Lrp1 is a host entry factor for Rift Valley fever virus.

Rift Valley fever virus (RVFV) is a zoonotic pathogen with pandemic potential. RVFV entry is mediated by the viral glycoprotein (Gn), but host entry factors remain poorly defined. Our genome-wide CRISPR screen identified low-density lipoprotein receptor-related protein 1 (mouse Lrp1/human LRP1), heat shock protein (Grp94), and receptor-associated protein (RAP) as critical host factors for RVFV infection. RVFV Gn directly binds to specific Lrp1 clusters and is glycosylation independent. Exogenous addition of murine RAP domain 3 (mRAPD3) and anti-Lrp1 antibodies neutralizes RVFV infection in taxonomically diverse cell lines. Mice treated with mRAPD3 and infected with pathogenic RVFV are protected from disease and death. A mutant mRAPD3 that binds Lrp1 weakly failed to protect from RVFV infection. Together, these data support Lrp1 as a host entry factor for RVFV infection and define a new target to limit RVFV infections.

Ubiquitin variants potently inhibit SARS-CoV-2 PLpro and viral replication via a novel site distal to the protease active site.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has made it clear that combating coronavirus outbreaks benefits from a combination of vaccines and therapeutics. A promising drug target common to all coronaviruses-including SARS-CoV, MERS-CoV, and SARS-CoV-2-is the papain-like protease (PLpro). PLpro cleaves part of the viral replicase polyproteins into non-structural protein subunits, which are essential to the viral replication cycle. Additionally, PLpro can cleave both ubiquitin and the ubiquitin-like protein ISG15 from host cell substrates as a mechanism to evade innate immune responses during infection. These roles make PLpro an attractive antiviral drug target. Here we demonstrate that ubiquitin variants (UbVs) can be selected from a phage-displayed library and used to specifically and potently block SARS-CoV-2 PLpro activity. A crystal structure of SARS-CoV-2 PLpro in complex with a representative UbV reveals a dimeric UbV bound to PLpro at a site distal to the catalytic site. Yet, the UbV inhibits the essential cleavage activities of the protease in vitro and in cells, and it reduces viral replication in cell culture by almost five orders of magnitude.

Large-scale survey and database of high affinity ligands for peptide recognition modules.

Many proteins involved in signal transduction contain peptide recognition modules (PRMs) that recognize short linear motifs (SLiMs) within their interaction partners. Here, we used large-scale peptide-phage display methods to derive optimal ligands for 163 unique PRMs representing 79 distinct structural families. We combined the new data with previous data that we collected for the large SH3, PDZ, and WW domain families to assemble a database containing 7,984 unique peptide ligands for 500 PRMs representing 82 structural families. For 74 PRMs, we acquired enough new data to map the specificity profiles in detail and derived position weight matrices and binding specificity logos based on multiple peptide ligands. These analyses showed that optimal peptide ligands resembled peptides observed in existing structures of PRM-ligand complexes, indicating that a large majority of the phage-derived peptides are likely to target natural peptide-binding sites and could thus act as inhibitors of natural protein-protein interactions. The complete dataset has been assembled in an online database (http://www.prm-db.org) that will enable many structural, functional, and biological studies of PRMs and SLiMs.

Magnetite Biomineralization in Magnetospirillum magneticum Is Regulated by a Switch-like Behavior in the HtrA Protease MamE.

Magnetotactic bacteria are aquatic organisms that produce subcellular magnetic particles in order to orient in the earth's geomagnetic field. MamE, a predicted HtrA protease required to produce magnetite crystals in the magnetotactic bacterium Magnetospirillum magneticum AMB-1, was recently shown to promote the proteolytic processing of itself and two other biomineralization factors in vivo Here, we have analyzed the in vivo processing patterns of three proteolytic targets and used this information to reconstitute proteolysis with a purified form of MamE. MamE cleaves a custom peptide substrate with positive cooperativity, and its autoproteolysis can be stimulated with exogenous substrates or peptides that bind to either of its PDZ domains. A misregulated form of the protease that circumvents specific genetic requirements for proteolysis causes biomineralization defects, showing that proper regulation of its activity is required during magnetite biosynthesis in vivo Our results represent the first reconstitution of the proteolytic activity of MamE and show that its behavior is consistent with the previously proposed checkpoint model for biomineralization.

ELASPIC web-server: proteome-wide structure-based prediction of mutation effects on protein stability and binding affinity.

UNLABELLED: ELASPIC is a novel ensemble machine-learning approach that predicts the effects of mutations on protein folding and protein-protein interactions. Here, we present the ELASPIC webserver, which makes the ELASPIC pipeline available through a fast and intuitive interface. The webserver can be used to evaluate the effect of mutations on any protein in the Uniprot database, and allows all predicted results, including modeled wild-type and mutated structures, to be managed and viewed online and downloaded if needed. It is backed by a database which contains improved structural domain definitions, and a list of curated domain-domain interactions for all known proteins, as well as homology models of domains and domain-domain interactions for the human proteome. Homology models for proteins of other organisms are calculated on the fly, and mutations are evaluated within minutes once the homology model is available. AVAILABILITY AND IMPLEMENTATION: The ELASPIC webserver is available online at http://elaspic.kimlab.org CONTACT: pm.kim@utoronto.ca or pi@kimlab.orgSupplementary data: Supplementary data are available at Bioinformatics online.

Large-scale interaction profiling of PDZ domains through proteomic peptide-phage display using human and viral phage peptidomes.

The human proteome contains a plethora of short linear motifs (SLiMs) that serve as binding interfaces for modular protein domains. Such interactions are crucial for signaling and other cellular processes, but are difficult to detect because of their low to moderate affinities. Here we developed a dedicated approach, proteomic peptide-phage display (ProP-PD), to identify domain-SLiM interactions. Specifically, we generated phage libraries containing all human and viral C-terminal peptides using custom oligonucleotide microarrays. With these libraries we screened the nine PSD-95/Dlg/ZO-1 (PDZ) domains of human Densin-180, Erbin, Scribble, and Disks large homolog 1 for peptide ligands. We identified several known and putative interactions potentially relevant to cellular signaling pathways and confirmed interactions between full-length Scribble and the target proteins ß-PIX, plakophilin-4, and guanylate cyclase soluble subunit α-2 using colocalization and coimmunoprecipitation experiments. The affinities of recombinant Scribble PDZ domains and the synthetic peptides representing the C termini of these proteins were in the 1- to 40-µM range. Furthermore, we identified several well-established host-virus protein-protein interactions, and confirmed that PDZ domains of Scribble interact with the C terminus of Tax-1 of human T-cell leukemia virus with micromolar affinity. Previously unknown putative viral protein ligands for the PDZ domains of Scribble and Erbin were also identified. Thus, we demonstrate that our ProP-PD libraries are useful tools for probing PDZ domain interactions. The method can be extended to interrogate all potential eukaryotic, bacterial, and viral SLiMs and we suggest it will be a highly valuable approach for studying cellular and pathogen-host protein-protein interactions.

PAT: predictor for structured units and its application for the optimization of target molecules for the generation of synthetic antibodies.

BACKGROUND: The identification of structured units in a protein sequence is an important first step for most biochemical studies. Importantly for this study, the identification of stable structured region is a crucial first step to generate novel synthetic antibodies. While many approaches to find domains or predict structured regions exist, important limitations remain, such as the optimization of domain boundaries and the lack of identification of non-domain structured units. Moreover, no integrated tool exists to find and optimize structural domains within protein sequences. RESULTS: Here, we describe a new tool, PAT ( http://www.kimlab.org/software/pat ) that can efficiently identify both domains (with optimized boundaries) and non-domain putative structured units. PAT automatically analyzes various structural properties, evaluates the folding stability, and reports possible structural domains in a given protein sequence. For reliability evaluation of PAT, we applied PAT to identify antibody target molecules based on the notion that soluble and well-defined protein secondary and tertiary structures are appropriate target molecules for synthetic antibodies. CONCLUSION: PAT is an efficient and sensitive tool to identify structured units. A performance analysis shows that PAT can characterize structurally well-defined regions in a given sequence and outperforms other efforts to define reliable boundaries of domains. Specially, PAT successfully identifies experimentally confirmed target molecules for antibody generation. PAT also offers the pre-calculated results of 20,210 human proteins to accelerate common queries. PAT can therefore help to investigate large-scale structured domains and improve the success rate for synthetic antibody generation.

Structural and functional validation of a highly specific Smurf2 inhibitor.

Smurf1 and Smurf2 are two closely related member of the HECT (homologous to E6AP carboxy terminus) E3 ubiquitin ligase family and play important roles in the regulation of various cellular processes. Both were initially identified to regulate transforming growth factor-ß and bone morphogenetic protein signaling pathways through regulating Smad protein stability and are now implicated in various pathological processes. Generally, E3 ligases, of which over 800 exist in humans, are ideal targets for inhibition as they determine substrate specificity; however, there are few inhibitors with the ability to precisely target a particular E3 ligase of interest. In this work, we explored a panel of ubiquitin variants (UbVs) that were previously identified to bind Smurf1 or Smurf2. In vitro binding and ubiquitination assays identified a highly specific Smurf2 inhibitor, UbV S2.4, which was able to inhibit ligase activity with high potency in the low nanomolar range. Orthologous cellular assays further demonstrated high specificity of UbV S2.4 toward Smurf2 and no cross-reactivity toward Smurf1. Structural analysis of UbV S2.4 in complex with Smurf2 revealed its mechanism of inhibition was through targeting the E2 binding site. In summary, we investigated several protein-based inhibitors of Smurf1 and Smurf2 and identified a highly specific Smurf2 inhibitor that disrupts the E2-E3 protein interaction interface.

A genome-scale DNA repair RNAi screen identifies SPG48 as a novel gene associated with hereditary spastic paraplegia.

DNA repair is essential to maintain genome integrity, and genes with roles in DNA repair are frequently mutated in a variety of human diseases. Repair via homologous recombination typically restores the original DNA sequence without introducing mutations, and a number of genes that are required for homologous recombination DNA double-strand break repair (HR-DSBR) have been identified. However, a systematic analysis of this important DNA repair pathway in mammalian cells has not been reported. Here, we describe a genome-scale endoribonuclease-prepared short interfering RNA (esiRNA) screen for genes involved in DNA double strand break repair. We report 61 genes that influenced the frequency of HR-DSBR and characterize in detail one of the genes that decreased the frequency of HR-DSBR. We show that the gene KIAA0415 encodes a putative helicase that interacts with SPG11 and SPG15, two proteins mutated in hereditary spastic paraplegia (HSP). We identify mutations in HSP patients, discovering KIAA0415/SPG48 as a novel HSP-associated gene, and show that a KIAA0415/SPG48 mutant cell line is more sensitive to DNA damaging drugs. We present the first genome-scale survey of HR-DSBR in mammalian cells providing a dataset that should accelerate the discovery of novel genes with roles in DNA repair and associated medical conditions. The discovery that proteins forming a novel protein complex are required for efficient HR-DSBR and are mutated in patients suffering from HSP suggests a link between HSP and DNA repair.

Monoclonal antibodies binding data for SARS-CoV-2 proteins.

SARS-CoV-2 pandemic opens up the curiosity of understanding the coronavirus. This demand for the development of the regent, which can be used for academic and therapeutic applications. The present data provide the biochemical characterization of synthetically developed monoclonal antibodies for the SARS-CoV-2 proteins. The antibodies from phage-displayed antibody libraries were selected with the SARS-CoV-2 proteins immobilized in microwell plates. The clones which bind to the antigen in Fab-phage ELISA were selected, and a two-point competitive phage ELISA was performed. Antibodies binding kinetic of IgGs for SARS-CoV2 proteins further carried with B.L.I. Systematic analysis of binding with different control proteins and purified SARS-CoV-2 ensured the robustness of the antibodies.

Development of Monoclonal Antibodies to Detect for SARS-CoV-2 Proteins.

The COVID-19 pandemic caused by SARS-CoV-2 infection has impacted the world economy and healthcare infrastructure. Key reagents with high specificity to SARS-CoV-2 proteins are currently lacking, which limits our ability to understand the pathophysiology of SARS-CoV-2 infections. To address this need, we initiated a series of studies to generate and develop highly specific antibodies against proteins from SARS-CoV-2 using an antibody engineering platform. These efforts resulted in 18 monoclonal antibodies against nine SARS-CoV-2 proteins. Here we report the characterization of several antibodies, including those that recognize Nsp1, Nsp8, Nsp12, and Orf3b viral proteins. Our validation studies included evaluation for use of antibodies in ELISA, western blots, and immunofluorescence assays (IFA). We expect that availability of these antibodies will enhance our ability to further characterize host-viral interactions, including specific roles played by viral proteins during infection, to acquire a better understanding of the pathophysiology of SARS-CoV-2 infections.

Multifaceted N-Degron Recognition and Ubiquitylation by GID/CTLH E3 Ligases.

N-degron E3 ubiquitin ligases recognize specific residues at the N-termini of substrates. Although molecular details of N-degron recognition are known for several E3 ligases, the range of N-terminal motifs that can bind a given E3 substrate binding domain remains unclear. Here, we discovered capacity of Gid4 and Gid10 substrate receptor subunits of yeast "GID"/human "CTLH" multiprotein E3 ligases to tightly bind a wide range of N-terminal residues whose recognition is determined in part by the downstream sequence context. Screening of phage displaying peptide libraries with exposed N-termini identified novel consensus motifs with non-Pro N-terminal residues binding Gid4 or Gid10 with high affinity. Structural data reveal that conformations of flexible loops in Gid4 and Gid10 complement sequences and folds of interacting peptides. Together with analysis of endogenous substrate degrons, the data show that degron identity, substrate domains harboring targeted lysines, and varying E3 ligase higher-order assemblies combinatorially determine efficiency of ubiquitylation and degradation.

SCOWLP update: 3D classification of protein-protein, -peptide, -saccharide and -nucleic acid interactions, and structure-based binding inferences across folds.

BACKGROUND: Protein interactions are essential for coordinating cellular functions. Proteomic studies have already elucidated a huge amount of protein-protein interactions that require detailed functional analysis. Understanding the structural basis of each individual interaction through their structural determination is necessary, yet an unfeasible task. Therefore, computational tools able to predict protein binding regions and recognition modes are required to rationalize putative molecular functions for proteins. With this aim, we previously created SCOWLP, a structural classification of protein binding regions at protein family level, based on the information obtained from high-resolution 3D protein-protein and protein-peptide complexes. DESCRIPTION: We present here a new version of SCOWLP that has been enhanced by the inclusion of protein-nucleic acid and protein-saccharide interactions. SCOWLP takes interfacial solvent into account for a detailed characterization of protein interactions. In addition, the binding regions obtained per protein family have been enriched by the inclusion of predicted binding regions, which have been inferred from structurally related proteins across all existing folds. These inferences might become very useful to suggest novel recognition regions and compare structurally similar interfaces from different families. CONCLUSIONS: The updated SCOWLP has new functionalities that allow both, detection and comparison of protein regions recognizing different types of ligands, which include other proteins, peptides, nucleic acids and saccharides, within a solvated environment. Currently, SCOWLP allows the analysis of predicted protein binding regions based on structure-based inferences across fold space. These predictions may have a unique potential in assisting protein docking, in providing insights into protein interaction networks, and in guiding rational engineering of protein ligands. The newly designed SCOWLP web application has an improved user-friendly interface that facilitates its usage, and is available at http://www.scowlp.org.

Studies on the inference of protein binding regions across fold space based on structural similarities.

The emerging picture of a continuous protein fold space highlights the existence of non obvious structural similarities between proteins with apparent different topologies. The identification of structure resemblances across fold space and the analysis of similar recognition regions may be a valuable source of information towards protein structure-based functional characterization. In this work, we use non-sequential structural alignment methods (ns-SAs) to identify structural similarities between protein pairs independently of their SCOP hierarchy, and we calculate the significance of binding region conservation using the interacting residues overlap in the ns-SA. We cluster the binding inferences for each family to distinguish already known family binding regions from putative new ones. Our methodology exploits the enormous amount of data available in the PDB to identify binding region similarities within protein families and to propose putative binding regions. Our results indicate that there is a plethora of structurally common binding regions among proteins, independently of current fold classifications. We obtain a 6- to 8-fold enrichment of novel binding regions, and identify binding inferences for 728 protein families that so far lack binding information in the PDB. We explore binding mode analogies between ligands from commonly clustered binding regions to investigate the utility of our methodology. A comprehensive analysis of the obtained binding inferences may help in the functional characterization of protein recognition and assist rational engineering. The data obtained in this work is available in the download link at www.scowlp.org.

Docking glycosaminoglycans to proteins: analysis of solvent inclusion.

Glycosaminoglycans (GAGs) are anionic polysaccharides, which participate in key processes in the extracellular matrix by interactions with protein targets. Due to their charged nature, accurate consideration of electrostatic and water-mediated interactions is indispensable for understanding GAGs binding properties. However, solvent is often overlooked in molecular recognition studies. Here we analyze the abundance of solvent in GAG-protein interfaces and investigate the challenges of adding explicit solvent in GAG-protein docking experiments. We observe PDB GAG-protein interfaces being significantly more hydrated than protein-protein interfaces. Furthermore, by applying molecular dynamics approaches we estimate that about half of GAG-protein interactions are water-mediated. With a dataset of eleven GAG-protein complexes we analyze how solvent inclusion affects Autodock 3, eHiTs, MOE and FlexX docking. We develop an approach to de novo place explicit solvent into the binding site prior to docking, which uses the GRID program to predict positions of waters and to locate possible areas of solvent displacement upon ligand binding. To investigate how solvent placement affects docking performance, we compare these results with those obtained by taking into account information about the solvent position in the crystal structure. In general, we observe that inclusion of solvent improves the results obtained with these methods. Our data show that Autodock 3 performs best, though it experiences difficulties to quantitatively reproduce experimental data on specificity of heparin/heparan sulfate disaccharides binding to IL-8. Our work highlights the current challenges of introducing solvent in protein-GAGs recognition studies, which is crucial for exploiting the full potential of these molecules for rational engineering.

A Panel of Engineered Ubiquitin Variants Targeting the Family of Domains Found in Ubiquitin Specific Proteases (DUSPs).

Domains found in ubiquitin specific proteases (DUSPs) occur in seven members of the ubiquitin specific protease (USP) family. DUSPs are defined by a distinct structural fold but their functions remain largely unknown, although studies with USP4 suggest that its DUSP enhances deubiquitination activity. We used phage-displayed libraries of ubiquitin variants (UbVs) to derive protein-based tools to target DUSP family members with high affinity and specificity. We designed a UbV library based on insights from the structure of a previously identified UbV bound to the DUSP of USP15. The new library yielded 33 unique UbVs that bound to DUSPs from five different USPs (USP4, USP11, USP15, USP20 and USP33). For each USP, we were able to identify at least one DUSP that bound with high affinity and absolute specificity relative to the other DUSPs. We showed that UbVs targeting the DUSPs of USP15, USP11 and USP20 inhibited the catalytic activity of the enzyme, despite the fact that the DUSP is located outside of the catalytic domain. These findings provide an alternative means of inhibiting USP activity by targeting DUSPs, and this mechanism could be potentially extended other DUSP-containing USPs.

Comprehensive Assessment of the Relationship Between Site-2 Specificity and Helix α2 in the Erbin PDZ Domain.

PDZ domains are key players in signalling pathways. These modular domains generally recognize short linear C-terminal stretches of sequences in proteins that organize the formation of complex multi-component assemblies. The development of new methodologies for the characterization of the molecular principles governing these interactions is critical to fully understand the functional diversity of the family and to elucidate biological functions for family members. Here, we applied an in vitro evolution strategy to explore comprehensively the capacity of PDZ domains for specific recognition of different amino acids at a key position in C-terminal peptide ligands. We constructed a phage-displayed library of the Erbin PDZ domain by randomizing the binding site-2 and adjacent residues, which are all contained in helix α2, and we selected for variants binding to a panel of peptides representing all possible position-2 residues. This approach generated insights into the basis for the common natural class I and II specificities, demonstrated an alternative basis for a rare natural class III specificity for Asp-2, and revealed a novel specificity for Arg-2 that has not been reported in natural PDZ domains. A structure of a PDZ-peptide complex explained the minimum requirement for switching specificity from class I ligands containing Thr/Ser-2 to class II ligands containing hydrophobic residues at position-2. A second structure explained the molecular basis for the specificity for ligands containing Arg-2. Overall, the evolved PDZ variants greatly expand our understanding of site-2 specificities and the variants themselves may prove useful as building blocks for synthetic biology.

Identification of Ubiquitin Variants That Inhibit the E2 Ubiquitin Conjugating Enzyme, Ube2k.

Transfer of ubiquitin to substrate proteins regulates most processes in eukaryotic cells. E2 enzymes are a central component of the ubiquitin machinery, and generally determine the type of ubiquitin signal generated and thus the ultimate fate of substrate proteins. The E2, Ube2k, specifically builds degradative ubiquitin chains on diverse substrates. Here we have identified protein-based reagents, called ubiquitin variants (UbVs), that bind tightly and specifically to Ube2k. Crystal structures reveal that the UbVs bind to the E2 enzyme at a hydrophobic cleft that is distinct from the active site and previously identified ubiquitin binding sites. We demonstrate that the UbVs are potent inhibitors of Ube2k and block both ubiquitin charging of the E2 enzyme and E3-catalyzed ubiquitin transfer. The binding site of the UbVs suggests they directly clash with the ubiquitin activating enzyme, while potentially disrupting interactions with E3 ligases via allosteric effects. Our data reveal the first protein-based inhibitors of Ube2k and unveil a hydrophobic groove that could be an effective target for inhibiting Ube2k and other E2 enzymes.

Comprehensive analysis of all evolutionary paths between two divergent PDZ domain specificities.

To understand the molecular evolution of functional diversity in protein families, we comprehensively investigated the consequences of all possible mutation combinations separating two peptide-binding domains with highly divergent specificities. We analyzed the Erbin PDZ domain (Erbin-PDZ), which exhibits canonical type I specificity, and a synthetic Erbin-PDZ variant (E-14) that differs at six positions and exhibits an atypical specificity that closely resembles that of the natural Pdlim4 PDZ domain (Pdlim4-PDZ). We constructed a panel of 64 PDZ domains covering all possible transitions between Erbin-PDZ and E-14 (i.e., the panel contained variants with all possible combinations of either the Erbin-PDZ or E-14 sequence at the six differing positions). We assessed the specificity profiles of the 64 PDZ domains using a C-terminal phage-displayed peptide library containing all possible genetically encoded heptapeptides. The specificity profiles clustered into six distinct groups, showing that intermediate domains can be nodes for the evolution of divergent functions. Remarkably, three substitutions were sufficient to convert the specificity of Erbin-PDZ to that of Pdlim4-PDZ, whereas Pdlim4-PDZ contains 71 differences relative to Erbin-PDZ. X-ray crystallography revealed the structural basis for specificity transition: a single substitution in the center of the binding site, supported by contributions from auxiliary substitutions, altered the main chain conformation of the peptide ligand to resemble that of ligands bound to Pdlim4-PDZ. Our results show that a very small set of mutations can dramatically alter protein specificity, and these findings support the hypothesis whereby complex protein functions evolve by gene duplication followed by cumulative mutations.