over amino acids at each residue position conditioned on the local structural environment around the residues. Our method for sequence design involves iteratively sampling from this conditional distribution. We demonstrate that this approach is able to produce feasible, novel designs with quality on par with the state-of-the-art, while achieving greater design diversity. In terms of generalizability, our method produces plausible and variable designs for a de novo TIM-barrel structure, showcasing its practical utility in design applications for which there are no known native structures.

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“…However, DF and PS1 have distinct bundle architectures with respect to their interhelical packing, helical offsets, and helical registers, which together presented challenges for structural design. To address these challenges, we extended previous fragment-based approaches ( 43 – 48 ) and designed artificial multidomain proteins with allosterically communicating sites.…”

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confidence: 99%

Allosteric cooperation in a de novo-designed two-domain protein

Pirro

Schmidt

Lincoff

et al. 2020

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

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We describe the de novo design of an allosterically regulated protein, which comprises two tightly coupled domains. One domain is based on the DF (Due Ferri in Italian or two-iron in English) family of de novo proteins, which have a diiron cofactor that catalyzes a phenol oxidase reaction, while the second domain is based on PS1 (Porphyrin-binding Sequence), which binds a synthetic Zn-porphyrin (ZnP). The binding of ZnP to the original PS1 protein induces changes in structure and dynamics, which we expected to influence the catalytic rate of a fused DF domain when appropriately coupled. Both DF and PS1 are four-helix bundles, but they have distinct bundle architectures. To achieve tight coupling between the domains, they were connected by four helical linkers using a computational method to discover the most designable connections capable of spanning the two architectures. The resulting protein, DFP1 (Due Ferri Porphyrin), bound the two cofactors in the expected manner. The crystal structure of fully reconstituted DFP1 was also in excellent agreement with the design, and it showed the ZnP cofactor bound over 12 Å from the dimetal center. Next, a substrate-binding cleft leading to the diiron center was introduced into DFP1. The resulting protein acts as an allosterically modulated phenol oxidase. Its Michaelis–Menten parameters were strongly affected by the binding of ZnP, resulting in a fourfold tighter Km and a 7-fold decrease in kcat. These studies establish the feasibility of designing allosterically regulated catalytic proteins, entirely from scratch.

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A general-purpose protein design framework based on mining sequence–structure relationships in known protein structures

Cited by 92 publications

References 84 publications

Structural analysis of cross α-helical nanotubes provides insight into the designability of filamentous peptide nanomaterials

Structural analysis of cross α-helical nanotubes provides insight into the designability of filamentous peptide nanomaterials

Protein Sequence Design with a Learned Potential

Allosteric cooperation in a de novo-designed two-domain protein

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