Engineering of glycoside hydrolase family 7 cellobiohydrolases directed by natural diversity screening
Not Available
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Results for “protein design and engineering”
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A designed Copper Histidine-brace enzyme for oxidative depolymerization of polysaccharides as a model of lytic polysaccharide monooxygenase
The “Histidine-brace” (His-brace) copper-binding site, composed of Cu(His) 2 with a backbone amine, is found in metalloproteins with diverse functions. A primary example is lytic polysaccharide monooxygenase (LPMO), a class of enzymes that catalyze the oxidative depolymerization of polysaccharides, providing not only an energy source for native microorganisms but also a route to more effective industrial biomass conversion. Despite its importance, how the Cu His-brace site performs this unique and challenging oxidative depolymerization reaction remains to be understood. To answer this question, we have designed a biosynthetic model of LPMO by incorporating the Cu His-brace motif into azurin, an electron transfer protein. Spectroscopic studies, including ultraviolet-visible (UV–Vis) absorption and electron paramagnetic resonance, confirm copper binding at the designed His-brace site. Moreover, the designed protein is catalytically active towards both cellulose and starch, the native substrates of LPMO, generating degraded oligosaccharides with multiturnovers by C1 oxidation. It also performs oxidative cleavage of the model substrate 4-nitrophenyl-D-glucopyranoside, achieving a turnover number ~9% of that of a native LPMO assayed under identical conditions. This work presents a rationally designed artificial metalloenzyme that acts as a structural and functional mimic of LPMO, which provides a promising system for understanding the role of the Cu His-brace site in LPMO activity and potential application in polysaccharide degradation.
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Protein sequence design with a learned potential
The task of protein sequence design is central to nearly all rational protein engineering problems, and enormous effort has gone into the development of energy functions to guide design. Here, we investigate the capability of a deep neural network model to automate design of sequences onto protein backbones, having learned directly from crystal structure data and without any human-specified priors. The model generalizes to native topologies not seen during training, producing experimentally stable designs. We evaluate the generalizability of our method to a de novo TIM-barrel scaffold. The model produces novel sequences, and high-resolution crystal structures of two designs show excellent agreement with in silico models. Our findings demonstrate the tractability of an entirely learned method for protein sequence design.
59 BASIC BIOLOGICAL SCIENCES↗
De novo designed ice-binding proteins from twist-constrained helices
Attaining molecular-level control over solidification processes is a crucial aspect of materials science. To control ice formation, organisms have evolved bewildering arrays of ice-binding proteins (IBPs), but these have poorly understood structure–activity relationships. We propose that reverse engineering using de novo computational protein design can shed light on structure–activity relationships of IBPs. We hypothesized that the model alpha-helical winter flounder antifreeze protein uses an unusual undertwisting of its alpha-helix to align its putative ice-binding threonine residues in exactly the same direction. We test this hypothesis by designing a series of straight three-helix bundles with an ice-binding helix projecting threonines and two supporting helices constraining the twist of the ice-binding helix. Our findings show that ice-recrystallization inhibition by the designed proteins increases with the degree of designed undertwisting, thus validating our hypothesis, and opening up avenues for the computational design of IBPs.
Science & Technology - Other Topics↗
De novo protein design of photochemical reaction centers
Abstract Natural photosynthetic protein complexes capture sunlight to power the energetic catalysis that supports life on Earth. Yet these natural protein structures carry an evolutionary legacy of complexity and fragility that encumbers protein reengineering efforts and obfuscates the underlying design rules for light-driven charge separation. De novo development of a simplified photosynthetic reaction center protein can clarify practical engineering principles needed to build new enzymes for efficient solar-to-fuel energy conversion. Here, we report the rational design, X-ray crystal structure, and electron transfer activity of a multi-cofactor protein that incorporates essential elements of photosynthetic reaction centers. This highly stable, modular artificial protein framework can be reconstituted in vitro with interchangeable redox centers for nanometer-scale photochemical charge separation. Transient absorption spectroscopy demonstrates Photosystem II-like tyrosine and metal cluster oxidation, and we measure charge separation lifetimes exceeding 100 ms, ideal for light-activated catalysis. This de novo-designed reaction center builds upon engineering guidelines established for charge separation in earlier synthetic photochemical triads and modified natural proteins, and it shows how synthetic biology may lead to a new generation of genetically encoded, light-powered catalysts for solar fuel production.
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Monomer-scale design of functional protein polymers using consensus repeat sequences
Protein-based polymers possess chemically defined sequences that can encode diverse properties and functions into a new class of biopolymeric materials. However, sequence variation that emerges from evolution can obscure the sequence–function relationships of naturally derived polymers. One strategy to clarify these relationships is to identify common sequences between proteins with similar functions. These conserved sequences often emerge from repeat proteins, and “consensus repeat sequences” provide a convenient platform for systematic investigations of biopolymer sequence–property relationships. In this review, we highlight recent approaches to engineer tunable polymeric materials using monomer-scale design of consensus repeat proteins. Here, we explore established and emerging protein-based materials with mechanical resilience, thermodynamic phase behavior, chemical responsiveness, biomolecular transport, and hierarchical structure. Overall, recent advances in the monomer-scale design of repetitive protein polymers present exciting fundamental and translational opportunities for polymer scientists and engineers.
36 MATERIALS SCIENCE↗
In vitro continuous protein evolution empowered by machine learning and automation
Directed evolution has become one of the most successful and powerful tools for protein engineering. However, the efforts required for designing, constructing, and screening a large library of variants can be laborious, time-consuming, and costly. With the recent advent of machine learning (ML) in the directed evolution of proteins, researchers can now evaluate variants in silico and guide a more efficient directed evolution campaign. Furthermore, recent advancements in laboratory automation have enabled the rapid execution of long, complex experiments for high-throughput data acquisition in both industrial and academic settings, thus providing the means to collect a large quantity of data required to develop ML models for protein engineering. In this perspective, here we propose a closed-loop in vitro continuous protein evolution framework that leverages the best of both worlds, ML and automation, and provide a brief overview of the recent developments in the field.
59 BASIC BIOLOGICAL SCIENCES↗
Molecular Design Principles for Photosystem I-Based Biohybrid Solar Fuel Catalysts
Direct solar-to-chemical conversion offers a compelling route to clean, dispatchable energy. Photosystem I (PSI), an evolutionarily optimized light-driven oxidoreductase, can be repurposed for solar-fuel production by coupling its photochemistry to catalytic interfaces. However, the molecular determinants that govern productive electron transfer to abiotic catalysts remain poorly understood. Here, we present molecular structures of active PSI-Pt nanoparticle (PtNP) biohybrids that reveal how protein architecture controls catalyst access, binding geometry, and photocatalytic efficiency. Removal of stromal subunits exposes the electron transfer chain and enables PtNP binding proximal to the F X cluster, demonstrating that steric occlusion limits access to native acceptor regions in PSI. In contrast, in trimeric PSI, PtNPs bind at multiple sites per monomer, but only a subset are positioned within electron transfer distance of terminal cofactors, resulting in a heterogeneous population of productive and nonproductive configurations. Structural analyses and molecular dynamics simulations define the interface topology, electrostatics, and cofactor-to-nanoparticle distances that govern catalyst binding and electron transfer. These results establish that catalytic inefficiency arises not only from intrinsic electron transfer constraints but also from the distribution of binding geometries imposed by the protein scaffold. Together, these findings provide a molecular framework linking protein structure to biohybrid function and define design principles for engineering PSI-based solar fuel systems and protein-nanomaterial interfaces for light-driven catalysis.
biohybrid↗
Design and structure of two new protein cages illustrate successes and ongoing challenges in protein engineering
Abstract not provided
Cannon, Kevin A.↗
Computer-Aided Engineering of a Non-Phosphorylating Glyceraldehyde-3-Phosphate Dehydrogenase to Enable Cell-Free Biocatalysis
Not Available
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Combining chemistry and protein engineering for new-to-nature biocatalysis
Biocatalysis, the application of enzymes to solve synthetic problems of human import, has blossomed into a powerful technology for chemical innovation. In the past decade, a threefold partnership, where nature provides blueprints for enzymatic catalysis, chemists introduce innovative activity modes with abiological substrates, and protein engineers develop new tools and algorithms to tune and improve enzymatic function, has unveiled the frontier of new-to-nature enzyme catalysis. In this Perspective, we highlight examples of interdisciplinary studies, which have helped to expand the scope of biocatalysis, including concepts of enzymatic versatility explored through the lens of biomimicry, to achieve activities and selectivities beyond those currently possible with chemocatalysis. We indicate how modern tools, such as directed evolution, computational protein design and machine learning-based protein engineering methods, have already impacted and will continue to influence enzyme engineering for new abiological transformations. As a result, a sustained collaborative effort across disciplines is anticipated to spur further advances in biocatalysis in the coming years.
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Design of Large Stokes Shift Fluorescent Proteins Based on Excited State Proton Transfer of an Engin
Explore the source record for details and available documents.
Santos, Elizabeth M.↗
DeCOIL: Optimization of Degenerate Codon Libraries for Machine Learning-Assisted Protein Engineering
With advances in machine learning (ML)-assisted protein engineering, models based on data, biophysics, and natural evolution are being used to propose informed libraries of protein variants to explore. Synthesizing these libraries for experimental screens is a major bottleneck, as the cost of obtaining large numbers of exact gene sequences is often prohibitive. Degenerate codon (DC) libraries are a cost-effective alternative for generating combinatorial mutagenesis libraries where mutations are targeted to a handful of amino acid sites. However, existing computational methods to optimize DC libraries to include desired protein variants are not well suited to design libraries for ML-assisted protein engineering. To address these drawbacks, we present DEgenerate Codon Optimization for Informed Libraries (DeCOIL), a generalized method which directly optimizes DC libraries to be useful for protein engineering: to sample protein variants that are likely to have both high fitness and high diversity in the sequence search space. Using computational simulations and wet-lab experiments, we demonstrate that DeCOIL is effective across two specific case studies, with potential to be applied to many other use cases. DeCOIL offers several advantages over existing methods, as it is direct, easy-to-use, generalizable, and scalable. With accompanying software, DeCOIL can be readily implemented to generate desired informed libraries.
59 BASIC BIOLOGICAL SCIENCES↗
Attempts to develop an enzyme converting DHIV to KIV
Abstract Dihydroxy-acid dehydratase (DHAD) catalyzes the dehydration of R-2,3-dihydroxyisovalerate (DHIV) to 2-ketoisovalerate (KIV) using an Fe-S cluster as a cofactor, which is sensitive to oxidation and expensive to synthesize. In contrast, sugar acid dehydratases catalyze the same chemical reactions using a magnesium ion. Here, we attempted to substitute the high-cost DHAD with a cost-efficient engineered sugar acid dehydratase using computational protein design (CPD). First, we tried without success to modify the binding pocket of a sugar acid dehydratase to accommodate the smaller, more hydrophobic DHIV. Then, we used a chemically activated substrate analog to react with sugar acid dehydratases or other enolase superfamily enzymes. Mandelate racemase from Pseudomonas putida (PpManR) and the putative sugar acid dehydratase from Salmonella typhimurium (StPutD) showed beta-elimination activity towards chlorolactate (CLD). CPD combined with medium-throughput selection improved the PpManR kcat/KM for CLD by four-fold. However, these enzyme variants did not show dehydration activity towards DHIV. Lastly, assuming phosphorylation could also be a good activation mechanism, we found that mevalonate-3-kinase (M3K) from Picrophilus torridus (PtM3K) exhibited adenosine triphosphate (ATP) hydrolysis activity when mixed with DHIV, indicating phosphorylation activity towards DHIV. Engineering PpManR or StPutD to accept 3-phospho-DHIV as a substrate was performed, but no variants with the desired activity were obtained.
Oki, Kenji↗
Dual incorporation of non-canonical amino acids enables production of post-translationally modified selenoproteins
Post-translational modifications (PTMs) can occur on almost all amino acids in eukaryotes as a key mechanism for regulating protein function. The ability to study the role of these modifications in various biological processes requires techniques to modify proteins site-specifically. One strategy for this is genetic code expansion (GCE) in bacteria. The low frequency of post-translational modifications in bacteria makes it a preferred host to study whether the presence of a post-translational modification influences a protein’s function. Genetic code expansion employs orthogonal translation systems engineered to incorporate a modified amino acid at a designated protein position. Selenoproteins, proteins containing selenocysteine, are also known to be post-translationally modified. Selenoproteins have essential roles in oxidative stress, immune response, cell maintenance, and skeletal muscle regeneration. Their complicated biosynthesis mechanism has been a hurdle in our understanding of selenoprotein functions. As technologies for selenocysteine insertion have recently improved, we wanted to create a genetic system that would allow the study of post-translational modifications in selenoproteins. By combining genetic code expansion techniques and selenocysteine insertion technologies, we were able to recode stop codons for insertion of N ε -acetyl- l -lysine and selenocysteine, respectively, into multiple proteins. The specificity of these amino acids for their assigned position and the simplicity of reverting the modified amino acid via mutagenesis of the codon sequence demonstrates the capacity of this method to study selenoproteins and the role of their post-translational modifications. Moreover, the evidence that Sec insertion technology can be combined with genetic code expansion tools further expands the chemical biology applications.
59 BASIC BIOLOGICAL SCIENCES↗
Cryo-EM, Protein Engineering, and Simulation Enable the Development of Peptide Therapeutics against Acute Myeloid Leukemia
Cryogenic electron microscopy (cryo-EM) has emerged as a viable structural tool for molecular therapeutics development against human diseases. However, it remains a challenge to determine structures of proteins that are flexible and smaller than 30 kDa. The 11 kDa KIX domain of CREB-binding protein (CBP), a potential therapeutic target for acute myeloid leukemia and other cancers, is a protein which has defied structure-based inhibitor design. Here, we develop an experimental approach to overcome the size limitation by engineering a protein double-shell to sandwich the KIX domain between apoferritin as the inner shell and maltose-binding protein as the outer shell. To assist homogeneous orientations of the target, disulfide bonds are introduced at the target–apoferritin interface, resulting in a cryo-EM structure at 2.6 Å resolution. We used molecular dynamics simulations to design peptides that block the interaction of the KIX domain of CBP with the intrinsically disordered pKID domain of CREB. The double-shell design allows for fluorescence polarization assays confirming the binding between the KIX domain in the double-shell and these interacting peptides. Further cryo-EM analysis reveals a helix–helix interaction between a single KIX helix and the best peptide, providing a possible strategy for developments of next-generation inhibitors.
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Computational design of highly signalling-active membrane receptors through solvent-mediated allosteric networks
Abstract Protein catalysis and allostery require the atomic-level orchestration and motion of residues and ligand, solvent and protein effector molecules. However, the ability to design protein activity through precise protein–solvent cooperative interactions has not yet been demonstrated. Here we report the design of 14 membrane receptors that catalyse G protein nucleotide exchange through diverse engineered allosteric pathways mediated by cooperative networks of intraprotein, protein–ligand and –solvent molecule interactions. Consistent with predictions, the designed protein activities correlated well with the level of plasticity of the networks at flexible transmembrane helical interfaces. Several designs displayed considerably enhanced thermostability and activity compared with related natural receptors. The most stable and active variant crystallized in an unforeseen signalling-active conformation, in excellent agreement with the design models. The allosteric network topologies of the best designs bear limited similarity to those of natural receptors and reveal an allosteric interaction space larger than previously inferred from natural proteins. The approach should prove useful for engineering proteins with novel complex protein binding, catalytic and signalling activities.
Chemistry↗
Engineered mRNA–ribosome fusions for facile biosynthesis of selenoproteins
Ribosomes are often used in synthetic biology as a tool to produce desired proteins with enhanced properties or entirely new functions. However, repurposing ribosomes for producing designer proteins is challenging due to the limited number of engineering solutions available to alter the natural activity of these enzymes. In this study, we advance ribosome engineering by describing a novel strategy based on functional fusions of ribosomal RNA (rRNA) with messenger RNA (mRNA). Specifically, we create an mRNA–ribosome fusion called RiboU, where the 16S rRNA is covalently attached to selenocysteine insertion sequence (SECIS), a regulatory RNA element found in mRNAs encoding selenoproteins. When SECIS sequences are present in natural mRNAs, they instruct ribosomes to decode UGA codons as selenocysteine (Sec, U) codons instead of interpreting them as stop codons. This enables ribosomes to insert Sec into the growing polypeptide chain at the appropriate site. Our work demonstrates that the SECIS sequence maintains its functionality even when inserted into the ribosome structure. As a result, the engineered ribosomes RiboU interpret UAG codons as Sec codons, allowing easy and site-specific insertion of Sec in a protein of interest with no further modification to the natural machinery of protein synthesis. To validate this approach, we use RiboU ribosomes to produce three functional target selenoproteins in Escherichia coli by site-specifically inserting Sec into the proteins’ active sites. Overall, our work demonstrates the feasibility of creating functional mRNA–rRNA fusions as a strategy for ribosome engineering, providing a novel tool for producing Sec-containing proteins in live bacterial cells.
59 BASIC BIOLOGICAL SCIENCES↗