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

Holdup Multiplex Assay for High-Throughput Measurement of Protein-Ligand Affinity Constants Using a Mass Spectrometry Readout

The accurate description and subsequent modeling of protein interactomes require quantification of their affinities at the proteome-wide scale. Here we develop and validate the Holdup Multiplex, a versatile assay with a mass spectrometry (MS) readout for profiling the affinities of a protein for large pools of peptides. The method can precisely quantify, in one single run, thousands of affinity constants over several orders of magnitude. The throughput, dynamic range, and sensitivity can be pushed to the performance limit of the MS readout. We applied the Holdup Multiplex to quantify in a few sample runs the affinities of the 14-3-3s, phosphoreader proteins highly abundant in humans, for 1000 different phosphopeptides. The seven human 14-3-3 isoforms were found to display similar specificities but staggered affinities, with 14-3-3γ being always the best binder and 14-3-3ε and σ being the weakest. Hundreds of new 14-3-3 binding sites were identified. We also identified dozens of 14-3-3 binding sites, some intervening in key signaling pathways, that were either stabilized or destabilized by the phytotoxin Fusicoccin-A. The results were corroborated by X-ray crystallography. Finally, we demonstrated the transferability of the Holdup Multiplex by quantifying the interactions of a PDZ domain for 5400 PBM peptides at once. The approach is applicable to any category of protein-binding ligands that can be quantifiable by mass spectrometry.

Dehydrin Client Proteins Identified Using Phage Display Affinity Selected Libraries Processed With Paired-End Phage Sequencing

The late embryogenesis abundant proteins (LEAPs) are a class of noncatalytic, intrinsically disordered proteins with a malleable structure. Some LEAPs exhibit a protein and/or membrane binding capacity and LEAP binding to various targets has been positively correlated with abiotic stress tolerance. Regarding the LEAPs' presumptive role in protein protection, identifying client proteins (CtPs) to which LEAPs bind is one practicable means of revealing the mechanism by which they exert their function. To this end, we used phage display affinity selection to screen libraries derived from Arabidopsis thaliana seed mRNA with recombinant orthologous LEAPs from Arabidopsis and soybean (Glycine max). Subsequent high-throughput sequencing of DNA from affinity-purified phage was performed to characterize the entire subpopulation of phage retained by each LEAP ortholog. This entailed cataloging in-frame fusions, elimination of false positives, and aligning the hits on the CtP scaffold to reveal domains of respective CtPs that bound to orthologous LEAPs. This approach (paired-end phage sequencing) revealed a subpopulation of the proteome constituting the CtP repertoire in common between the two dehydrin orthologs (LEA14 and GmPm12) compared to bovine serum albumin (unrelated binding control). The veracity of LEAP:CtP binding for one of the CtPs (LEA14 and GmPM12 self-association) was independently assessed using temperature-related intensity change analysis. Moreover, LEAP:CtP interactions for four other CtPs were confirmed in planta using bimolecular fluorescence complementation assays. The results provide insights into the involvement of the dehydrin Y-segments and K-domains in protein binding.

Studying protein-protein interactions: Latest and most popular approaches

PPIs, or protein-protein interactions, are essential for many biological processes. According to the findings, abnormal PPIs have been linked to several diseases, such as cancer and infectious and neurological disorders. Consequently, focusing on PPIs is a path toward disease treatment and a crucial tool for producing novel medications. Many methods exist to investigate PPIs, including low- and high-throughput studies. Since many PPIs have been discovered using in vitro and in vivo experimental approaches, the use of computational methods to predict PPIs has grown due to the expanding scale of PPI data and the intrinsic complexity of interacting mechanisms. Recognizing PPI networks offers a systematic means of predicting protein functions, and pathways that are included. These investigations can help uncover the underlying molecular mechanisms of complex phenotypes and clarify the biological processes related to health and diseases. Therefore, our goal in this study is to provide an overview of the latest and most popular approaches for investigating PPIs. We also overview some important clinical approaches based on the PPIs and how these interactions can be targeted.

FaSTPACE: a fast and scalable tool for peptide alignment and consensus extraction

Several novel high-throughput experimental techniques have been developed in recent years that generate large datasets of putative biologically functional peptides. However, many of the computational tools required to process these datasets have not yet been created. In this study, we introduce FaSTPACE, a fast and scalable computational tool to rapidly align short peptides and extract enriched specificity determinants. The tool aligns peptides in a pairwise manner to produce a position-specific global similarity matrix for each peptide. Peptides are realigned in an iterative manner scoring the updated alignment based on the global similarity matrices of the peptides and updating the global similarity matrices based on the new alignment. The method then iterates until the global similarity matrices converge. Finally, an alignment and consensus motif are extracted from the resulting global similarity matrices. The tool is the first to support custom weighting for the input peptides to satisfy the pressing need to include experimental attributes encoding peptide confidence in specificity determinant extraction. FaSTPACE exhibited state-of-the-art performance and accuracy when benchmarked against similar tools on motif datasets generated using curated peptides and high-throughput data from proteomic peptide phage display. FaSTPACE is available as an open-source Python package and a web server.

Uncovering domain motif interactions using high-throughput protein-protein interaction detection methods

Protein-protein interactions (PPIs) are often mediated by short linear motifs (SLiMs) in one protein and domain in another, known as domain-motif interactions (DMIs). During the past decade, SLiMs have been studied to find their role in cellular functions such as post-translational modifications, regulatory processes, protein scaffolding, cell cycle progression, cell adhesion, cell signalling and substrate selection for proteasomal degradation. This review provides a comprehensive overview of the current PPI detection techniques and resources, focusing on their relevance to capturing interactions mediated by SLiMs. We also address the challenges associated with capturing DMIs. Moreover, a case study analysing the BioGrid database as a source of DMI prediction revealed significant known DMI enrichment in different PPI detection methods. Overall, it can be said that current high-throughput PPI detection methods can be a reliable source for predicting DMIs.

Proteome-wide assessment of human interactome as a source of capturing domain-motif and domain-domain interactions

Protein-protein interactions (PPIs) play a crucial role in various biological processes by establishing domain-motif (DMI) and domain-domain interactions (DDIs). While the existence of real DMIs/DDIs is generally assumed, it is rarely tested; therefore, this study extensively compared high-throughput methods and public PPI repositories as sources for DMI and DDI prediction based on the assumption that the human interactome provides sufficient data for the reliable identification of DMIs and DDIs. Different datasets from leading high-throughput methods (Yeast two-hybrid [Y2H], Affinity Purification coupled Mass Spectrometry [AP-MS], and Co-fractionation-coupled Mass Spectrometry) were assessed for their ability to capture DMIs and DDIs using known DMI/DDI information. High-throughput methods were not notably worse than PPI databases and, in some cases, appeared better. In conclusion, all PPI datasets demonstrated significant enrichment in DMIs and DDIs (p-value <0.001), establishing Y2H and AP-MS as reliable methods for predicting these interactions. This study provides valuable insights for biologists in selecting appropriate methods for predicting DMIs, ultimately aiding in SLiM discovery.

Prediction of motif-mediated viral mimicry through the integration of host-pathogen interactions

One of the mechanisms viruses use in hijacking host cellular machinery is mimicking Short Linear Motifs (SLiMs) in host proteins to maintain their life cycle inside host cells. In the face of the escalating volume of virus-host protein-protein interactions (vhPPIs) documented in databases; the accurate prediction of molecular mimicry remains a formidable challenge due to the inherent degeneracy of SLiMs. Consequently, there is a pressing need for computational methodologies to predict new instances of viral mimicry. Our present study introduces a DMI-de-novo pipeline, revealing that vhPPIs catalogued in the VirHostNet3.0 database effectively capture domain-motif interactions (DMIs). Notably, both affinity purification coupled mass spectrometry and yeast two-hybrid assays emerged as good approaches for delineating DMIs. Furthermore, we have identified new vhPPIs mediated by SLiMs across different viruses. Importantly, the de-novo prediction strategy facilitated the recognition of several potential mimicry candidates implicated in the subversion of host cellular proteins. The insights gleaned from this research not only enhance our comprehension of the mechanisms by which viruses co-opt host cellular machinery but also pave the way for the development of novel therapeutic interventions.

Discovery and Characterization of Linear Motif Mediated Protein-Protein Complexes

There are myriads of protein-protein complexes that form within the cell. In addition to classical binding events between globular domains, many protein-protein interactions involve short disordered protein regions. The latter contain so-called linear motifs binding specifically to ordered protein domain surfaces. Linear binding motifs are classified based on their consensus sequence, where only a few amino acids are conserved. In this chapter we will review experimental and in silico techniques that can be used for the discovery and characterization of linear motif mediated protein-protein complexes involved in cellular signaling, protein level and gene expression regulation.

Exploiting the endogenous yeast nuclear proteome to identify short linear motifs in vivo

Peptide-domain interactions mediated by short linear motifs (SLiMs) play crucial roles in cellular biology. The simplicity of SLiMs poses challenges in their computational identification. Existing high-throughput methods for discovering SLiMs lack cellular context as they are typically performed in vitro. We developed a functional selection method using yeast to identify peptides that interact with the endogenous yeast nuclear proteome. Remarkably, peptides selected for in yeast also mediated nuclear import in human cells. Notably, the identified peptides did not resemble classical nuclear localization sequences. This platform has the potential to identify and investigate motifs that interact with the nuclear proteome of yeast and human and to aid in the identification and understanding of alternative protein nuclear import mechanisms.

How different viruses perturb host cellular machinery via short linear motifs

The virus interacts with its hosts by developing protein-protein interactions. Most viruses employ protein interactions to imitate the host protein: A viral protein with the same amino acid sequence or structure as the host protein attaches to the host protein's binding partner and interferes with the host protein's pathways. Being opportunistic, viruses have evolved to manipulate host cellular mechanisms by mimicking short linear motifs. In this review, we shed light on the current understanding of mimicry via short linear motifs and focus on viral mimicry by genetically different viral subtypes by providing recent examples of mimicry evidence and how high-throughput methods can be a reliable source to study SLiM-mediated viral mimicry.

Targeting peptide-mediated interactions in omics

Peptide-mediated interactions (PMIs) play a crucial role in cell signaling network, which are responsible for about half of cellular protein-protein associations in the human interactome and have recently been recognized as a new kind of promising druggable target for drug development and disease therapy. In this article, we give a systematic review regarding the proteome-wide discovery of PMIs and targeting druggable PMIs (dPMIs) with chemical drugs, self-inhibitory peptides (SIPs) and protein agents, particularly focusing on their implications and applications for therapeutic purpose in omics. We also introduce computational peptidology strategies used to model, analyze, and design PMI-targeted molecular entities and further extend the concepts of protein context, direct/indirect readout, and enthalpy/entropy effect involved in PMIs. Current issues and future perspective on this topic are discussed. There is still a long way to go before establishment of efficient therapeutic strategies to target PMIs on the omics scale.

Protein-protein interactions in plant antioxidant defense

The regulation of reactive oxygen species (ROS) levels in plants is ensured by mechanisms preventing their over accumulation, and by diverse antioxidants, including enzymes and nonenzymatic compounds. These are affected by redox conditions, posttranslational modifications, transcriptional and posttranscriptional modifications, Ca²⁺, nitric oxide (NO) and mitogen-activated protein kinase signaling pathways. Recent knowledge about protein-protein interactions (PPIs) of antioxidant enzymes advanced during last decade. The best-known examples are interactions mediated by redox buffering proteins such as thioredoxins and glutaredoxins. This review summarizes interactions of major antioxidant enzymes with regulatory and signaling proteins and their diverse functions. Such interactions are important for stability, degradation and activation of interacting partners. Moreover, PPIs of antioxidant enzymes may connect diverse metabolic processes with ROS scavenging. Proteins like receptor for activated C kinase 1 may ensure coordination of antioxidant enzymes to ensure efficient ROS regulation. Nevertheless, PPIs in antioxidant defense are understudied, and intensive research is required to define their role in complex regulation of ROS scavenging.

Protein-protein interactions: Methods, databases, and applications in virus-host study

Almost all the cellular processes in a living system are controlled by proteins: They regulate gene expression, catalyze chemical reactions, transport small molecules across membranes, and transmit signal across membranes. Even, a viral infection is often initiated through virus-host protein interactions. Protein-protein interactions (PPIs) are the physical contacts between two or more proteins and they represent complex biological functions. Nowadays, PPIs have been used to construct PPI networks to study complex pathways for revealing the functions of unknown proteins. Scientists have used PPIs to find the molecular basis of certain diseases and also some potential drug targets. In this review, we will discuss how PPI networks are essential to understand the molecular basis of virus-host relationships and several databases which are dedicated to virus-host interaction studies. Here, we present a short but comprehensive review on PPIs, including the experimental and computational methods of finding PPIs, the databases dedicated to virus-host PPIs, and the associated various applications in protein interaction networks of some lethal viruses with their hosts.

MRBLE-pep Measurements Reveal Accurate Binding Affinities for B56, a PP2A Regulatory Subunit

Signal transduction pathways rely on dynamic interactions between protein globular domains and short linear motifs (SLiMs). The weak affinities of these interactions are essential to allow fast rewiring of signaling pathways and downstream responses but also pose technical challenges for interaction detection and measurement. We recently developed a technique (MRBLE-pep) that leverages spectrally encoded hydrogel beads to measure binding affinities between a single protein of interest and 48 different peptide sequences in a single small volume. In prior work, we applied it to map the binding specificity landscape between calcineurin and the PxIxIT SLiM (Nguyen, H. Q. et al. Elife 2019, 8). Here, using peptide sequences known to bind the PP2A regulatory subunit B56α, we systematically compare affinities measured by MRBLE-pep or isothermal calorimetry (ITC) and confirm that MRBLE-pep accurately quantifies relative affinity over a wide dynamic range while using a fraction of the material required for traditional methods such as ITC.

Screening Intrinsically Disordered Regions for Short Linear Binding Motifs

The intrinsically disordered regions of the proteome are enriched in short linear motifs (SLiMs) that serve as binding sites for peptide binding proteins. These interactions are often of low-to-mid micromolar affinities and are challenging to screen for experimentally. However, a range of dedicated methods have been developed recently, which open for screening of SLiM-based interactions on large scale. A variant of phage display, termed proteomic peptide phage display (ProP-PD), has proven particularly useful for the purpose. Here, we describe a complete high-throughput ProP-PD protocol for screening intrinsically disordered regions for SLiMs. The protocol requires some basic bioinformatics skills for the design of the library and for data analysis but can be performed in a standard biochemistry lab. The protocol starts from the construction of a library, followed by the high-throughput expression and purification of bait proteins, the phage selection, and the analysis of the binding-enriched phage pools using next-generation sequencing. As the protocol generates rather large data sets, we also emphasize the importance of data management and storage.

Critical assessment of protein intrinsic disorder prediction

Intrinsically disordered proteins, defying the traditional protein structure-function paradigm, are a challenge to study experimentally. Because a large part of our knowledge rests on computational predictions, it is crucial that their accuracy is high. The Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment was established as a community-based blind test to determine the state of the art in prediction of intrinsically disordered regions and the subset of residues involved in binding. A total of 43 methods were evaluated on a dataset of 646 proteins from DisProt. The best methods use deep learning techniques and notably outperform physicochemical methods. The top disorder predictor has F_max = 0.483 on the full dataset and F_max = 0.792 following filtering out of bona fide structured regions. Disordered binding regions remain hard to predict, with F_max = 0.231. Interestingly, computing times among methods can vary by up to four orders of magnitude.

Peptide-based Interaction Proteomics

Protein-protein interactions are often mediated by short linear motifs (SLiMs) that are located in intrinsically disordered regions (IDRs) of proteins. Interactions mediated by SLiMs are notoriously difficult to study, and many functionally relevant interactions likely remain to be uncovered. Recently, pull-downs with synthetic peptides in combination with quantitative mass spectrometry emerged as a powerful screening approach to study protein-protein interactions mediated by SLiMs. Specifically, arrays of synthetic peptides immobilized on cellulose membranes provide a scalable means to identify the interaction partners of many peptides in parallel. In this minireview we briefly highlight the relevance of SLiMs for protein-protein interactions, outline existing screening technologies, discuss unique advantages of peptide-based interaction screens and provide practical suggestions for setting up such peptide-based screens.

Resources to Discover and Use Short Linear Motifs in Viral Proteins

Viral proteins evade host immune function by molecular mimicry, often achieved by short linear motifs (SLiMs) of three to ten consecutive amino acids (AAs). Motif mimicry tolerates mutations, evolves quickly to modify interactions with the host, and enables modular interactions with protein complexes. Host cells cannot easily coordinate changes to conserved motif recognition and binding interfaces under selective pressure to maintain critical signaling pathways. SLiMs offer potential for use in synthetic biology, such as better immunogens and therapies, but may also present biosecurity challenges. We survey viral uses of SLiMs to mimic host proteins, and information resources available for motif discovery. As the number of examples continues to grow, knowledge management tools are essential to help organize and compare new findings.

An intrinsically disordered proteins community for ELIXIR

Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) are now recognised as major determinants in cellular regulation. This white paper presents a roadmap for future e-infrastructure developments in the field of IDP research within the ELIXIR framework. The goal of these developments is to drive the creation of high-quality tools and resources to support the identification, analysis and functional characterisation of IDPs. The roadmap is the result of a workshop titled “An intrinsically disordered protein user community proposal for ELIXIR” held at the University of Padua. The workshop, and further consultation with the members of the wider IDP community, identified the key priority areas for the roadmap including the development of standards for data annotation, storage and dissemination; integration of IDP data into the ELIXIR Core Data Resources; and the creation of benchmarking criteria for IDP-related software. Here, we discuss these areas of priority, how they can be implemented in cooperation with the ELIXIR platforms, and their connections to existing ELIXIR Communities and international consortia. The article provides a preliminary blueprint for an IDP Community in ELIXIR and is an appeal to identify and involve new stakeholders.

Quantitative mapping of protein-peptide affinity landscapes using spectrally encoded beads

Transient, regulated binding of globular protein domains to Short Linear Motifs (SLiMs) in disordered regions of other proteins drives cellular signaling. Mapping the energy landscapes of these interactions is essential for deciphering and perturbing signaling networks but is challenging due to their weak affinities. We present a powerful technology (MRBLE-pep) that simultaneously quantifies protein binding to a library of peptides directly synthesized on beads containing unique spectral codes. Using MRBLE-pep, we systematically probe binding of calcineurin (CN), a conserved protein phosphatase essential for the immune response and target of immunosuppressants, to the PxIxIT SLiM. We discover that flanking residues and post-translational modifications critically contribute to PxIxIT-CN affinity and identify CN-binding peptides based on multiple scaffolds with a wide range of affinities. The quantitative biophysical data provided by this approach will improve computational modeling efforts, elucidate a broad range of weak protein-SLiM interactions, and revolutionize our understanding of signaling networks.

SLiMSearch: a framework for proteome-wide discovery and annotation of functional modules in intrinsically disordered regions

The extensive intrinsically disordered regions of higher eukaryotic proteomes contain vast numbers of functional interaction modules known as short linear motifs (SLiMs). Here, we present SLiMSearch, a motif discovery tool that scans a motif consensus, representing the specificity determinants of a motif-binding domain, against a proteome to discover putative novel motif instances. SLiMSearch applies several distinct and complementary approaches exploiting the common properties of SLiMs to predict novel motifs. Consensus matches are annotated with overlapping sequence annotation, including feature information describing protein modular architecture, post-translational modification, structure, sequence variation and experimental characterisation of functional regions. Discriminatory motif attributes such as conservation and accessibility are also calculated. In addition, SLiMSearch provides functional enrichment and evolutionary analysis tools. The enrichment tool analyses GO terms, keywords and interacting partner enrichment to indicate possible motif function. The evolutionary tool evaluates motif taxonomic range and the conservation of motif sequence context. Consensus matches can be filtered based on motif attributes such as accessibility and taxonomic range; or by the localisation, interacting partners or ontology annotation of the peptide-containing protein. SLiMSearch supports a range of species of experimental and therapeutic relevance and is available online at http://slim.ucd.ie/slimsearch/.

Improved methods for the detection of histone interactions with peptide microarrays

Histone post-translational modifications contribute to chromatin function largely through the recruitment of effector proteins that contain specialized "reader" domains. While a significant number of reader domains have been characterized for their histone binding specificities, many of these domains remain poorly characterized. Peptide microarrays have been widely employed for the characterization of histone readers, as well as modifying enzymes and histone antibodies. While powerful, this platform has limitations in terms of its sensitivity and they frequently miss low affinity reader domain interactions. Here, we provide several technical changes that improve reader domain detection of low-affinity interactions. We show that 1% non-fat milk in 1X PBST as the blocking reagent during incubation improved reader-domain interaction results. Further, coupling this with post-binding high-salt washes and a brief, low-percentage formaldehyde cross-linking step prior to the high-salt washes provided the optimal balance between resolving specific low-affinity interactions and minimizing background or spurious signals. We expect this improved methodology will lead to the elucidation of previously unreported reader-histone interactions that will be important for chromatin function.

The potential application of genome editing by using CRISPR/Cas9, and its engineered and ortholog variants for studying the transcription factors involved in the maintenance of phosphate homeostasis in model plants

Phosphorus (P), an essential macronutrient, is pivotal for growth and development of plants. Availability of phosphate (Pi), the only assimilable P, is often suboptimal in rhizospheres. Pi deficiency triggers an array of spatiotemporal adaptive responses including the differential regulation of several transcription factors (TFs). Studies on MYB TF PHR1 in Arabidopsis thaliana (Arabidopsis) and its orthologs OsPHRs in Oryza sativa (rice) have provided empirical evidence of their significant roles in the maintenance of Pi homeostasis. Since the functional characterization of PHR1 in 2001, several other TFs have now been identified in these model plants. This raised a pertinent question whether there are any likely interactions across these TFs. Clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein 9 (Cas9) system has provided an attractive paradigm for editing genome in plants. Here, we review the applications and challenges of this technique for genome editing of the TFs for deciphering the function and plausible interactions across them. This technology could thus provide a much-needed fillip towards engineering TFs for generating Pi use efficient plants for sustainable agriculture. Furthermore, we contemplate whether this technology could be a viable alternative to the controversial genetically modified (GM) rice or it may also eventually embroil into a limbo.

Artificial scaffolds for enhanced biocatalysis

Proteins are not designed to be standalone entities and must coordinate their collective action for optimum performance. Nature has developed through evolution the ability to colocalize the functional partners of a cascade enzymatic reaction in order to ensure efficient exchange of intermediates. Inspired by these natural designs, synthetic scaffolds have been created to enhance the overall biological pathway performance. In this chapter, we describe several DNA- and protein-based scaffold approaches to assemble artificial enzyme cascades for a wide range of applications. We highlight the key benefits and drawbacks of these approaches to provide insights on how to choose the appropriate scaffold for different cascade systems.

Affinity and specificity of motif-based protein-protein interactions

It is becoming increasingly clear that eukaryotic cell physiology is largely controlled by protein-protein interactions involving disordered protein regions, which usually interact with globular domains in a coupled binding and folding reaction. Several protein recognition domains are part of large families where members can interact with similar peptide ligands. Because of this, much research has been devoted to understanding how specificity can be achieved. A combination of interface complementarity, interactions outside of the core binding site, avidity from multidomain architecture and spatial and temporal regulation of expression resolves the conundrum. Here, we review recent advances in molecular aspects of affinity and specificity in such protein-protein interactions.

The present and the future of motif-mediated protein-protein interactions

Protein-protein interactions (PPIs) are essential to governing virtually all cellular processes. Of particular importance are the versatile motif-mediated interactions (MMIs), which are thus far underrepresented in available interaction data. This is largely due to technical difficulties inherent in the properties of MMIs, but due to the increasing recognition of the vital roles of MMIs in biology, several systematic approaches have recently been developed to detect novel MMIs. Consequently, rapidly growing numbers of motifs are being identified and pursued further for therapeutic applications. In this review, we discuss the current understanding on the diverse functions and disease-relevance of MMIs, the key methodologies for detection of MMIs, and the potential of MMIs for drug development.

Novel linear motif filtering protocol reveals the role of the LC8 dynein light chain in the Hippo pathway

Protein-protein interactions (PPIs) formed between short linear motifs and globular domains play important roles in many regulatory and signaling processes but are highly underrepresented in current protein-protein interaction databases. These types of interactions are usually characterized by a specific binding motif that captures the key amino acids shared among the interaction partners. However, the computational proteome-level identification of interaction partners based on the known motif is hindered by the huge number of randomly occurring matches from which biologically relevant motif hits need to be extracted. In this work, we established a novel bioinformatic filtering protocol to efficiently explore interaction network of a hub protein. We introduced a novel measure that enabled the optimization of the elements and parameter settings of the pipeline which was built from multiple sequence-based prediction methods. In addition, data collected from PPI databases and evolutionary analyses were also incorporated to further increase the biological relevance of the identified motif hits. The approach was applied to the dynein light chain LC8, a ubiquitous eukaryotic hub protein that has been suggested to be involved in motor-related functions as well as promoting the dimerization of various proteins by recognizing linear motifs in its partners. From the list of putative binding motifs collected by our protocol, several novel peptides were experimentally verified to bind LC8. Altogether 71 potential new motif instances were identified. The expanded list of LC8 binding partners revealed the evolutionary plasticity of binding partners despite the highly conserved binding interface. In addition, it also highlighted a novel, conserved function of LC8 in the upstream regulation of the Hippo signaling pathway. Beyond the LC8 system, our work also provides general guidelines that can be applied to explore the interaction network of other linear motif binding proteins or protein domains.

Fine-tuning of many cellular processes relies on weak, transient protein-protein interactions. Such interactions often involve compact functional modules, called short linear motifs (SLiMs) that can bind to specific globular domains. SLiM-mediated interactions can carry out diverse molecular functions by targeting proteins to specific cellular locations, regulating the activity and binding preferences of proteins, or aiding the assembly of macromolecular complexes. The key to the function of SLiMs is their small size and highly flexible nature. At the same time, these properties make their experimental identification challenging. Consequently, only a small portion of SLiM-mediated interactions is currently known. This underlies the importance of novel computational methods that can reliably identify candidate sites involved in binding to linear motif binding domains. Here we present a novel bioinformatic approach that efficiently predicts new binding partners for SLiM-binding domains. We applied this method to the dynein light chain LC8, a protein that was already known to bind many partners in a wide range of organisms. With this method, we not only significantly expanded the interaction network of LC8, but also identified a novel function of LC8 in a highly important pathway controlling organ size in animals.

Rapid identification and validation of novel targeted approaches for Glioblastoma: A combined ex vivo-in vivo pharmaco-omic model

Tumor heterogeneity is a major factor in glioblastoma's poor response to therapy and seemingly inevitable recurrence. Only two glioblastoma drugs have received Food and Drug Administration approval since 1998, highlighting the urgent need for new therapies. Profiling "omics" analyses have helped characterize glioblastoma molecularly and have thus identified multiple molecular targets for precision medicine. These molecular targets have influenced clinical trial design; many "actionable" mutation-focused trials are underway, but because they have not yet led to therapeutic breakthroughs, new strategies for treating glioblastoma, especially those with a pharmacological functional component, remain in high demand. In that regard, high-throughput screening that allows for expedited preclinical drug testing and the use of GBM models that represent tumor heterogeneity more accurately than traditional cancer cell lines is necessary to maximize the successful translation of agents into the clinic. High-throughput screening has been successfully used in the testing, discovery, and validation of potential therapeutics in various cancer models, but it has not been extensively utilized in glioblastoma models. In this report, we describe the basic aspects of high-throughput screening and propose a modified high-throughput screening model in which ex vivo and in vivo drug testing is complemented by post-screening pharmacological, pan-omic analysis to expedite anti-glioma drugs' preclinical testing and develop predictive biomarker datasets that can aid in personalizing glioblastoma therapy and inform clinical trial design.

PP2A-B' holoenzyme substrate recognition, regulation and role in cytokinesis

Protein phosphatase 2A (PP2A) is a major Ser/Thr phosphatase; it forms diverse heterotrimeric holoenzymes that counteract kinase actions. Using a peptidome that tiles the disordered regions of the human proteome, we identified proteins containing [LMFI]xx[ILV]xEx motifs that serve as interaction sites for B′-family PP2A regulatory subunits and holoenzymes. The B′-binding motifs have important roles in substrate recognition and in competitive inhibition of substrate binding. With more than 100 novel ligands identified, we confirmed that the recently identified LxxIxEx B′α-binding motifs serve as common binding sites for B′ subunits with minor variations, and that S/T phosphorylation or D/E residues at positions 2, 7, 8 and 9 of the motifs reinforce interactions. Hundreds of proteins in the human proteome harbor intrinsic or phosphorylation-responsive B′-interaction motifs, and localize at distinct cellular organelles, such as midbody, predicting kinase-facilitated recruitment of PP2A-B′ holoenzymes for tight spatiotemporal control of phosphorylation at mitosis and cytokinesis. Moroever, Polo-like kinase 1-mediated phosphorylation of Cyk4/RACGAP1, a centralspindlin component at the midbody, facilitates binding of both RhoA guanine nucleotide exchange factor (epithelial cell transforming sequence 2 (Ect2)) and PP2A-B′ that in turn dephosphorylates Cyk4 and disrupts Ect2 binding. This feedback signaling loop precisely controls RhoA activation and specifies a restricted region for cleavage furrow ingression. Our results provide a framework for further investigation of diverse signaling circuits formed by PP2A-B′ holoenzymes in various cellular processes.

Assembly and use of high-density recombinant peptide chips for large-scale ligand screening is a practical alternative to synthetic peptide libraries

Background

Recombinant peptide chips could constitute a versatile complementation to state-of-the-art in situ (chemical on-chip) synthesis, particle-based printing, or pre-manufactured peptide spotting. Bottlenecks still impeding a routine implementation - from restricted peptide lengths, low diversity and low array densities to high costs - could so be overcome.

Methods

To assess overall performance, we assembled recombinant chips composed of 38,400 individual peptide spots on the area of a standard 96-well microtiter plate from comprehensive, highly diverse (>107 single clones) short random peptide libraries.

Results

Screening of altogether 476,160 clones against Streptavidin uncovered 2 discrete new binders: a characteristic HPQ-motif containing VSHPQAPF and a cyclic CSGSYGSC peptide. Interactions were technically confirmed by fluorescence polarization as well as biolayer-interferometry, and their potential suitability as novel detection tags evaluated by detection of a peptide-fused exemplary test protein.

Conclusion

From our data we conclude that the presented technical pipeline can reliably identify novel hits, useful as first-generation binders or templates for subsequent ligand design plus engineering.

Peptides and peptidomimetics as regulators of protein-protein interactions

Protein-protein interactions are essential for almost all intracellular and extracellular biological processes. Regulation of protein-protein interactions is one strategy to regulate cell fate in a highly selective manner. Specifically, peptides are ideal candidates for inhibition of protein-protein interactions because they can mimic a protein surface to effectively compete for binding. Additionally, peptides are synthetically accessible and can be stabilized by chemical modifications. In this review, we survey screening and rational design methods for identifying peptides to inhibit protein-protein interactions, as well as methods for stabilizing peptides to effectively mimic protein surfaces. In addition, we discuss recent applications of peptides to regulate protein-protein interactions for both basic research and therapeutic purposes.

Prediction of virus-host protein-protein interactions mediated by short linear motifs

BACKGROUND

Short linear motifs in host organisms proteins can be mimicked by viruses to create protein-protein interactions that disable or control metabolic pathways. Given that viral linear motif instances of host motif regular expressions can be found by chance, it is necessary to develop filtering methods of functional linear motifs. We conduct a systematic comparison of linear motifs filtering methods to develop a computational approach for predicting motif-mediated protein-protein interactions between human and the human immunodeficiency virus 1 (HIV-1).

RESULTS

We implemented three filtering methods to obtain linear motif sets: 1) conserved in viral proteins (C), 2) located in disordered regions (D) and 3) rare or scarce in a set of randomized viral sequences (R). The sets C,D,R are united and intersected. The resulting sets are compared by the number of protein-protein interactions correctly inferred with them - with experimental validation. The comparison is done with HIV-1 sequences and interactions from the National Institute of Allergy and Infectious Diseases (NIAID). The number of correctly inferred interactions allows to rank the interactions by the sets used to deduce them: D∪R and C. The ordering of the sets is descending on the probability of capturing functional interactions. With respect to HIV-1, the sets C∪R, D∪R, C∪D∪R infer all known interactions between HIV1 and human proteins mediated by linear motifs. We found that the majority of conserved linear motifs in the virus are located in disordered regions.

CONCLUSION

We have developed a method for predicting protein-protein interactions mediated by linear motifs between HIV-1 and human proteins. The method only use protein sequences as inputs. We can extend the software developed to any other eukaryotic virus and host in order to find and rank candidate interactions. In future works we will use it to explore possible viral attack mechanisms based on linear motif mimicry.

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.

ProViz-a web-based visualization tool to investigate the functional and evolutionary features of protein sequences

Low-throughput experiments and high-throughput proteomic and genomic analyses have created enormous quantities of data that can be used to explore protein function and evolution. The ability to consolidate these data into an informative and intuitive format is vital to our capacity to comprehend these distinct but complementary sources of information. However, existing tools to visualize protein-related data are restricted by their presentation, sources of information, functionality or accessibility. We introduce ProViz, a powerful browser-based tool to aid biologists in building hypotheses and designing experiments by simplifying the analysis of functional and evolutionary features of proteins. Feature information is retrieved in an automated manner from resources describing protein modular architecture, post-translational modification, structure, sequence variation and experimental characterization of functional regions. These features are mapped to evolutionary information from precomputed multiple sequence alignments. Data are displayed in an interactive and information-rich yet intuitive visualization, accessible through a simple protein search interface. This allows users with limited bioinformatic skills to rapidly access data pertinent to their research. Visualizations can be further customized with user-defined data either manually or using a REST API. ProViz is available at http://proviz.ucd.ie/.

Proteomic peptide phage display uncovers novel interactions of the PDZ1-2 supramodule of syntenin

Syntenin has crucial roles in cell adhesion, cell migration and synaptic transmission. Its closely linked postsynaptic density-95, discs large 1, zonula occludens-1 (PDZ) domains typically interact with C-terminal ligands. We profile syntenin PDZ1-2 through proteomic peptide phage display (ProP-PD) using a library that displays C-terminal regions of the human proteome. The protein recognizes a broad range of peptides, with a preference for hydrophobic motifs and has a tendency to recognize cryptic internal ligands. We validate the interaction with nectin-1 through orthogonal assays. The study demonstrates the power of ProP-PD as a complementary approach to uncover interactions of potential biological relevance.

Genetically modified bacteriophages

Applications of genetically modified bacteriophages.

Motif co-regulation and co-operativity are common mechanisms in transcriptional, post-transcriptional and post-translational regulation

A substantial portion of the regulatory interactions in the higher eukaryotic cell are mediated by simple sequence motifs in the regulatory segments of genes and (pre-)mRNAs, and in the intrinsically disordered regions of proteins. Although these regulatory modules are physicochemically distinct, they share an evolutionary plasticity that has facilitated a rapid growth of their use and resulted in their ubiquity in complex organisms. The ease of motif acquisition simplifies access to basal housekeeping functions, facilitates the co-regulation of multiple biomolecules allowing them to respond in a coordinated manner to changes in the cell state, and supports the integration of multiple signals for combinatorial decision-making. Consequently, motifs are indispensable for temporal, spatial, conditional and basal regulation at the transcriptional, post-transcriptional and post-translational level. In this review, we highlight that many of the key regulatory pathways of the cell are recruited by motifs and that the ease of motif acquisition has resulted in large networks of co-regulated biomolecules. We discuss how co-operativity allows simple static motifs to perform the conditional regulation that underlies decision-making in higher eukaryotic biological systems. We observe that each gene and its products have a unique set of DNA, RNA or protein motifs that encode a regulatory program to define the logical circuitry that guides the life cycle of these biomolecules, from transcription to degradation. Finally, we contrast the regulatory properties of protein motifs and the regulatory elements of DNA and (pre-)mRNAs, advocating that co-regulation, co-operativity, and motif-driven regulatory programs are common mechanisms that emerge from the use of simple, evolutionarily plastic regulatory modules.