Efficient phage display of polypeptides fused to the carboxy-terminus of the M13 gene-3 minor coat protein

AbstractWe report that, contrary to common belief, polypeptides fused to the carboxy-terminus of the M13 gene-3 minor coat protein are functionally displayed on the phage surface. In a phagemid display system, carboxy-terminal fusion through optimized linker sequences resulted in display levels comparable to those achieved with conventional amino-terminal fusions. These findings are of considerable importance to phage display technology because they enable investigations not suited to amino-terminal display, including the study of protein–protein interactions requiring free carboxy-termini, functional cDNA cloning efforts, and the display of intracellular proteins

Identification and characterization of mutations in ubiquitin required for non-covalent dimer formation

Ubiquitin (Ub) is a small protein that post-translationally modifies a variety of substrates in eukaryotic cells to modulate substrate function. The ability of Ub to interact with numerous protein domains makes Ub an attractive scaffold for engineering ubiquitin variants (UbVs) with high target specificity. Previously, we identified a UbV that formed a non-covalent stable dimer via a β-strand exchange, and in the current work we identified and characterized the minimal substitutions in the primary sequence of Ub required to form a higher ordered complex. Using solution angle scattering and X-ray crystallography, we show that a single substitution of residue Gly10 to either Ala or Val is sufficient to convert Ub from a monomer to a dimer. We also investigate contributions to dimer formation by the residues in the surrounding sequence. These results can be used to develop next-generation phage-display libraries of UbVs to engineer new interfaces for protein recognition

A general strategy for discovery of inhibitors and activators of RING and U-box E3 ligases with ubiquitin variants

RING and U-box E3 ubiquitin ligases regulate diverse eukaryotic processes and have been implicated in numerous diseases, but targeting these enzymes remains a major challenge. We report the development of three ubiquitin variants (UbVs), each binding selectively to the RING or U-box domain of a distinct E3 ligase: monomeric UBE4B, phosphorylated active CBL, or dimeric XIAP. Structural and biochemical analyses revealed that UbVs specifically inhibited the activity of UBE4B or phosphorylated CBL by blocking the E2∼Ub binding site. Surprisingly, the UbV selective for dimeric XIAP formed a dimer to stimulate E3 activity by stabilizing the closed E2∼Ub conformation. We further verified the inhibitory and stimulatory functions of UbVs in cells. Our work provides a general strategy to inhibit or activate RING/U-box E3 ligases and provides a resource for the research community to modulate these enzymes

Biosynthetic Oligoclonal Antivenom (BOA) for Snakebite and Next-Generation Treatments for Snakebite Victims

Snakebite envenoming is a neglected tropical disease that each year claims the lives of 80,000⁻140,000 victims worldwide. The only effective treatment against envenoming involves intravenous administration of antivenoms that comprise antibodies that have been isolated from the plasma of immunized animals, typically horses. The drawbacks of such conventional horse-derived antivenoms include their propensity for causing allergenic adverse reactions due to their heterologous and foreign nature, an inability to effectively neutralize toxins in distal tissue, a low content of toxin-neutralizing antibodies, and a complex manufacturing process that is dependent on husbandry and procurement of snake venoms. In recent years, an opportunity to develop a fundamentally novel type of antivenom has presented itself. By using modern antibody discovery strategies, such as phage display selection, and repurposing small molecule enzyme inhibitors, next-generation antivenoms that obviate the drawbacks of existing plasma-derived antivenoms could be developed. This article describes the conceptualization of a novel therapeutic development strategy for biosynthetic oligoclonal antivenom (BOA) for snakebites based on recombinantly expressed oligoclonal mixtures of human monoclonal antibodies, possibly combined with repurposed small molecule enzyme inhibitors

MUSI: an integrated system for identifying multiple specificity from very large peptide or nucleic acid data sets

Peptide recognition domains and transcription factors play crucial roles in cellular signaling. They bind linear stretches of amino acids or nucleotides, respectively, with high specificity. Experimental techniques that assess the binding specificity of these domains, such as microarrays or phage display, can retrieve thousands of distinct ligands, providing detailed insight into binding specificity. In particular, the advent of next-generation sequencing has recently increased the throughput of such methods by several orders of magnitude. These advances have helped reveal the presence of distinct binding specificity classes that co-exist within a set of ligands interacting with the same target. Here, we introduce a software system called MUSI that can rapidly analyze very large data sets of binding sequences to determine the relevant binding specificity patterns. Our pipeline provides two major advances. First, it can detect previously unrecognized multiple specificity patterns in any data set. Second, it offers integrated processing of very large data sets from next-generation sequencing machines. The results are visualized as multiple sequence logos describing the different binding preferences of the protein under investigation. We demonstrate the performance of MUSI by analyzing recent phage display data for human SH3 domains as well as microarray data for mouse transcription factor

Highly multiplexed and quantitative cell-surface protein profiling using genetically barcoded antibodies.

Human cells express thousands of different surface proteins that can be used for cell classification, or to distinguish healthy and disease conditions. A method capable of profiling a substantial fraction of the surface proteome simultaneously and inexpensively would enable more accurate and complete classification of cell states. We present a highly multiplexed and quantitative surface proteomic method using genetically barcoded antibodies called phage-antibody next-generation sequencing (PhaNGS). Using 144 preselected antibodies displayed on filamentous phage (Fab-phage) against 44 receptor targets, we assess changes in B cell surface proteins after the development of drug resistance in a patient with acute lymphoblastic leukemia (ALL) and in adaptation to oncogene expression in a Myc-inducible Burkitt lymphoma model. We further show PhaNGS can be applied at the single-cell level. Our results reveal that a common set of proteins including FLT3, NCR3LG1, and ROR1 dominate the response to similar oncogenic perturbations in B cells. Linking high-affinity, selective, genetically encoded binders to NGS enables direct and highly multiplexed protein detection, comparable to RNA-sequencing for mRNA. PhaNGS has the potential to profile a substantial fraction of the surface proteome simultaneously and inexpensively to enable more accurate and complete classification of cell states

Identification of specificity determining residues in peptide recognition domains using an information theoretic approach applied to large-scale binding maps

<p>Abstract</p> <p>Background</p> <p>Peptide Recognition Domains (PRDs) are commonly found in signaling proteins. They mediate protein-protein interactions by recognizing and binding short motifs in their ligands. Although a great deal is known about PRDs and their interactions, prediction of PRD specificities remains largely an unsolved problem.</p> <p>Results</p> <p>We present a novel approach to identifying these Specificity Determining Residues (SDRs). Our algorithm generalizes earlier information theoretic approaches to coevolution analysis, to become applicable to this problem. It leverages the growing wealth of binding data between PRDs and large numbers of random peptides, and searches for PRD residues that exhibit strong evolutionary covariation with some positions of the statistical profiles of bound peptides. The calculations involve only information from sequences, and thus can be applied to PRDs without crystal structures. We applied the approach to PDZ, SH3 and kinase domains, and evaluated the results using both residue proximity in co-crystal structures and verified binding specificity maps from mutagenesis studies.</p> <p>Discussion</p> <p>Our predictions were found to be strongly correlated with the physical proximity of residues, demonstrating the ability of our approach to detect physical interactions of the binding partners. Some high-scoring pairs were further confirmed to affect binding specificity using previous experimental results. Combining the covariation results also allowed us to predict binding profiles with higher reliability than two other methods that do not explicitly take residue covariation into account.</p> <p>Conclusions</p> <p>The general applicability of our approach to the three different domain families demonstrated in this paper suggests its potential in predicting binding targets and assisting the exploration of binding mechanisms.</p

MOTIPS: Automated Motif Analysis for Predicting Targets of Modular Protein Domains

<p>Abstract</p> <p>Background</p> <p>Many protein interactions, especially those involved in signaling, involve short linear motifs consisting of 5-10 amino acid residues that interact with modular protein domains such as the SH3 binding domains and the kinase catalytic domains. One straightforward way of identifying these interactions is by scanning for matches to the motif against all the sequences in a target proteome. However, predicting domain targets by motif sequence alone without considering other genomic and structural information has been shown to be lacking in accuracy.</p> <p>Results</p> <p>We developed an efficient search algorithm to scan the target proteome for potential domain targets and to increase the accuracy of each hit by integrating a variety of pre-computed features, such as conservation, surface propensity, and disorder. The integration is performed using naïve Bayes and a training set of validated experiments.</p> <p>Conclusions</p> <p>By integrating a variety of biologically relevant features to predict domain targets, we demonstrated a notably improved prediction of modular protein domain targets. Combined with emerging high-resolution data of domain specificities, we believe that our approach can assist in the reconstruction of many signaling pathways.</p

Development and characterization of synthetic antibodies binding to the cystic fibrosis conductance regulator

Cystic fibrosis transmembrane conductance regulator (CFTR) is a chloride channel in the apical surface of epithelial cells in the airway and gastrointestinal tract, and mutation of CFTR is the underlying cause of cystic fibrosis. However, the precise molecular details of the structure and function of CFTR in native and disease states remains elusive and cystic fibrosis researchers are hindered by a lack of high specificity, high affinity binding reagents for use in structural and biological studies. Here, we describe a panel of synthetic antigen-binding fragments (Fabs) isolated from a phage-displayed library that are specific for intracellular domains of CFTR that include the nucleotide-binding domains (NBD1 and NBD2), the R-region, and the regulatory insertion loop of NBD1. Binding assays performed under conditions that promote the native fold of the protein demonstrated that all Fabs recognized full-length CFTR. However, only the NBD1-specific Fab recognized denatured CFTR by western blot, suggesting a conformational epitope requirement for the other Fabs. Surface plasmon resonance experiments showed that the R-region Fab binds with high affinity to both the phosphorylated and unphosphorylated R-region. In addition, NMR analysis of bound versus unbound R-region revealed a distinct conformational effect upon Fab binding. We further defined residues involved with antibody recognition using an overlapping peptide array. In summary, we describe methodology complementary to previous hybridoma-based efforts to develop antibody reagents to CFTR, and introduce a synthetic antibody panel to aid structural and biological studies