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.

Structural and Functional Characterization of Ubiquitin Variant Inhibitors of USP15.

The multi-domain deubiquitinase USP15 regulates diverse eukaryotic processes and has been implicated in numerous diseases. We developed ubiquitin variants (UbVs) that targeted either the catalytic domain or each of three adaptor domains in USP15, including the N-terminal DUSP domain. We also designed a linear dimer (diUbV), which targeted the DUSP and catalytic domains, and exhibited enhanced specificity and more potent inhibition of catalytic activity than either UbV alone. In cells, the UbVs inhibited the deubiquitination of two USP15 substrates, SMURF2 and TRIM25, and the diUbV inhibited the effects of USP15 on the transforming growth factor ß pathway. Structural analyses revealed that three distinct UbVs bound to the catalytic domain and locked the active site in a closed, inactive conformation, and one UbV formed an unusual strand-swapped dimer and bound two DUSP domains simultaneously. These inhibitors will enable the study of USP15 function in oncology, neurology, immunology, and inflammation.

Comprehensive Analysis of the Human SH3 Domain Family Reveals a Wide Variety of Non-canonical Specificities.

SH3 domains are protein modules that mediate protein-protein interactions in many eukaryotic signal transduction pathways. The majority of SH3 domains studied thus far act by binding to proline-rich sequences in partner proteins, but a growing number of studies have revealed alternative recognition mechanisms. We have comprehensively surveyed the specificity landscape of human SH3 domains in an unbiased manner using peptide-phage display and deep sequencing. Based on ∼70,000 unique binding peptides, we obtained 154 specificity profiles for 115 SH3 domains, which reveal that roughly half of the SH3 domains exhibit non-canonical specificities and collectively recognize a wide variety of peptide motifs, most of which were previously unknown. Crystal structures of SH3 domains with two distinct non-canonical specificities revealed novel peptide-binding modes through an extended surface outside of the canonical proline-binding site. Our results constitute a significant contribution toward a complete understanding of the mechanisms underlying SH3-mediated cellular responses.

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.

A systematic approach to identify novel cancer drug targets using machine learning, inhibitor design and high-throughput screening.

We present an integrated approach that predicts and validates novel anti-cancer drug targets. We first built a classifier that integrates a variety of genomic and systematic datasets to prioritize drug targets specific for breast, pancreatic and ovarian cancer. We then devised strategies to inhibit these anti-cancer drug targets and selected a set of targets that are amenable to inhibition by small molecules, antibodies and synthetic peptides. We validated the predicted drug targets by showing strong anti-proliferative effects of both synthetic peptide and small molecule inhibitors against our predicted targets.

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.

Elucidation of the binding preferences of peptide recognition modules: SH3 and PDZ domains.

Peptide-binding domains play a critical role in regulation of cellular processes by mediating protein interactions involved in signalling. In recent years, the development of large-scale technologies has enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. These efforts have provided significant insights into the binding specificities of these modular domains. Many research groups have taken advantage of this unprecedented volume of specificity data and have developed a variety of new algorithms for the prediction of binding specificities of peptide-binding domains and for the prediction of their natural binding targets. This knowledge has also been applied to the design of synthetic peptide-binding domains in order to rewire protein-protein interaction networks. Here, we describe how these experimental technologies have impacted on our understanding of peptide-binding domain specificities and on the elucidation of their natural ligands. We discuss SH3 and PDZ domains as well characterized examples, and we explore the feasibility of expanding high-throughput experiments to other peptide-binding domains.

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.

The role of residue stability in transient protein-protein interactions involved in enzymatic phosphate hydrolysis. A computational study.

Finding why protein-protein interactions (PPIs) are so specific can provide a valuable tool in a variety of fields. Statistical surveys of so-called transient complexes (like those relevant for signal transduction mechanisms) have shown a tendency of polar residues to participate in the interaction region. Following this scheme, residues in the unbound partners have to compete between interacting with water or interacting with other residues of the protein. On the other hand, several works have shown that the notion of active site electrostatic preorganization can be used to interpret the high efficiency in enzyme reactions. This preorganization can be related to the instability of the residues important for catalysis. In some enzymes, in addition, conformational changes upon binding to other proteins lead to an increase in the activity of the enzymatic partner. In this article the linear response approximation version of the semimacroscopic protein dipoles Langevin dipoles (PDLD/S-LRA) model is used to evaluate the stability of several residues in two phosphate hydrolysis enzymes upon complexation with their activating partners. In particular, the residues relevant for PPI and for phosphate hydrolysis in the CDK2/Cyclin A and Ras/GAP complexes are analyzed. We find that the evaluation of the stability of residues in these systems can be used to identify not only active site regions but it can also be used as a guide to locate "hot spots" for PPIs. We also show that conformational changes play a major role in positioning interfacing residues in a proper "energetic" orientation, ready to interact with the residues in the partner protein surface. Thus, we extend the preorganization theory to PPIs, extrapolating the results we obtained from the above-mentioned complexes to a more general case. We conclude that the correlation between stability of a residue in the surface and the likelihood that it participates in the interaction can be a general fact for transient PPIs.