Structure of orthoreovirus RNA chaperone σNS, a component of viral replication factories.

The mammalian orthoreovirus (reovirus) σNS protein is required for formation of replication compartments that support viral genome replication and capsid assembly. Despite its functional importance, a mechanistic understanding of σNS is lacking. We conducted structural and biochemical analyses of a σNS mutant that forms dimers instead of the higher-order oligomers formed by wildtype (WT) σNS. The crystal structure shows that dimers interact with each other using N-terminal arms to form a helical assembly resembling WT σNS filaments in complex with RNA observed using cryo-EM. The interior of the helical assembly is of appropriate diameter to bind RNA. The helical assembly is disrupted by bile acids, which bind to the same site as the N-terminal arm. This finding suggests that the N-terminal arm functions in conferring context-dependent oligomeric states of σNS, which is supported by the structure of σNS lacking an N-terminal arm. We further observed that σNS has RNA chaperone activity likely essential for presenting mRNA to the viral polymerase for genome replication. This activity is reduced by bile acids and abolished by N-terminal arm deletion, suggesting that the activity requires formation of σNS oligomers. Our studies provide structural and mechanistic insights into the function of σNS in reovirus replication.

Blueprinting extendable nanomaterials with standardized protein blocks.

A wooden house frame consists of many different lumber pieces, but because of the regularity of these building blocks, the structure can be designed using straightforward geometrical principles. The design of multicomponent protein assemblies, in comparison, has been much more complex, largely owing to the irregular shapes of protein structures1. Here we describe extendable linear, curved and angled protein building blocks, as well as inter-block interactions, that conform to specified geometric standards; assemblies designed using these blocks inherit their extendability and regular interaction surfaces, enabling them to be expanded or contracted by varying the number of modules, and reinforced with secondary struts. Using X-ray crystallography and electron microscopy, we validate nanomaterial designs ranging from simple polygonal and circular oligomers that can be concentrically nested, up to large polyhedral nanocages and unbounded straight 'train track' assemblies with reconfigurable sizes and geometries that can be readily blueprinted. Because of the complexity of protein structures and sequence-structure relationships, it has not previously been possible to build up large protein assemblies by deliberate placement of protein backbones onto a blank three-dimensional canvas; the simplicity and geometric regularity of our design platform now enables construction of protein nanomaterials according to 'back of an envelope' architectural blueprints.

Network of epistatic interactions in an enzyme active site revealed by large-scale deep mutational scanning.

Cooperative interactions between amino acids are critical for protein function. A genetic reflection of cooperativity is epistasis, which is when a change in the amino acid at one position changes the sequence requirements at another position. To assess epistasis within an enzyme active site, we utilized CTX-M ß-lactamase as a model system. CTX-M hydrolyzes ß-lactam antibiotics to provide antibiotic resistance, allowing a simple functional selection for rapid sorting of modified enzymes. We created all pairwise mutations across 17 active site positions in the ß-lactamase enzyme and quantitated the function of variants against two ß-lactam antibiotics using next-generation sequencing. Context-dependent sequence requirements were determined by comparing the antibiotic resistance function of double mutations across the CTX-M active site to their predicted function based on the constituent single mutations, revealing both positive epistasis (synergistic interactions) and negative epistasis (antagonistic interactions) between amino acid substitutions. The resulting trends demonstrate that positive epistasis is present throughout the active site, that epistasis between residues is mediated through substrate interactions, and that residues more tolerant to substitutions serve as generic compensators which are responsible for many cases of positive epistasis. Additionally, we show that a key catalytic residue (Glu166) is amenable to compensatory mutations, and we characterize one such double mutant (E166Y/N170G) that acts by an altered catalytic mechanism. These findings shed light on the unique biochemical factors that drive epistasis within an enzyme active site and will inform enzyme engineering efforts by bridging the gap between amino acid sequence and catalytic function.

Rapid and automated design of two-component protein nanomaterials using ProteinMPNN.

The design of protein-protein interfaces using physics-based design methods such as Rosetta requires substantial computational resources and manual refinement by expert structural biologists. Deep learning methods promise to simplify protein-protein interface design and enable its application to a wide variety of problems by researchers from various scientific disciplines. Here, we test the ability of a deep learning method for protein sequence design, ProteinMPNN, to design two-component tetrahedral protein nanomaterials and benchmark its performance against Rosetta. ProteinMPNN had a similar success rate to Rosetta, yielding 13 new experimentally confirmed assemblies, but required orders of magnitude less computation and no manual refinement. The interfaces designed by ProteinMPNN were substantially more polar than those designed by Rosetta, which facilitated in vitro assembly of the designed nanomaterials from independently purified components. Crystal structures of several of the assemblies confirmed the accuracy of the design method at high resolution. Our results showcase the potential of deep learning-based methods to unlock the widespread application of designed protein-protein interfaces and self-assembling protein nanomaterials in biotechnology.

Targeting prostate tumor low-molecular weight tyrosine phosphatase for oxidation-sensitizing therapy.

Protein tyrosine phosphatases (PTPs) play major roles in cancer and are emerging as therapeutic targets. Recent reports suggest low-molecular weight PTP (LMPTP)-encoded by the ACP1 gene-is overexpressed in prostate tumors. We found ACP1 up-regulated in human prostate tumors and ACP1 expression inversely correlated with overall survival. Using CRISPR-Cas9-generated LMPTP knockout C4-2B and MyC-CaP cells, we identified LMPTP as a critical promoter of prostate cancer (PCa) growth and bone metastasis. Through metabolomics, we found that LMPTP promotes PCa cell glutathione synthesis by dephosphorylating glutathione synthetase on inhibitory Tyr270. PCa cells lacking LMPTP showed reduced glutathione, enhanced activation of eukaryotic initiation factor 2-mediated stress response, and enhanced reactive oxygen species after exposure to taxane drugs. LMPTP inhibition slowed primary and bone metastatic prostate tumor growth in mice. These findings reveal a role for LMPTP as a critical promoter of PCa growth and metastasis and validate LMPTP inhibition as a therapeutic strategy for treating PCa through sensitization to oxidative stress.

Improving Protein Expression, Stability, and Function with ProteinMPNN.

Natural proteins are highly optimized for function but are often difficult to produce at a scale suitable for biotechnological applications due to poor expression in heterologous systems, limited solubility, and sensitivity to temperature. Thus, a general method that improves the physical properties of native proteins while maintaining function could have wide utility for protein-based technologies. Here, we show that the deep neural network ProteinMPNN, together with evolutionary and structural information, provides a route to increasing protein expression, stability, and function. For both myoglobin and tobacco etch virus (TEV) protease, we generated designs with improved expression, elevated melting temperatures, and improved function. For TEV protease, we identified multiple designs with improved catalytic activity as compared to the parent sequence and previously reported TEV variants. Our approach should be broadly useful for improving the expression, stability, and function of biotechnologically important proteins.

Structural Studies of Inhibitors with Clinically Relevant Influenza Endonuclease Variants.

Vital to the treatment of influenza is the use of antivirals such as Oseltamivir (Tamiflu) and Zanamivir (Relenza); however, antiviral resistance is becoming an increasing problem for these therapeutics. The RNA-dependent RNA polymerase acidic N-terminal (PAN) endonuclease, a critical component of influenza viral replication machinery, is an antiviral target that was recently validated with the approval of Baloxavir Marboxil (BXM). Despite its clinical success, BXM has demonstrated susceptibility to resistance mutations, specifically the I38T, E23K, and A36 V mutants of PAN. To better understand the effects of these mutations on BXM resistance and improve the design of more robust therapeutics, this study examines key differences in protein-inhibitor interactions with two inhibitors and the I38T, E23K, and A36 V mutants. Differences in inhibitor binding were evaluated by measuring changes in binding to PAN using two biophysical methods. The binding mode of two distinct inhibitors was determined crystallographically with both wild-type and mutant forms of PAN. Collectively, these studies give some insight into the mechanism of antiviral resistance of these mutants.

Klebsiella pneumoniae carbapenemase variant 44 acquires ceftazidime-avibactam resistance by altering the conformation of active-site loops.

Klebsiella pneumoniae carbapenemase 2 (KPC-2) is an important source of drug resistance as it can hydrolyze and inactivate virtually all ß-lactam antibiotics. KPC-2 is potently inhibited by avibactam via formation of a reversible carbamyl linkage of the inhibitor with the catalytic serine of the enzyme. However, the use of avibactam in combination with ceftazidime (CAZ-AVI) has led to the emergence of CAZ-AVI-resistant variants of KPC-2 in clinical settings. One such variant, KPC-44, bears a 15 amino acid duplication in one of the active-site loops (270-loop). Here, we show that the KPC-44 variant exhibits higher catalytic efficiency in hydrolyzing ceftazidime, lower efficiency toward imipenem and meropenem, and a similar efficiency in hydrolyzing ampicillin, than the WT KPC-2 enzyme. In addition, the KPC-44 variant enzyme exhibits 12-fold lower AVI carbamylation efficiency than the KPC-2 enzyme. An X-ray crystal structure of KPC-44 showed that the 15 amino acid duplication results in an extended and partially disordered 270-loop and also changes the conformation of the adjacent 240-loop, which in turn has altered interactions with the active-site omega loop. Furthermore, a structure of KPC-44 with avibactam revealed that formation of the covalent complex results in further disorder in the 270-loop, suggesting that rearrangement of the 270-loop of KPC-44 facilitates AVI carbamylation. These results suggest that the duplication of 15 amino acids in the KPC-44 enzyme leads to resistance to CAZ-AVI by modulating the stability and conformation of the 270-, 240-, and omega-loops.

Exploiting the Carboxylate-Binding Pocket of ß-Lactamase Enzymes Using a Focused DNA-Encoded Chemical Library.

ß-Lactamase enzymes hydrolyze and thereby provide bacterial resistance to the important ß-lactam class of antibiotics. The OXA-48 and NDM-1 ß-lactamases cause resistance to the last-resort ß-lactams, carbapenems, leading to a serious public health threat. Here, we utilized DNA-encoded chemical library (DECL) technology to discover novel ß-lactamase inhibitors. We exploited the ß-lactamase enzyme-substrate binding interactions and created a DECL targeting the carboxylate-binding pocket present in all ß-lactamases. A library of 106 compounds, each containing a carboxylic acid or a tetrazole as an enzyme recognition element, was designed, constructed, and used to identify OXA-48 and NDM-1 inhibitors with micromolar to nanomolar potency. Further optimization led to NDM-1 inhibitors with increased potencies and biological activities. This work demonstrates that the carboxylate-binding pocket-targeting DECL, designed based on substrate binding information, aids in inhibitor identification and led to the discovery of novel non-ß-lactam pharmacophores for the development of ß-lactamase inhibitors for enzymes of different structural and mechanistic classes.

A single nanobody neutralizes multiple epochally evolving human noroviruses by modulating capsid plasticity.

Acute gastroenteritis caused by human noroviruses (HuNoVs) is a significant global health and economic burden and is without licensed vaccines or antiviral drugs. The GII.4 HuNoV causes most epidemics worldwide. This virus undergoes epochal evolution with periodic emergence of variants with new antigenic profiles and altered specificity for histo-blood group antigens (HBGA), the determinants of cell attachment and susceptibility, hampering the development of immunotherapeutics. Here, we show that a llama-derived nanobody M4 neutralizes multiple GII.4 variants with high potency in human intestinal enteroids. The crystal structure of M4 complexed with the protruding domain of the GII.4 capsid protein VP1 revealed a conserved epitope, away from the HBGA binding site, fully accessible only when VP1 transitions to a "raised" conformation in the capsid. Together with dynamic light scattering and electron microscopy of the GII.4 VLPs, our studies suggest a mechanism in which M4 accesses the epitope by altering the conformational dynamics of the capsid and triggering its disassembly to neutralize GII.4 infection.

Accurate computational design of three-dimensional protein crystals.

Protein crystallization plays a central role in structural biology. Despite this, the process of crystallization remains poorly understood and highly empirical, with crystal contacts, lattice packing arrangements and space group preferences being largely unpredictable. Programming protein crystallization through precisely engineered side-chain-side-chain interactions across protein-protein interfaces is an outstanding challenge. Here we develop a general computational approach for designing three-dimensional protein crystals with prespecified lattice architectures at atomic accuracy that hierarchically constrains the overall number of degrees of freedom of the system. We design three pairs of oligomers that can be individually purified, and upon mixing, spontaneously self-assemble into >100 µm three-dimensional crystals. The structures of these crystals are nearly identical to the computational design models, closely corresponding in both overall architecture and the specific protein-protein interactions. The dimensions of the crystal unit cell can be systematically redesigned while retaining the space group symmetry and overall architecture, and the crystals are extremely porous and highly stable. Our approach enables the computational design of protein crystals with high accuracy, and the designed protein crystals, which have both structural and assembly information encoded in their primary sequences, provide a powerful platform for biological materials engineering.

Identification of potent and selective N-myristoyltransferase inhibitors of Plasmodium vivax liver stage hypnozoites and schizonts.

Drugs targeting multiple stages of the Plasmodium vivax life cycle are needed to reduce the health and economic burdens caused by malaria worldwide. N-myristoyltransferase (NMT) is an essential eukaryotic enzyme and a validated drug target for combating malaria. However, previous PvNMT inhibitors have failed due to their low selectivity over human NMTs. Herein, we apply a structure-guided hybridization approach combining chemical moieties of previously reported NMT inhibitors to develop the next generation of PvNMT inhibitors. A high-resolution crystal structure of PvNMT bound to a representative selective hybrid compound reveals a unique binding site architecture that includes a selective conformation of a key tyrosine residue. The hybridized compounds significantly decrease P. falciparum blood-stage parasite load and consistently exhibit dose-dependent inhibition of P. vivax liver stage schizonts and hypnozoites. Our data demonstrate that hybridized NMT inhibitors can be multistage antimalarials, targeting dormant and developing forms of liver and blood stage.

Precisely patterned nanofibres made from extendable protein multiplexes.

Molecular systems with coincident cyclic and superhelical symmetry axes have considerable advantages for materials design as they can be readily lengthened or shortened by changing the length of the constituent monomers. Among proteins, alpha-helical coiled coils have such symmetric, extendable architectures, but are limited by the relatively fixed geometry and flexibility of the helical protomers. Here we describe a systematic approach to generating modular and rigid repeat protein oligomers with coincident C2 to C8 and superhelical symmetry axes that can be readily extended by repeat propagation. From these building blocks, we demonstrate that a wide range of unbounded fibres can be systematically designed by introducing hydrophilic surface patches that force staggering of the monomers; the geometry of such fibres can be precisely tuned by varying the number of repeat units in the monomer and the placement of the hydrophilic patches.

Identification of and Structural Insights into Hit Compounds Targeting N-Myristoyltransferase for Cryptosporidium Drug Development.

Each year, approximately 50,000 children under 5 die as a result of diarrhea caused by Cryptosporidium parvum, a protozoan parasite. There are currently no effective drugs or vaccines available to cure or prevent Cryptosporidium infection, and there are limited tools for identifying and validating targets for drug or vaccine development. We previously reported a high throughput screening (HTS) of a large compound library against Plasmodium N-myristoyltransferase (NMT), a validated drug target in multiple protozoan parasite species. To identify molecules that could be effective against Cryptosporidium, we counter-screened hits from the Plasmodium NMT HTS against Cryptosporidium NMT. We identified two potential hit compounds and validated them against CpNMT to determine if NMT might be an attractive drug target also for Cryptosporidium. We tested the compounds against Cryptosporidium using both cell-based and NMT enzymatic assays. We then determined the crystal structure of CpNMT bound to Myristoyl-Coenzyme A (MyrCoA) and structures of ternary complexes with MyrCoA and the hit compounds to identify the ligand binding modes. The binding site architectures display different conformational states in the presence of the two inhibitors and provide a basis for rational design of selective inhibitors.

De novo design of monomeric helical bundles for pH-controlled membrane lysis.

Targeted intracellular delivery via receptor-mediated endocytosis requires the delivered cargo to escape the endosome to prevent lysosomal degradation. This can in principle be achieved by membrane lysis tightly restricted to endosomal membranes upon internalization to avoid general membrane insertion and lysis. Here, we describe the design of small monomeric proteins with buried histidine containing pH-responsive hydrogen bond networks and membrane permeating amphipathic helices. Of the 30 designs that were experimentally tested, all expressed in Escherichia coli, 13 were monomeric with the expected secondary structure, and 4 designs disrupted artificial liposomes in a pH-dependent manner. Mutational analysis showed that the buried histidine hydrogen bond networks mediate pH-responsiveness and control lysis of model membranes within a very narrow range of pH (6.0-5.5) with almost no lysis occurring at neutral pH. These tightly controlled lytic monomers could help mediate endosomal escape in designed targeted delivery platforms.

Design of stimulus-responsive two-state hinge proteins.

In nature, proteins that switch between two conformations in response to environmental stimuli structurally transduce biochemical information in a manner analogous to how transistors control information flow in computing devices. Designing proteins with two distinct but fully structured conformations is a challenge for protein design as it requires sculpting an energy landscape with two distinct minima. Here we describe the design of "hinge" proteins that populate one designed state in the absence of ligand and a second designed state in the presence of ligand. X-ray crystallography, electron microscopy, double electron-electron resonance spectroscopy, and binding measurements demonstrate that despite the significant structural differences the two states are designed with atomic level accuracy and that the conformational and binding equilibria are closely coupled.

Rapid and automated design of two-component protein nanomaterials using ProteinMPNN.

The design of novel protein-protein interfaces using physics-based design methods such as Rosetta requires substantial computational resources and manual refinement by expert structural biologists. A new generation of deep learning methods promises to simplify protein-protein interface design and enable its application to a wide variety of problems by researchers from various scientific disciplines. Here we test the ability of a deep learning method for protein sequence design, ProteinMPNN, to design two-component tetrahedral protein nanomaterials and benchmark its performance against Rosetta. ProteinMPNN had a similar success rate to Rosetta, yielding 13 new experimentally confirmed assemblies, but required orders of magnitude less computation and no manual refinement. The interfaces designed by ProteinMPNN were substantially more polar than those designed by Rosetta, which facilitated in vitro assembly of the designed nanomaterials from independently purified components. Crystal structures of several of the assemblies confirmed the accuracy of the design method at high resolution. Our results showcase the potential of deep learning-based methods to unlock the widespread application of designed protein-protein interfaces and self-assembling protein nanomaterials in biotechnology.

Structure of Orthoreovirus RNA Chaperone σNS, a Component of Viral Replication Factories.

The reovirus σNS RNA-binding protein is required for formation of intracellular compartments during viral infection that support viral genome replication and capsid assembly. Despite its functional importance, a mechanistic understanding of σNS is lacking. We conducted structural and biochemical analyses of an R6A mutant of σNS that forms dimers instead of the higher-order oligomers formed by wildtype (WT) σNS. The crystal structure of selenomethionine-substituted σNS-R6A reveals that the mutant protein forms a stable antiparallel dimer, with each subunit having a well-folded central core and a projecting N-terminal arm. The dimers interact with each other by inserting the N-terminal arms into a hydrophobic pocket of the neighboring dimers on either side to form a helical assembly that resembles filaments of WT σNS in complex with RNA observed using cryo-EM. The interior of the crystallographic helical assembly is positively charged and of appropriate diameter to bind RNA. The helical assembly is disrupted by bile acids, which bind to the same hydrophobic pocket as the N-terminal arm, as demonstrated in the crystal structure of σNS-R6A in complex with bile acid, suggesting that the N-terminal arm functions in conferring context-dependent oligomeric states of σNS. This idea is supported by the structure of σNS lacking the N-terminal arm. We discovered that σNS displays RNA helix destabilizing and annealing activities, likely essential for presenting mRNA to the viral RNA-dependent RNA polymerase for genome replication. The RNA chaperone activity is reduced by bile acids and abolished by N-terminal arm deletion, suggesting that the activity requires formation of σNS oligomers. Our studies provide structural and mechanistic insights into the function of σNS in reovirus replication.

DNA-encoded chemical libraries yield non-covalent and non-peptidic SARS-CoV-2 main protease inhibitors.

The development of SARS-CoV-2 main protease (Mpro) inhibitors for the treatment of COVID-19 has mostly benefitted from X-ray structures and preexisting knowledge of inhibitors; however, an efficient method to generate Mpro inhibitors, which circumvents such information would be advantageous. As an alternative approach, we show here that DNA-encoded chemistry technology (DEC-Tec) can be used to discover inhibitors of Mpro. An affinity selection of a 4-billion-membered DNA-encoded chemical library (DECL) using Mpro as bait produces novel non-covalent and non-peptide-based small molecule inhibitors of Mpro with low nanomolar Ki values. Furthermore, these compounds demonstrate efficacy against mutant forms of Mpro that have shown resistance to the standard-of-care drug nirmatrelvir. Overall, this work demonstrates that DEC-Tec can efficiently generate novel and potent inhibitors without preliminary chemical or structural information.

Blueprinting expandable nanomaterials with standardized protein building blocks.

A wooden house frame consists of many different lumber pieces, but because of the regularity of these building blocks, the structure can be designed using straightforward geometrical principles. The design of multicomponent protein assemblies in comparison has been much more complex, largely due to the irregular shapes of protein structures 1 . Here we describe extendable linear, curved, and angled protein building blocks, as well as inter-block interactions that conform to specified geometric standards; assemblies designed using these blocks inherit their extendability and regular interaction surfaces, enabling them to be expanded or contracted by varying the number of modules, and reinforced with secondary struts. Using X-ray crystallography and electron microscopy, we validate nanomaterial designs ranging from simple polygonal and circular oligomers that can be concentrically nested, up to large polyhedral nanocages and unbounded straight "train track" assemblies with reconfigurable sizes and geometries that can be readily blueprinted. Because of the complexity of protein structures and sequence-structure relationships, it has not been previously possible to build up large protein assemblies by deliberate placement of protein backbones onto a blank 3D canvas; the simplicity and geometric regularity of our design platform now enables construction of protein nanomaterials according to "back of an envelope" architectural blueprints.