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Controlled degradation of proteins is necessary for ensuring their abundance and sustaining a healthy and accurately functioning proteome. One of the degradation routes involves the uncapped 20S proteasome, which cleaves proteins with a partially unfolded region, including those that are damaged or contain intrinsically disordered regions. This degradation route is tightly controlled by a recently discovered family of proteins named Catalytic Core Regulators (CCRs). Here, we show that CCRs function through an allosteric mechanism, coupling the physical binding of the PSMB4 β-subunit with attenuation of the complex's three proteolytic activities. In addition, by dissecting the structural properties that are required for CCR-like function, we could recapitulate this activity using a designed protein that is half the size of natural CCRs. These data uncover an allosteric path that does not involve the proteasome's enzymatic subunits but rather propagates through the non-catalytic subunit PSMB4. This way of 20S proteasome-specific attenuation opens avenues for decoupling the 20S and 26S proteasome degradation pathways as well as for developing selective 20S proteasome inhibitors. A family of regulators named Catalytic Core Regulators (CCRs) oversees the function of the 20S proteasome. Here, the authors show that CCRs function through an allosteric mechanism, coupling the physical binding of the PSMB4 β-subunit with attenuation of the proteasome three proteolytic activities. [ABSTRACT FROM AUTHOR]

Mutations in a protein active site can lead to dramatic and useful changes in protein activity. The active site, however, is sensitive to mutations due to a high density of molecular interactions, substantially reducing the likelihood of obtaining functional multipoint mutants. We introduce an atomistic and machine-learning-based approach, called high-throughput Functional Libraries (htFuncLib), that designs a sequence space in which mutations form low-energy combinations that mitigate the risk of incompatible interactions. We apply htFuncLib to the GFP chromophore-binding pocket, and, using fluorescence readout, recover >16,000 unique designs encoding as many as eight active-site mutations. Many designs exhibit substantial and useful diversity in functional thermostability (up to 96 °C), fluorescence lifetime, and quantum yield. By eliminating incompatible active-site mutations, htFuncLib generates a large diversity of functional sequences. We envision that htFuncLib will be used in one-shot optimization of activity in enzymes, binders, and other proteins. Mutations in a protein active site can alter function in useful ways, but the active site is sensitive to changes. Here the authors present a general strategy to design combinatorial mutation libraries. Applied to GFP, the authors isolate thousands of fluorescent designs that exhibit large and useful changes in spectral properties. [ABSTRACT FROM AUTHOR]

Until now, membrane-protein stabilization has relied on iterations of mutations and screening. We now validate a one-step algorithm, mPROSS, for stabilizing membrane proteins directly from an AlphaFold2 model structure. Applied to the lipid-generating enzyme, ceramide synthase, 37 designed mutations lead to a more stable form of human CerS2. Together with molecular dynamics simulations, we propose a pathway by which substrates might be delivered to the ceramide synthases. Membrane proteins are involved in many critical cellular pathways. Here, authors use a combination of structural predictions, an algorithm for stabilizing membrane proteins, and molecular dynamics to reveal a putative mechanism for the action of ceramide synthases. [ABSTRACT FROM AUTHOR]

Imaging of gene-expression patterns in live animals is difficult to achieve with fluorescent proteins because tissues are opaque to visible light. Imaging of transgene expression with magnetic resonance imaging (MRI), which penetrates to deep tissues, has been limited by single reporter visualization capabilities. Moreover, the low-throughput capacity of MRI limits large-scale mutagenesis strategies to improve existing reporters. Here we develop an MRI system, called GeneREFORM, comprising orthogonal reporters for two-color imaging of transgene expression in deep tissues. Starting from two promiscuous deoxyribonucleoside kinases, we computationally designed highly active, orthogonal enzymes ('reporter genes') that specifically phosphorylate two MRI-detectable synthetic deoxyribonucleosides ('reporter probes'). Systemically administered reporter probes exclusively accumulate in cells expressing the designed reporter genes, and their distribution is displayed as pseudo-colored MRI maps based on dynamic proton exchange for noninvasive visualization of transgene expression. We envision that future extensions of GeneREFORM will pave the way to multiplexed deep-tissue mapping of gene expression in live animals. MRI detection of transgene expression in animals is expanded to two colors. [ABSTRACT FROM AUTHOR]

The ability to alter the genomes of living cells is key to understanding how genes influence the functions of organisms and will be critical to modify living systems for useful purposes. However, this promise has long been limited by the technical challenges involved in genetic engineering. Recent advances in gene editing have bypassed some of these challenges but they are still far from ideal. Here we use FuncLib to computationally design Cas9 enzymes with substantially higher donor-independent editing activities. We use genetic circuits linked to cell survival in yeast to quantify Cas9 activity and discover synergistic interactions between engineered regions. These hyperactive Cas9 variants function efficiently in mammalian cells and introduce larger and more diverse pools of insertions and deletions into targeted genomic regions, providing tools to enhance and expand the possible applications of CRISPR-based gene editing. The ability to alter the genomes of living cells is key to understanding how genes influence the functions of organisms and will be critical to modify living systems for useful purposes. Here, the authors use computational design to discover Cas9 enzymes with increased activity. [ABSTRACT FROM AUTHOR]

Lassa virus (LASV) is a human pathogen, causing substantial morbidity and mortality1,2. Similar to other Arenaviridae, it presents a class-I spike complex on its surface that facilitates cell entry. The virus’s cellular receptor is matriglycan, a linear carbohydrate that is present on α-dystroglycan3,4, but the molecular mechanism that LASV uses to recognize this glycan is unknown. In addition, LASV and other arenaviruses have a unique signal peptide that forms an integral and functionally important part of the mature spike5–8; yet the structure, function and topology of the signal peptide in the membrane remain uncertain9–11. Here we solve the structure of a complete native LASV spike complex, finding that the signal peptide crosses the membrane once and that its amino terminus is located in the extracellular region. Together with a double-sided domain-switching mechanism, the signal peptide helps to stabilize the spike complex in its native conformation. This structure reveals that the LASV spike complex is preloaded with matriglycan, suggesting the mechanism of binding and rationalizing receptor recognition by α-dystroglycan-tropic arenaviruses. This discovery further informs us about the mechanism of viral egress and may facilitate the rational design of novel therapeutics that exploit this binding site.The structure of the complete native spike complex of Lassa virus reveals its membrane topology and the matriglycan-depended recognition of its α-dystroglycan cellular receptor. [ABSTRACT FROM AUTHOR]

Protein networks in all organisms comprise homologous interacting pairs. In these networks, some proteins are specific, interacting with one or a few binding partners, whereas others are multispecific and bind a range of targets. We describe an algorithm that starts from an interacting pair and designs dozens of new pairs with diverse backbone conformations at the binding site as well as new binding orientations and sequences. Applied to a high-affinity bacterial pair, the algorithm results in 18 new ones, with cognate affinities from pico- to micromolar. Three pairs exhibit 3-5 orders of magnitude switch in specificity relative to the wild type, whereas others are multispecific, collectively forming a protein-interaction network. Crystallographic analysis confirms design accuracy, including in new backbones and polar interactions. Preorganized polar interaction networks are responsible for high specificity, thus defining design principles that can be applied to program synthetic cellular interaction networks of desired affinity and specificity. [ABSTRACT FROM AUTHOR]

Automated design of enzymes with wild-type-like catalytic properties has been a long- standing but elusive goal. Here, we present a general, automated method for enzyme design through combinatorial backbone assembly. Starting from a set of homologous yet structurally diverse enzyme structures, the method assembles new backbone combinations and uses Rosetta to optimize the amino acid sequence, while conserving key catalytic residues. We apply this method to two unrelated enzyme families with TIM-barrel folds, glycoside hydrolase 10 (GH10) xylanases and phosphotriesterase-like lactonases (PLLs), designing 43 and 34 proteins, respectively. Twenty-one GH10 and seven PLL designs are active, including designs derived from templates with <25% sequence identity. Moreover, four designs are as active as natural enzymes in these families. Atomic accuracy in a high-activity GH10 design is further confirmed by crystallographic analysis. Thus, combinatorial-backbone assembly and design may be used to generate stable, active, and structurally diverse enzymes with altered selectivity or activity. [ABSTRACT FROM AUTHOR]

We show that comprehensive sequence-function maps obtained by deep sequencing can be used to reprogram interaction specificity and to leapfrog over bottlenecks in affinity maturation by combining many individually small contributions not detectable in conventional approaches. We use this approach to optimize two computationally designed inhibitors against H1N1 influenza hemagglutinin and, in both cases, obtain variants with subnanomolar binding affinity. The most potent of these, a 51-residue protein, is broadly cross-reactive against all influenza group 1 hemagglutinins, including human H2, and neutralizes H1N1 viruses with a potency that rivals that of several human monoclonal antibodies, demonstrating that computational design followed by comprehensive energy landscape mapping can generate proteins with potential therapeutic utility. [ABSTRACT FROM AUTHOR]

We present a large-scale approach to investigate the functional consequences of sequence variation in a protein. The approach entails the display of hundreds of thousands of protein variants, moderate selection for activity and high-throughput DNA sequencing to quantify the performance of each variant. Using this strategy, we tracked the performance of >600,000 variants of a human WW domain after three and six rounds of selection by phage display for binding to its peptide ligand. Binding properties of these variants defined a high-resolution map of mutational preference across the WW domain; each position had unique features that could not be captured by a few representative mutations. Our approach could be applied to many in vitro or in vivo protein assays, providing a general means for understanding how protein function relates to sequence. [ABSTRACT FROM AUTHOR]

Characterization of overexpressed proteins is essential for assessing their quality, and providing input for iterative redesign and optimization. This process is typically carried out following purification procedures that require pronounced cost of time and labor. Therefore, quality assessment of recombinant proteins with no prior purification offers a major advantage. Here, we report a native mass spectrometry method that enables characterization of overproduced proteins directly from culture media. Properties such as solubility, molecular weight, folding, assembly state, overall structure, post-translational modifications and binding to relevant biomolecules are immediately revealed. We show the applicability of the method for in-depth characterization of secreted recombinant proteins from eukaryotic systems such as yeast, insect, and human cells. This method, which can be readily extended to high-throughput analysis, considerably shortens the time gap between protein production and characterization, and is particularly suitable for characterizing engineered and mutated proteins, and optimizing yield and quality of overexpressed proteins. Ben-Nissan et al. present a rapid mass-spectrometry method for characterizing recombinant proteins directly from culture media. They test their method on secreted recombinant proteins from yeast, insect, and human cells, revealing solubility, molecular weight, structure, ligand binding and post-translational modifications. [ABSTRACT FROM AUTHOR]