Defining short linear motif binding determinants by phage display-based deep mutational scanning

Deep mutational scanning (DMS) has emerged as a powerful approach for evaluating the effects of mutations on binding or function. Here, we developed a DMS by phage display protocol to define the specificity determinants of short linear motifs (SLiMs) binding to peptide-binding domains. We first designed a benchmarking DMS library to evaluate the performance of the approach on well-known ligands for 11 different peptide-binding domains, including the talin-1 PTB domain, the G3BP1 NTF2 domain, and the MDM2 SWIB domain. Comparison with a set of reference motifs from the eukaryotic linear motif (ELM) database confirmed that the DMS by phage display analysis correctly identifies known motif binding determinants and provides novel insights into specificity determinants, including defining a non-canonical talin-1 PTB binding motif with a putative extended conformation. A second DMS library was designed, aiming to provide information on the binding determinants for 19 SLiM-based interactions between human and SARS-CoV-2 proteins. The analysis confirmed the affinity determining residues of viral peptides binding to host proteins and refined the consensus motifs in human peptides binding to five domains from SARS-CoV-2 proteins, including the non-structural protein (NSP) 9. The DMS analysis further pinpointed mutations that increased the affinity of ligands for NSP3 and NSP9. An affinity-improved cell-permeable NSP9-binding peptide was found to exert stronger antiviral effects than the wild-type peptide. Our study demonstrates that DMS by phage display can efficiently be multiplexed and applied to refine binding determinants and shows how the results can guide peptide-engineering efforts.

Phage libraries screening on P53: Yield improvement by zinc and a new parasites-integrating analysis

P53 is a transcription factor that controls a variety of genes, primarily involved in cell cycle and other processes related to cell survival and death. We have isolated peptides targeting P53 (protein and domains) using the "phage display" technique. Interestingly, adding ZnCl2 at 5-10 mM in panning solutions helped to recover more plaque-forming units at least at round one of the screening. Subtractive docking analyses were designed by using a pool of common redundant peptides known as parasites. This rationale helped us differentiate between possibly specific and non-specific bindings. We found notable differences in docking characteristics between different sets of peptides either related to different targets or related to zinc-conditions. The set of zinc-related peptides shows advantageous docking profiles: sharper binding for some positions and distinct exclusive bound residues, including the relevant R248 and R273. Zinc would have modulating/helping role in the targeting of protein P53 by phage displayed peptides in addition to an enhancement action on bacterial infection.

Molecular determinants of TRAF6 binding specificity suggest that native interaction partners are not optimized for affinity

TRAF6 is an adaptor protein involved in signaling pathways that are essential for development and the immune system. It participates in many protein-protein interactions, some of which are mediated by the C-terminal MATH domain, which binds to short peptide segments containing the motif PxExx[FYWHDE], where x is any amino acid. Blocking MATH domain interactions is associated with favorable effects in various disease models. To better define TRAF6 MATH domain binding preferences, we screened a combinatorial library using bacterial cell-surface peptide display. We identified 236 of the best TRAF6-interacting peptides and a set of 1,200 peptides that match the sequence PxE but do not bind TRAF6 MATH. The peptides that were most enriched in the screen bound TRAF6 tighter than previously measured native peptides. To better understand the structural basis for TRAF6 interaction preferences, we built all-atom structural models of the MATH domain in complex with high-affinity binders and nonbinders identified in the screen. We identified favorable interactions for motif features in binders as well as negative design elements distributed across the motif that can disfavor or preclude binding. Searching the human proteome revealed that the most biologically relevant TRAF6 motif matches occupy a different sequence space from the best hits discovered in combinatorial library screening, suggesting that native interactions are not optimized for affinity. Our experimentally determined binding preferences and structural models support the design of peptide-based interaction inhibitors with higher affinities than endogenous TRAF6 ligands.

Promiscuity mapping of the S100 protein family using a high-throughput holdup assay

S100 proteins are small, typically homodimeric, vertebrate-specific EF-hand proteins that establish Ca²⁺-dependent protein-protein interactions in the intra- and extracellular environment and are overexpressed in various pathologies. There are about 20 distinct human S100 proteins with numerous potential partner proteins. Here, we used a quantitative holdup assay to measure affinity profiles of most members of the S100 protein family against a library of chemically synthetized foldamers. The profiles allowed us to quantitatively map the binding promiscuity of each member towards the foldamer library. Since the library was designed to systematically contain most binary natural amino acid side chain combinations, the data also provide insight into the promiscuity of each S100 protein towards all potential naturally occurring S100 partners in the human proteome. Such information will be precious for future drug design to interfere with S100 related pathologies.

Proteome-scale mapping of binding sites in the unstructured regions of the human proteome

Specific protein-protein interactions are central to all processes that underlie cell physiology. Numerous studies have together identified hundreds of thousands of human protein-protein interactions. However, many interactions remain to be discovered, and low affinity, conditional, and cell type-specific interactions are likely to be disproportionately underrepresented. Here, we describe an optimized proteomic peptide-phage display library that tiles all disordered regions of the human proteome and allows the screening of ~ 1,000,000 overlapping peptides in a single binding assay. We define guidelines for processing, filtering, and ranking the results and provide PepTools, a toolkit to annotate the identified hits. We uncovered >2,000 interaction pairs for 35 known short linear motif (SLiM)-binding domains and confirmed the quality of the produced data by complementary biophysical or cell-based assays. Finally, we show how the amino acid resolution-binding site information can be used to pinpoint functionally important disease mutations and phosphorylation events in intrinsically disordered regions of the proteome. The optimized human disorderome library paired with PepTools represents a powerful pipeline for unbiased proteome-wide discovery of SLiM-based interactions.

Identification of PDZ Interactions by Proteomic Peptide Phage Display

PSD95-Disc large-Zonula occludens (PDZ) domains are among the most abundant modular domains in the human proteome. They typically bind short carboxy-terminal sequence motifs of their ligand proteins, which may be transmembrane proteins such as ion channels and GPCRs, as well as soluble proteins. The identity of the endogenous ligands of many PDZ domains remains unclear despite more than two decades of PDZ research. Combinatorial peptide phage display and bioinformatics predictions have contributed to shed light on PDZ-mediated interactions. However, the efficiency of these methods for the identification of interactions of potential biological relevance is hampered by different biases. Proteomic peptide-phage display (ProP-PD) was developed to overcome these limitations. Here we describe a ProP-PD protocol for the identification of C-terminal PDZ domain ligands. The method efficiently identifies peptide ligands within a proteome of interest, and pinpoint targets of potential biological relevance.

Phage-Displayed Peptides for Targeting Tyrosine Kinase Membrane Receptors in Cancer Therapy

Receptor tyrosine kinases (RTKs) regulate critical physiological processes, such as cell growth, survival, motility, and metabolism. Abnormal activation of RTKs and relative downstream signaling is implicated in cancer pathogenesis. Phage display allows the rapid selection of peptide ligands of membrane receptors. These peptides can target in vitro and in vivo tumor cells and represent a novel therapeutic approach for cancer therapy. Further, they are more convenient compared to antibodies, being less expensive and non-immunogenic. In this review, we describe the state-of-the-art of phage display for development of peptide ligands of tyrosine kinase membrane receptors and discuss their potential applications for tumor-targeted therapy.

Rapid discovery of novel prophages using biological feature engineering and machine learning

Prophages are phages that are integrated into bacterial genomes and which are key to understanding many aspects of bacterial biology. Their extreme diversity means they are challenging to detect using sequence similarity, yet this remains the paradigm and thus many phages remain unidentified. We present a novel, fast and generalizing machine learning method based on feature space to facilitate novel prophage discovery. To validate the approach, we reanalyzed publicly available marine viromes and single-cell genomes using our feature-based approaches and found consistently more phages than were detected using current state-of-the-art tools while being notably faster. This demonstrates that our approach significantly enhances bacteriophage discovery and thus provides a new starting point for exploring new biologies.

Phage-Display Based Discovery and Characterization of Peptide Ligands against WDR5

WD40 is a ubiquitous domain presented in at least 361 human proteins and acts as scaffold to form protein complexes. Among them, WDR5 protein is an important mediator in several protein complexes to exert its functions in histone modification and chromatin remodeling. Therefore, it was considered as a promising epigenetic target involving in anti-cancer drug development. In view of the protein-protein interaction nature of WDR5, we initialized a campaign to discover new peptide-mimic inhibitors of WDR5. In current study, we utilized the phage display technique and screened with a disulfide-based cyclic peptide phage library. Five rounds of biopanning were performed and isolated clones were sequenced. By analyzing the sequences, total five peptides were synthesized for binding assay. The four peptides are shown to have the moderate binding affinity. Finally, the detailed binding interactions were revealed by solving a WDR5-peptide cocrystal structure.

A Computational Protocol to Analyze PDZ/PBM Affinity Data Obtained by High-Throughput Holdup Assay

The holdup assay is an automated high-throughput comparative chromatographic retention approach that allows to measure quantitative binding intensities (BI) for a large number of domain-motif pairs and deduce equilibrium binding affinity constants. We routinely apply this approach to obtain quantitative binding specificity profiles of particular PDZ-binding motifs (PBMs) toward the full library of known human PDZ domains (the PDZome). The quality of the electropherograms extracted from the capillary electrophoresis instrument at the final step of the holdup assay may vary, influencing the accuracy and reproducibility of the measurement. By using bioinformatic tools, we can solve these issues to extract more reliable BIs by means of a better superimposition of the electropherograms. The protocol presented in this chapter describes the main principles and strategies of our curated method to process holdup data and new ways to plot and compare the BIs for the PBM-PDZ interactions. For this particular protocol, all the necessary computing commands are freely available in open Python packages.

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.

Mapping Protein-Protein Interaction Interface Peptides with Jun-Fos Assisted Phage Display and Deep Sequencing

Protein-protein interactions govern many cellular processes, and identifying binding interaction sites on proteins can facilitate the discovery of inhibitors to block such interactions. Here we identify peptides from a randomly fragmented plasmid encoding the β-lactamase inhibitory protein (BLIP) and the Lac repressor (LacI) that represent regions of protein-protein interactions. We utilized a Jun-Fos-assisted phage display system that has previously been used to screen cDNA and genomic libraries to identify antibody antigens. Affinity selection with polyclonal antibodies against LacI or BLIP resulted in the rapid enrichment of in-frame peptides from various regions of the proteins. Further, affinity selection with β-lactamase enriched peptides that encompass regions of BLIP previously shown to contribute strongly to the binding energy of the BLIP/β-lactamase interaction, i.e., hotspot residues. Further, one of the regions enriched by affinity selection encompassed a disulfide-constrained region of BLIP that forms part of the BLIP interaction surface in the native complex that we show also binds to β-lactamase as a disulfide-constrained macrocycle peptide with a K_D of ∼1 μM. Fragmented open reading frame (ORF) libraries may efficiently identify such naturally constrained peptides at protein-protein interaction interfaces. With sufficiently deep coverage of ORFs by peptide-coding inserts, phage display and deep sequencing can provide detailed information on the domains or peptides that contribute to an interaction. Such information should enable the design of potentially therapeutic macrocycles or peptidomimetics that block the interaction.

A Multireporter Bacterial 2-Hybrid Assay for the High-Throughput and Dynamic Assay of PDZ Domain-Peptide Interactions

The accurate determination of protein-protein interactions has been an important focus of molecular biology toward which much progress has been made due to the continuous development of existing and new technologies. However, current methods can have limitations, including scale and restriction to high affinity interactions, limiting our understanding of a large subset of these interactions. Here, we describe a modified bacterial-hybrid assay that employs combined selectable and scalable reporters that enable the sensitive screening of large peptide libraries followed by the sorting of positive interactions by the level of reporter output. We have applied this tool to characterize a set of human and E. coli PDZ domains. Our results are consistent with prior characterization of these proteins, and the improved sensitivity increases our ability to predict known and novel in vivo binding partners. This approach allows for the recovery of a wide range of affinities with a high throughput method that does not sacrifice the scale of the screen.

Emerging Themes in PDZ Domain Signaling: Structure, Function, and Inhibition

Post-synaptic density-95, disks-large and zonula occludens-1 (PDZ) domains are small globular protein-protein interaction domains widely conserved from yeast to humans. They are composed of ∼90 amino acids and form a classical two α-helical/six β-strand structure. The prototypical ligand is the C-terminus of partner proteins; however, they also bind internal peptide sequences. Recent findings indicate that PDZ domains also bind phosphatidylinositides and cholesterol. Through their ligand interactions, PDZ domain proteins are critical for cellular trafficking and the surface retention of various ion channels. In addition, PDZ proteins are essential for neuronal signaling, memory, and learning. PDZ proteins also contribute to cytoskeletal dynamics by mediating interactions critical for maintaining cell-cell junctions, cell polarity, and cell migration. Given their important biological roles, it is not surprising that their dysfunction can lead to multiple disease states. As such, PDZ domain-containing proteins have emerged as potential targets for the development of small molecular inhibitors as therapeutic agents. Recent data suggest that the critical binding function of PDZ domains in cell signaling is more than just glue, and their binding function can be regulated by phosphorylation or allosterically by other binding partners. These studies also provide a wealth of structural and biophysical data that are beginning to reveal the physical features that endow this small modular domain with a central role in cell signaling.

High-throughput discovery of functional disordered regions

Partially or fully intrinsically disordered proteins are widespread in eukaryotic proteomes and play important biological functions. With the recognition that well defined protein structure is not a fundamental requirement for function come novel challenges, such as assigning function to disordered regions. In their recent work, Babu and colleagues (Ravarani et al, 2018) took on this challenge by developing IDR‐Screen, a robust high‐throughput approach for identifying functions of disordered regions.

New Phage Display-Isolated Heptapeptide Recognizing the Regulatory Carboxy-Terminal Domain of Human Tumour Protein p53

The transcription factor tumor protein p53 (P53) controls a variety of genes most involved in cell cycle and is at the origin of apoptosis when DNA is irreparably damaged. We planned to select novel tumor protein p53-interacting peptides through the screening of hepta-peptide phage-display libraries. For this aim, human tumor suppressor protein p53 was expressed in Escherichia coli as Glutathione S-transferase fusion and purified by affinity chromatography. The phage library was then screened on this immobilized protein target. After three rounds of panning, phages were sequenced and shown to contain a consensus sequence NPNSAQG. Thereafter, either free p53 liberated from the fusion protein through thrombin treatment or Histidine-tagged p53 were recognized efficiently by the selected phage. To locate the p53-binding epitope of the selected hepta-peptide, three long peptides parts of the three known domains of the protein were synthesized and screened by the selected phage/peptide. Thus, the Carboxy-terminal p53 region was shown to be the target of the isolated phage as well as by its derived Fluorescein isothiocyanate-peptide. Molecular docking showed Lysine 386 as an important residue potentially engaged in this interaction. The selected hepta-peptide is a novel p53-interacting peptide, not described by other studies, and could be used as therapeutic tool in the future.

Dual-functioning peptides discovered by phage display increase the magnitude and specificity of BMSC attachment to mineralized biomaterials

Design of biomaterials for cell-based therapies requires presentation of specific physical and chemical cues to cells, analogous to cues provided by native extracellular matrices (ECM). We previously identified a peptide sequence with high affinity towards apatite (VTKHLNQISQSY, VTK) using phage display. The aims of this study were to identify a human MSC-specific peptide sequence through phage display, combine it with the apatite-specific sequence, and verify the specificity of the combined dual-functioning peptide to both apatite and human bone marrow stromal cells. In this study, a combinatorial phage display identified the cell binding sequence (DPIYALSWSGMA, DPI) which was combined with the mineral binding sequence to generate the dual peptide DPI-VTK. DPI-VTK demonstrated significantly greater binding affinity (1/K_D) to apatite surfaces compared to VTK, phosphorylated VTK (VTK_phos), DPI-VTK_phos, RGD-VTK, and peptide-free apatite surfaces (p < 0.01), while significantly increasing hBMSC adhesion strength (τ₅₀, p < 0.01). MSCs demonstrated significantly greater adhesion strength to DPI-VTK compared to other cell types, while attachment of MC3T3 pre-osteoblasts and murine fibroblasts was limited (p < 0.01). MSCs on DPI-VTK coated surfaces also demonstrated increased spreading compared to pre-osteoblasts and fibroblasts. MSCs cultured on DPI-VTK coated apatite films exhibited significantly greater proliferation compared to controls (p < 0.001). Moreover, early and late stage osteogenic differentiation markers were elevated on DPI-VTK coated apatite films compared to controls. Taken together, phage display can identify non-obvious cell and material specific peptides to increase human MSC adhesion strength to specific biomaterial surfaces and subsequently increase cell proliferation and differentiation. These new peptides expand biomaterial design methodology for cell-based regeneration of bone defects. This strategy of combining cell and material binding phage display derived peptides is broadly applicable to a variety of systems requiring targeted adhesion of specific cell populations, and may be generalized to the engineering of any adhesion surface.

Discovery of short linear motif-mediated interactions through phage display of intrinsically disordered regions of the human proteome

The intrinsically disordered regions of eukaryotic proteomes are enriched in short linear motifs (SLiMs), which are of crucial relevance for cellular signaling and protein regulation; many mediate interactions by providing binding sites for peptide-binding domains. The vast majority of SLiMs remain to be discovered highlighting the need for experimental methods for their large-scale identification. We present a novel proteomic peptide phage display (ProP-PD) library that displays peptides representing the disordered regions of the human proteome, allowing direct large-scale interrogation of most potential binding SLiMs in the proteome. The performance of the ProP-PD library was validated through selections against SLiM-binding bait domains with distinct folds and binding preferences. The vast majority of identified binding peptides contained sequences that matched the known SLiM-binding specificities of the bait proteins. For SHANK1 PDZ, we establish a novel consensus TxF motif for its non-C-terminal ligands. The binding peptides mostly represented novel target proteins, however, several previously validated protein-protein interactions (PPIs) were also discovered. We determined the affinities between the VHS domain of GGA1 and three identified ligands to 40-130 μm through isothermal titration calorimetry, and confirmed interactions through coimmunoprecipitation using full-length proteins. Taken together, we outline a general pipeline for the design and construction of ProP-PD libraries and the analysis of ProP-PD-derived, SLiM-based PPIs. We demonstrated the methods potential to identify low affinity motif-mediated interactions for modular domains with distinct binding preferences. The approach is a highly useful complement to the current toolbox of methods for PPI discovery.

Strategies to Develop Inhibitors of Motif-Mediated Protein-Protein Interactions as Drug Leads

Protein-protein interactions are fundamental for virtually all functions of the cell. A large fraction of these interactions involve short peptide motifs, and there has been increased interest in targeting them using peptide-based therapeutics. Peptides benefit from being specific, relatively safe, and easy to produce. They are also easy to modify using chemical synthesis and molecular biology techniques. However, significant challenges remain regarding the use of peptides as therapeutic agents. Identification of peptide motifs is difficult, and peptides typically display low cell permeability and sensitivity to enzymatic degradation. In this review, we outline the principal high-throughput methodologies for motif discovery and describe current methods for overcoming pharmacokinetic and bioavailability limitations.

Motif mediated protein-protein interactions as drug targets

Protein-protein interactions (PPI) are involved in virtually every cellular process and thus represent an attractive target for therapeutic interventions. A significant number of protein interactions are frequently formed between globular domains and short linear peptide motifs (DMI). Targeting these DMIs has proven challenging and classical approaches to inhibiting such interactions with small molecules have had limited success. However, recent new approaches have led to the discovery of potent inhibitors, some of them, such as Obatoclax, ABT-199, AEG-40826 and SAH-p53-8 are likely to become approved drugs. These novel inhibitors belong to a wide range of different molecule classes, ranging from small molecules to peptidomimetics and biologicals. This article reviews the main reasons for limited success in targeting PPIs, discusses how successful approaches overcome these obstacles to discovery promising inhibitors for human protein double minute 2 (HDM2), B-cell lymphoma 2 (Bcl-2), X-linked inhibitor of apoptosis protein (XIAP), and provides a summary of the promising approaches currently in development that indicate the future potential of PPI inhibitors in drug discovery.

High-throughput methods for identification of protein-protein interactions involving short linear motifs

Interactions between modular domains and short linear motifs (3–10 amino acids peptide stretches) are crucial for cell signaling. The motifs typically reside in the disordered regions of the proteome and the interactions are often transient, allowing for rapid changes in response to changing stimuli. The properties that make domain-motif interactions suitable for cell signaling also make them difficult to capture experimentally and they are therefore largely underrepresented in the known protein-protein interaction networks. Most of the knowledge on domain-motif interactions is derived from low-throughput studies, although there exist dedicated high-throughput methods for the identification of domain-motif interactions. The methods include arrays of peptides or proteins, display of peptides on phage or yeast, and yeast-two-hybrid experiments. We here provide a survey of scalable methods for domain-motif interaction profiling. These methods have frequently been applied to a limited number of ubiquitous domain families. It is now time to apply them to a broader set of peptide binding proteins, to provide a comprehensive picture of the linear motifs in the human proteome and to link them to their potential binding partners. Despite the plethora of methods, it is still a challenge for most approaches to identify interactions that rely on post-translational modification or context dependent or conditional interactions, suggesting directions for further method development.

Design and construction of small perturbation mutagenesis libraries for antibody affinity maturation using massive microchip-synthesized oligonucleotides

We report a rational strategy to design and construct multiple small perturbation mutagenesis (SPM) libraries using massively parallel synthesis of oligonucleotides on a microchip for affinity maturation of an engineered anti-ErbB2 antibody chA21. On the basis of a comprehensive analysis of the sequence and structural relationships of six complementary determination regions (CDRs) in the Kabatman database, a computational algorithm was developed to introduce single-site and double-site mutations into variable CDR positions using ambiguous nucleotides. The six SPM libraries were composed of 419 degenerate oligonucleotides that can be expanded into 161,832 unique CDR sequences with a high coverage ratio of 95% natural amino acid diversity. We used Illumina next-generation sequencing to demonstrate that the synthetic CDR library sequences, as well as relative quantities per sequence, can be controlled precisely by adjusting reaction chamber assignment and input nucleoside composition. The microchip-synthesized oligonucleotides were used for construction of single-chain antibody fragment (scFv) phage libraries through one-step mutagenic PCR of double-stranded plasmids with >10(6)E. coli transformants. A variant with combinatorial mutations from four individual CDRs achieved more than 19-fold affinity increase. The strategy described herein should be broadly applicable to affinity and selectivity studies of antibodies and other proteins.

Epitope identification from fixed-complexity random-sequence peptide microarrays

Antibodies play an important role in modern science and medicine. They are essential in many biological assays and have emerged as an important class of therapeutics. Unfortunately, current methods for mapping antibody epitopes require costly synthesis or enrichment steps, and no low-cost universal platform exists. In order to address this, we tested a random-sequence peptide microarray consisting of over 330,000 unique peptide sequences sampling 83% of all possible tetramers and 27% of pentamers. It is a single, unbiased platform that can be used in many different types of tests, it does not rely on informatic selection of peptides for a particular proteome, and it does not require iterative rounds of selection. In order to optimize the platform, we developed an algorithm that considers the significance of k-length peptide subsequences (k-mers) within selected peptides that come from the microarray. We tested eight monoclonal antibodies and seven infectious disease cohorts. The method correctly identified five of the eight monoclonal epitopes and identified both reported and unreported epitope candidates in the infectious disease cohorts. This algorithm could greatly enhance the utility of random-sequence peptide microarrays by enabling rapid epitope mapping and antigen identification.

Interaction analysis through proteomic phage display

Phage display is a powerful technique for profiling specificities of peptide binding domains. The method is suited for the identification of high-affinity ligands with inhibitor potential when using highly diverse combinatorial peptide phage libraries. Such experiments further provide consensus motifs for genome-wide scanning of ligands of potential biological relevance. A complementary but considerably less explored approach is to display expression products of genomic DNA, cDNA, open reading frames (ORFs), or oligonucleotide libraries designed to encode defined regions of a target proteome on phage particles. One of the main applications of such proteomic libraries has been the elucidation of antibody epitopes. This review is focused on the use of proteomic phage display to uncover protein-protein interactions of potential relevance for cellular function. The method is particularly suited for the discovery of interactions between peptide binding domains and their targets. We discuss the largely unexplored potential of this method in the discovery of domain-motif interactions of potential biological relevance.

Prediction and experimental characterization of nsSNPs altering human PDZ-binding motifs

Single nucleotide polymorphisms (SNPs) are a major contributor to genetic and phenotypic variation within populations. Non-synonymous SNPs (nsSNPs) modify the sequence of proteins and can affect their folding or binding properties. Experimental analysis of all nsSNPs is currently unfeasible and therefore computational predictions of the molecular effect of nsSNPs are helpful to guide experimental investigations. While some nsSNPs can be accurately characterized, for instance if they fall into strongly conserved or well annotated regions, the molecular consequences of many others are more challenging to predict. In particular, nsSNPs affecting less structured, and often less conserved regions, are difficult to characterize. Binding sites that mediate protein-protein or other protein interactions are an important class of functional sites on proteins and can be used to help interpret nsSNPs. Binding sites targeted by the PDZ modular peptide recognition domain have recently been characterized. Here we use this data to show that it is possible to computationally identify nsSNPs in PDZ binding motifs that modify or prevent binding to the proteins containing the motifs. We confirm these predictions by experimentally validating a selected subset with ELISA. Our work also highlights the importance of better characterizing linear motifs in proteins as many of these can be affected by genetic variations.

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 β-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.

Screening peptides binding specifically to colorectal cancer cells from a phage random peptide library

The aim of this study was to screen for polypeptides binding specifically to LoVo human colorectal cancer cells using a phage-displayed peptide library as a targeting vector for colorectal cancer therapy. Human normal colorectal mucous epithelial cells were applied as absorber cells for subtraction biopanning with a c7c phage display peptide library. Positive phage clones were identified by enzyme-linked immunosorbent assay and immunofluorescence detection; amino acid sequences were deduced by DNA sequencing. After 3 rounds of screening, 5 of 20 phage clones screened positive, showing specific binding to LoVo cells and a conserved RPM motif. Specific peptides against colorectal cancer cells could be obtained from a phage display peptide library and may be used as potential vectors for targeting therapy for colorectal cancer.

The emerging contribution of sequence context to the specificity of protein interactions mediated by PDZ domains

The canonical binding mode of PDZ domains to target motifs involves a small interface, unlikely to fully account for PDZ-target interaction specificities. Here, we review recent work on sequence context, defined as the regions surrounding not only the PDZ domains but also their target motifs. We also address the theoretical problem of defining the core of PDZ domains and the practical issue of designing PDZ constructs. Sequence context is found to introduce structural diversity, to impact the stability and solubility of constructs, and to deeply influence binding affinity and specificity, thereby increasing the difficulty of predicting PDZ-motif interactions. We expect that sequence context will have similar importance for other protein interactions mediated by globular domains binding to short linear motifs.

Uncovering new aspects of protein interactions through analysis of specificity landscapes in peptide recognition domains

Protein interactions underlie all biological processes. An important class of protein interactions, often observed in signaling pathways, consists of peptide recognition domains binding short protein segments on the surface of their target proteins. Recent developments in experimental techniques have uncovered many such interactions and shed new lights on their specificity. To analyze these data, novel computational methods have been introduced that can accurately describe the specificity landscape of peptide recognition domains and predict new interactions. Combining large-scale analysis of binding specificity data with structure-based modeling can further reveal new biological insights into the molecular recognition events underlying signaling pathways.

Putting into practice domain-linear motif interaction predictions for exploration of protein networks

PDZ domains recognise short sequence motifs at the extreme C-termini of proteins. A model based on microarray data has been recently published for predicting the binding preferences of PDZ domains to five residue long C-terminal sequences. Here we investigated the potential of this predictor for discovering novel protein interactions that involve PDZ domains. When tested on real negative data assembled from published literature, the predictor displayed a high false positive rate (FPR). We predicted and experimentally validated interactions between four PDZ domains derived from the human proteins MAGI1 and SCRIB and 19 peptides derived from human and viral C-termini of proteins. Measured binding intensities did not correlate with prediction scores, and the high FPR of the predictor was confirmed. Results indicate that limitations of the predictor may arise from an incomplete model definition and improper training of the model. Taking into account these limitations, we identified several novel putative interactions between PDZ domains of MAGI1 and SCRIB and the C-termini of the proteins FZD4, ARHGAP6, NET1, TANC1, GLUT7, MARCH3, MAS, ABC1, DLL1, TMEM215 and CYSLTR2. These proteins are localised to the membrane or suggested to act close to it and are often involved in G protein signalling. Furthermore, we showed that, while extension of minimal interacting domains or peptides toward tandem constructs or longer peptides never suppressed their ability to interact, the measured affinities and inferred specificity patterns often changed significantly. This suggests that if protein fragments interact, the full length proteins are also likely to interact, albeit possibly with altered affinities and specificities. Therefore, predictors dealing with protein fragments are promising tools for discovering protein interaction networks but their application to predict binding preferences within networks may be limited.

Evolutionarily conserved bias of amino-acid usage refines the definition of PDZ-binding motif

Background

The interactions between PDZ (PSD-95, Dlg, ZO-1) domains and PDZ-binding motifs play central roles in signal transductions within cells. Proteins with PDZ domains bind to PDZ-binding motifs almost exclusively when the motifs are located at the carboxyl (C-) terminal ends of their binding partners. However, it remains little explored whether PDZ-binding motifs show any preferential location at the C-terminal ends of proteins, at genome-level.

Results

Here, we examined the distribution of the type-I (x-x-S/T-x-I/L/V) or type-II (x-x-V-x-I/V) PDZ-binding motifs in proteins encoded in the genomes of five different species (human, mouse, zebrafish, fruit fly and nematode). We first established that these PDZ-binding motifs are indeed preferentially present at their C-terminal ends. Moreover, we found specific amino acid (AA) bias for the 'x' positions in the motifs at the C-terminal ends. In general, hydrophilic AAs were favored. Our genomics-based findings confirm and largely extend the results of previous interaction-based studies, allowing us to propose refined consensus sequences for all of the examined PDZ-binding motifs. An ontological analysis revealed that the refined motifs are functionally relevant since a large fraction of the proteins bearing the motif appear to be involved in signal transduction. Furthermore, co-precipitation experiments confirmed two new protein interactions predicted by our genomics-based approach. Finally, we show that influenza virus pathogenicity can be correlated with PDZ-binding motif, with high-virulence viral proteins bearing a refined PDZ-binding motif.

Conclusions

Our refined definition of PDZ-binding motifs should provide important clues for identifying functional PDZ-binding motifs and proteins involved in signal transduction.