Identification and Analysis of Natural Building Blocks for Evolution-Guided Fragment-Based Protein Design

Ferruz, Noelia; Lobos, Francisco; Lemm, Dominik; Toledo-Patiño, Saacnicteh; Farías-Rico, José Arcadio; Schmidt, Steffen; Höcker, Birte

doi:10.1016/j.jmb.2020.04.013

Cited by 39 publications

(63 citation statements)

References 87 publications

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“…Although the focus of this manuscript was on combining fragments from homologous family members, we note that we have used AbDesign to recombine fragments from non‐homologous proteins to generate new backbones and polar interaction networks in binding pairs 4 . Furthermore, recent proteome‐wide analyses have detected significant homology between protein fragments that come from evolutionarily very distant families 44–47 . These observations suggest that modular assembly can be used to generate structural innovations beyond the family and even fold level.…”

Section: Discussionmentioning

confidence: 99%

The AbDesign computational pipeline for modular backbone assembly and design of binders and enzymes

2020

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The functional sites of many protein families are dominated by diverse backbone regions that lack secondary structure (loops) but fold stably into their functionally competent state. Nevertheless, the design of structured loop regions from scratch, especially in functional sites, has met with great difficulty. We therefore developed an approach, called AbDesign, to exploit the natural modularity of many protein families and computationally assemble a large number of new backbones by combining naturally occurring modular fragments. This strategy yielded large, atomically accurate, and highly efficient proteins, including antibodies and enzymes exhibiting dozens of mutations from any natural protein. The combinatorial backbone‐conformation space that can be accessed by AbDesign even for a modestly sized family of homologs may exceed the diversity in the entire PDB, providing the sub‐Ångstrom level of control over the positioning of active‐site groups that is necessary for obtaining highly active proteins. This manuscript describes how to implement the pipeline using code that is freely available at https://github.com/Fleishman‐Lab/AbDesign_for_enzymes.

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Section: Discussionmentioning

confidence: 99%

The AbDesign computational pipeline for modular backbone assembly and design of binders and enzymes

2020

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“…1,1). Each hit in Fuzzle contains information about the two domains that contain a common fragment (denoted query and subject), start and end of the fragment they share, HHsearch probability, and RMSD, among others (Ferruz et al, 2020). Protlego enables fetching hits from the Fuzzle database searching via PDB identifier, domain identifiers, specific SCOPe groups (families, superfamilies and folds).…”

Section: Fetching Hits From the Fuzzle Databasementioning

confidence: 99%

“…In this case, we fetched 1737 hits which overall contain 432 different domains. All domains in the Fuzzle database have been clustered previously according to the regions in their sequence (Ferruz et al, 2020). For example, a domain A might have two hits: in hit1 it forms a local alignment with amino acids 1 to 30, while in hit2 it aligns with amino acids 90 to 150.…”

Section: View Of Evolutionary Relationships Via Networkmentioning

confidence: 99%

“…These 'island-like' motifs are termed components in network theory. For further details on the construction of the network and definitions we refer to our previous publication on Fuzzle (Ferruz et al, 2020). The network consists in this case of 17 components with very diverse sizes.…”

Section: View Of Evolutionary Relationships Via Networkmentioning

confidence: 99%

“…Similarly, we recently performed an all-againstall comparison of protein domains representing all existing folds and identified more than 1000 conserved protein fragments of various lengths across protein space. These fragments are present in different protein environments and represent building blocks that nature has reused through the course of evolution and that can now be browsed in the publicly available Fuzzle database (www.fuzzle.uni-bayreuth.de) (Ferruz et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

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Protlego: A Python package for the analysis and design of chimeric proteins

Ferruz

Noske

Hoecker

2020

Preprint

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MotivationGene duplication and recombination of protein fragments have led to the highly diverse protein space that we observe today. By mimicking this natural process, the design of protein chimeras via fragment recombination has proven experimentally successful and has opened a new era for the design of customizable proteins. The in-silico building of structural models for these chimeric proteins, however, remains a manual task that requires a considerable degree of expertise and is not amenable for high-throughput studies. Energetic and structural analysis of the designed proteins often require the use of several tools, each with their unique technical difficulties and available in different programming languages or web servers.ResultsWe have implemented a Python package that enables automated, high-throughput design of chimeras and their structural analysis. First, it is possible to fetch evolutionarily conserved fragments from a built-in database (also available at fuzzle.uni-bayreuth.de). These relationships can then be represented via networks or further selected for chimera construction via recombination. Designed chimeras or natural proteins are then scored and minimised with the Charmm and Amber forcefields and their diverse structural features can be analysed at ease. Here, we showcase Protlego’s pipeline by exploring the relationships between the P-loop and Rossmann superfolds and building and characterising their offspring chimeras. We believe that Protlego provides a powerful new tool for the protein design community.Availability and implementationProtlego is freely available at (https://hoecker-lab.github.io/protlego/) with tutorials and documentation.

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Molecular handcraft of a well‐folded protein chimera

Toledo‐Patiño,

Goetz,

Shanmugaratnam

et al. 2024

FEBS Letters

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Modular assembly is a compelling pathway to create new proteins, a concept supported by protein engineering and millennia of evolution. Natural evolution provided a repository of building blocks, known as domains, which trace back to even shorter segments that underwent numerous ‘copy‐paste’ processes culminating in the scaffolds we see today. Utilizing the subdomain‐database Fuzzle, we constructed a fold‐chimera by integrating a flavodoxin‐like fragment into a periplasmic binding protein. This chimera is well‐folded and a crystal structure reveals stable interfaces between the fragments. These findings demonstrate the adaptability of α/β‐proteins and offer a stepping stone for optimization. By emphasizing the practicality of fragment databases, our work pioneers new pathways in protein engineering. Ultimately, the results substantiate the conjecture that periplasmic binding proteins originated from a flavodoxin‐like ancestor.

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Identification and Analysis of Natural Building Blocks for Evolution-Guided Fragment-Based Protein Design

Cited by 39 publications

References 87 publications

The AbDesign computational pipeline for modular backbone assembly and design of binders and enzymes

The AbDesign computational pipeline for modular backbone assembly and design of binders and enzymes

Protlego: A Python package for the analysis and design of chimeric proteins

Molecular handcraft of a well‐folded protein chimera

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