Computational design of symmetrical eight-bladed β-propeller proteins

Why we are made of proteins and nucleic acids: Structural biology views on extraterrestrial life

Is it a miracle that life exists on the Earth, or is it a common phenomenon in the universe? If extraterrestrial organisms exist, what are they like? To answer these questions, we must understand what kinds of molecules could evolve into life, or in other words, what properties are generally required to perform biological functions and store genetic information. This review summarizes recent findings on simple ancestral proteins, outlines the basic knowledge in textbooks, and discusses the generally required properties for biological molecules from structural biology viewpoints (e.g., restriction of shapes, and types of intra- and intermolecular interactions), leading to the conclusion that proteins and nucleic acids are at least one of the simplest (and perhaps very common) forms of catalytic and genetic biopolymers in the universe. This review article is an extended version of the Japanese article, On the Origin of Life: Coevolution between RNA and Peptide, published in SEIBUTSU BUTSURI Vol. 61, p. 232-235 (2021).

Biochemical, biophysical, and functional characterisation of the E3 ubiquitin ligase APC/C regulator CDC20 from Arabidopsis thaliana

The Anaphase Promoting Complex (APC/C), a large cullin-RING E3-type ubiquitin ligase, constitutes the ultimate target of the Spindle Assembly Checkpoint (SAC), an intricate regulatory circuit that ensures the high fidelity of chromosome segregation in eukaryotic organisms by delaying the onset of anaphase until each chromosome is properly bi-oriented on the mitotic spindle. Cell-division cycle protein 20 homologue (CDC20) is a key regulator of APC/C function in mitosis. The formation of the APC/C^CDC20 complex is required for the ubiquitination and degradation of select substrates, which is necessary to maintain the mitotic state. In contrast to the roles of CDC20 in animal species, little is known about CDC20 roles in the regulation of chromosome segregation in plants. Here we address this gap in knowledge and report the expression in insect cells; the biochemical and biophysical characterisation of Arabidopsis thaliana (AtCDC20) WD40 domain; and the nuclear and cytoplasmic distribution of full-length AtCDC20 when transiently expressed in tobacco plants. We also show that most AtCDC20 degrons share a high sequence similarity to other eukaryotes, arguing in favour of conserved degron functions in AtCDC20. However, important exceptions were noted such as the lack of a canonical MAD1 binding motif; a fully conserved RRY-box in all six AtCDC20 isoforms instead of a CRY-box motif, and low conservation of key residues known to be phosphorylated by BUB1 and PLK1 in other species to ensure a robust SAC response. Taken together, our studies provide insights into AtCDC20 structure and function and the evolution of SAC signalling in plants.

Computational Design of Miniprotein Binders

Miniprotein binders hold a great interest as a class of drugs that bridges the gap between monoclonal antibodies and small molecule drugs. Like monoclonal antibodies, they can be designed to bind to therapeutic targets with high affinity, but they are more stable and easier to produce and to administer. In this chapter, we present a structure-based computational generic approach for miniprotein inhibitor design. Specifically, we describe step-by-step the implementation of the approach for the design of miniprotein binders against the SARS-CoV-2 coronavirus, using available structural data on the SARS-CoV-2 spike receptor binding domain (RBD) in interaction with its native target, the human receptor ACE2. Structural data being increasingly accessible around many protein-protein interaction systems, this method might be applied to the design of miniprotein binders against numerous therapeutic targets. The computational pipeline exploits provable and deterministic artificial intelligence-based protein design methods, with some recent additions in terms of binding energy estimation, multistate design and diverse library generation.

Protein Design with Deep Learning

Computational Protein Design (CPD) has produced impressive results for engineering new proteins, resulting in a wide variety of applications. In the past few years, various efforts have aimed at replacing or improving existing design methods using Deep Learning technology to leverage the amount of publicly available protein data. Deep Learning (DL) is a very powerful tool to extract patterns from raw data, provided that data are formatted as mathematical objects and the architecture processing them is well suited to the targeted problem. In the case of protein data, specific representations are needed for both the amino acid sequence and the protein structure in order to capture respectively 1D and 3D information. As no consensus has been reached about the most suitable representations, this review describes the representations used so far, discusses their strengths and weaknesses, and details their associated DL architecture for design and related tasks.

Structure and stability of the designer protein WRAP-T and its permutants

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta $$\end{document}β-Propeller proteins are common natural disc-like pseudo-symmetric proteins that contain multiple repeats (‘blades’) each consisting of a 4-stranded anti-parallel \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta $$\end{document}β-sheet. So far, 4- to 12-bladed \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta $$\end{document}β-propellers have been discovered in nature showing large functional and sequential variation. Using computational design approaches, we created perfectly symmetric \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta $$\end{document}β-propellers out of natural pseudo-symmetric templates. These proteins are useful tools to study protein evolution of this very diverse fold. While the 7-bladed architecture is the most common, no symmetric 7-bladed monomer has been created and characterized so far. Here we describe such a engineered protein, based on a highly symmetric natural template, and test the effects of circular permutation on its stability. Geometrical analysis of this protein and other artificial symmetrical proteins reveals no systematic constraint that could be used to help in engineering of this fold, and suggests sequence constraints unique to each \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta $$\end{document}β-propeller sub-family.

Iterated local search with partition crossover for computational protein design

Structure-based computational protein design (CPD) refers to the problem of finding a sequence of amino acids which folds into a specific desired protein structure, and possibly fulfills some targeted biochemical properties. Recent studies point out the particularly rugged CPD energy landscape, suggesting that local search optimization methods should be designed and tuned to easily escape local minima attraction basins. In this article, we analyze the performance and search dynamics of an iterated local search (ILS) algorithm enhanced with partition crossover. Our algorithm, PILS, quickly finds local minima and escapes their basins of attraction by solution perturbation. Additionally, the partition crossover operator exploits the structure of the residue interaction graph in order to efficiently mix solutions and find new unexplored basins. Our results on a benchmark of 30 proteins of various topology and size show that PILS consistently finds lower energy solutions compared to Rosetta fixbb and a classic ILS, and that the corresponding sequences are mostly closer to the native.

Guaranteed Diversity and Optimality in Cost Function Network Based Computational Protein Design Methods

Proteins are the main active molecules of life. Although natural proteins play many roles, as enzymes or antibodies for example, there is a need to go beyond the repertoire of natural proteins to produce engineered proteins that precisely meet application requirements, in terms of function, stability, activity or other protein capacities. Computational Protein Design aims at designing new proteins from first principles, using full-atom molecular models. However, the size and complexity of proteins require approximations to make them amenable to energetic optimization queries. These approximations make the design process less reliable, and a provable optimal solution may fail. In practice, expensive libraries of solutions are therefore generated and tested. In this paper, we explore the idea of generating libraries of provably diverse low-energy solutions by extending cost function network algorithms with dedicated automaton-based diversity constraints on a large set of realistic full protein redesign problems. We observe that it is possible to generate provably diverse libraries in reasonable time and that the produced libraries do enhance the Native Sequence Recovery, a traditional measure of design methods reliability.

The symmetric designer protein Pizza as a scaffold for metal coordination

Symmetric proteins are currently of interest as they allow creation of larger assemblies and facilitate the incorporation of metal ions in the larger complexes. Recently this was demonstrated by the biomineralization of the cadmium-chloride nanocrystal via the Pizza designer protein. However, the mechanism behind this formation remained unclear. Here, we set out to investigate the mechanism driving the formation of this nanocrystal via truncation, mutation, and circular permutations. In addition, the interaction of other biologically relevant metal ions with these symmetric proteins to form larger symmetric complexes was also studied. The formation of the initial nanocrystal is shown to originate from steric strain, where His 58 induces a different rotameric conformation on His 73, thereby distorting an otherwise perfect planar ring of alternating cadmium and chlorine ions, resulting in the smallest nanocrystal. Similar highly symmetric complexes were also observed for the other biological relevant metal ions. However, the flexibility of the coordinating histidine residues allows each metal ion to adopt its preferred geometry leading to either monomeric or dimeric β-propeller units, where the metal ions are located at the interface between both propeller units. These results demonstrate that symmetric proteins are not only interesting to generate larger assemblies, but are also the perfect scaffold to create more complex metal based assemblies. Such metal protein assemblies may then find applications in bionanotechnology or biocatalysis.

The Taming of the Screw: the natural and artificial development of β-propeller proteins

Many proteins are found to possess repeated structural elements, which hint at ancient evolutionary origins and ongoing evolutionary processes. β-propeller proteins are a large family of such proteins, and a popular focus of structural analysis. This review highlights recent work to understand how they arose, and how they have developed into one of the most successful of all protein folds.

Development and applications of artificial symmetrical proteins

Since the determination of the first molecular models of proteins there has been interest in creating proteins artificially, but such methods have only become widely successful in the last decade. Gradual improvements over a long period of time have now yielded numerous examples of non-natural proteins, many of which are built from repeated elements. In this review we discuss the design of such symmetrical proteins and their various applications in chemistry and medicine.

Influence of circular permutations on the structure and stability of a six-fold circular symmetric designer protein

The β-propeller fold is adopted by a sequentially diverse family of repeat proteins with apparent rotational symmetry. While the structure is mostly stabilized by hydrophobic interactions, an additional stabilization is provided by hydrogen bonds between the N-and C-termini, which are almost invariably part of the same β-sheet. This feature is often referred to as the "Velcro" closure. The positioning of the termini within a blade is variable and depends on the protein family. In order to investigate the influence of this location on protein structure, folding and stability, we created different circular permutants, and a circularized version, of the designer propeller protein named Pizza. This protein is perfectly symmetrical, possessing six identical repeats. While all mutants adopt the same structure, the proteins lacking the "Velcro" closure were found to be significantly less resistant to thermal and chemical denaturation. This could explain why such proteins are rarely observed in nature. Interestingly the most common "Velcro" configuration for this protein family was not the most stable among the Pizza variants tested. The circularized version shows dramatically improved stability, which could have implications for future applications.

Molecular assemblies built with the artificial protein Pizza

Recently an artificial protein named Pizza6 was reported, which possesses six identical tandem repeats and adopts a monomeric β -propeller fold with sixfold structural symmetry. Pizza2, a truncated form that consists of a double tandem repeat, self-assembles into a trimer reconstructing the same propeller architecture as Pizza6. The ability of pizza proteins to self-assemble to form complete propellers makes them interesting building blocks to engineer larger symmetrical protein complexes such as symmetric nanoparticles. Here we have explored the self-assembly of Pizza2 fused to homo-oligomerizing peptides. In total, we engineered five different fusion proteins, of which three appeared to assemble successfully into larger complexes. Further characterization of these proteins showed one monodisperse designer protein with a structure close to the intended design. This protein was further fused to eGFP to investigate functionalization of the nanoparticle. The fusion protein was stable and could be expressed in high yield, showing that Pizza-based nanoparticles may be further decorated with functional domains.

Harnessing Conformational Plasticity to Generate Designer Enzymes

Recent years have witnessed an explosion of interest in understanding the role of conformational dynamics both in the evolution of new enzymatic activities from existing enzymes and in facilitating the emergence of enzymatic activity de novo on scaffolds that were previously non-catalytic. There are also an increasing number of examples in the literature of targeted engineering of conformational dynamics being successfully used to alter enzyme selectivity and activity. Despite the obvious importance of conformational dynamics to both enzyme function and evolvability, many (although not all) computational design approaches still focus either on pure sequence-based approaches or on using structures with limited flexibility to guide the design. However, there exist a wide variety of computational approaches that can be (re)purposed to introduce conformational dynamics as a key consideration in the design process. Coupled with laboratory evolution and more conventional existing sequence- and structure-based approaches, these techniques provide powerful tools for greatly expanding the protein engineering toolkit. This Perspective provides an overview of evolutionary studies that have dissected the role of conformational dynamics in facilitating the emergence of novel enzymes, as well as advances in computational approaches that allow one to target conformational dynamics as part of enzyme design. Harnessing conformational dynamics in engineering studies is a powerful paradigm with which to engineer the next generation of designer biocatalysts.

Structural plasticity of a designer protein sheds light on β-propeller protein evolution

β-propeller proteins are common in nature, where they are observed to adopt 4- to 10-fold internal rotational pseudo-symmetry. This size diversity can be explained by the evolutionary process of gene duplication and fusion. In this study, we investigated a distorted β-propeller protein, an apparent intermediate between two symmetries. From this template, we created a perfectly symmetric 9-bladed β-propeller named Cake, using computational design and ancestral sequence reconstruction. The designed repeat sequence was found to be capable of generating both 8-fold and 9-fold propellers which are highly stable. Cake variants with 2-10 identical copies of the repeat sequence were characterised by X-ray crystallography and in solution. They were found to be highly stable, and to self-assemble into 8- or 9-fold symmetrical propellers. These findings show that the β-propeller fold allows sufficient structural plasticity to permit a given blade to assemble different forms, a transition from even to odd changes in blade number, and provide a potential explanation for the wide diversity of repeat numbers observed in natural propeller proteins. DATABASE: Structural data are available in Protein Data Bank database under the accession numbers 6TJB, 6TJC, 6TJD, 6TJE, 6TJF, 6TJG, 6TJH and 6TJI.

Hybrid assemblies of a symmetric designer protein and polyoxometalates with matching symmetry

A symmetric designer protein forms hybrid complexes with different polyoxometalates and may serve as a building block for porous frameworks.

Engineered assembly of a protein–cucurbituril biohybrid

Additional Q7 binding sites drive protein aggregation in solution and statistical disorder in the crystalline biohybrid suggest new possibilities for protein-based materials.

Structure and engineering of tandem repeat lectins

Through their ability to bind complex glycoconjugates, lectins have unique specificity and potential for biomedical and biotechnological applications. In particular, lectins with short repeated peptides forming carbohydrate-binding domains are not only of high interest for understanding protein evolution but can also be used as scaffold for engineering novel receptors. Synthetic glycobiology now provides the tools for engineering the specificity of lectins as well as their structure, multivalency and topologies. This review focuses on the structure and diversity of two families of tandem-repeat lectins, that is, β-trefoils and β-propellers, demonstrated as the most promising scaffold for engineering novel lectins.

Structural diversity of oligomeric β-propellers with different numbers of identical blades

β-Propellers arise through the amplification of a supersecondary structure element called a blade. This process produces toroids of between four and twelve repeats, which are almost always arranged sequentially in a single polypeptide chain. We found that new propellers evolve continuously by amplification from single blades. We therefore investigated whether such nascent propellers can fold as homo-oligomers before they have been fully amplified within a single chain. One- to six-bladed building blocks derived from two seven-bladed WD40 propellers yielded stable homo-oligomers with six to nine blades, depending on the size of the building block. High-resolution structures for tetramers of two blades, trimers of three blades, and dimers of four and five blades, respectively, show structurally diverse propellers and include a novel fold, highlighting the inherent flexibility of the WD40 blade. Our data support the hypothesis that subdomain-sized fragments can provide structural versatility in the evolution of new proteins.

Positive multistate protein design

Motivation

Structure-based computational protein design (CPD) plays a critical role in advancing the field of protein engineering. Using an all-atom energy function, CPD tries to identify amino acid sequences that fold into a target structure and ultimately perform a desired function. The usual approach considers a single rigid backbone as a target, which ignores backbone flexibility. Multistate design (MSD) allows instead to consider several backbone states simultaneously, defining challenging computational problems.

Results

We introduce efficient reductions of positive MSD problems to Cost Function Networks with two different fitness definitions and implement them in the Pompd (Positive Multistate Protein design) software. Pompd is able to identify guaranteed optimal sequences of positive multistate full protein redesign problems and exhaustively enumerate suboptimal sequences close to the MSD optimum. Applied to nuclear magnetic resonance and back-rubbed X-ray structures, we observe that the average energy fitness provides the best sequence recovery. Our method outperforms state-of-the-art guaranteed computational design approaches by orders of magnitudes and can solve MSD problems with sizes previously unreachable with guaranteed algorithms.

Availability and implementation

https://forgemia.inra.fr/thomas.schiex/pompd as documented Open Source.

Supplementary information

Supplementary data are available at Bioinformatics online.

A structural homology approach for computational protein design with flexible backbone

Motivation

Structure-based Computational Protein design (CPD) plays a critical role in advancing the field of protein engineering. Using an all-atom energy function, CPD tries to identify amino acid sequences that fold into a target structure and ultimately perform a desired function. Energy functions remain however imperfect and injecting relevant information from known structures in the design process should lead to improved designs.

Results

We introduce Shades, a data-driven CPD method that exploits local structural environments in known protein structures together with energy to guide sequence design, while sampling side-chain and backbone conformations to accommodate mutations. Shades (Structural Homology Algorithm for protein DESign), is based on customized libraries of non-contiguous in-contact amino acid residue motifs. We have tested Shades on a public benchmark of 40 proteins selected from different protein families. When excluding homologous proteins, Shades achieved a protein sequence recovery of 30% and a protein sequence similarity of 46% on average, compared with the PFAM protein family of the target protein. When homologous structures were added, the wild-type sequence recovery rate achieved 93%.

Availability and implementation

Shades source code is available at https://bitbucket.org/satsumaimo/shades as a patch for Rosetta 3.8 with a curated protein structure database and ITEM library creation software.

Supplementary information

Supplementary data are available at Bioinformatics online.