SLiMFinder: a web server to find novel, significantly over-represented, short protein motifs

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.

Motif-dependent binding on the intervening domain regulates O-GlcNAc transferase

The modification of intracellular proteins with O-linked β-N-acetylglucosamine (O-GlcNAc) moieties is a highly dynamic process that spatiotemporally regulates nearly every important cellular program. Despite its significance, little is known about the substrate recognition and regulation modes of O-GlcNAc transferase (OGT), the primary enzyme responsible for O-GlcNAc addition. In this study, we identified the intervening domain (Int-D), a poorly understood protein fold found only in metazoan OGTs, as a specific regulator of OGT protein-protein interactions and substrate modification. Using proteomic peptide phage display (ProP-PD) coupled with structural, biochemical and cellular characterizations, we discovered a strongly enriched peptide motif, employed by the Int-D to facilitate specific O-GlcNAcylation. We further show that disruption of Int-D binding dysregulates important cellular programs, including response to nutrient deprivation and glucose metabolism. These findings illustrate a mode of OGT substrate recognition and offer key insights into the biological roles of this unique domain.

Identification of motif-based interactions between SARS-CoV-2 protein domains and human peptide ligands pinpoint antiviral targets

The virus life cycle depends on host-virus protein-protein interactions, which often involve a disordered protein region binding to a folded protein domain. Here, we used proteomic peptide phage display (ProP-PD) to identify peptides from the intrinsically disordered regions of the human proteome that bind to folded protein domains encoded by the SARS-CoV-2 genome. Eleven folded domains of SARS-CoV-2 proteins were found to bind 281 peptides from human proteins, and affinities of 31 interactions involving eight SARS-CoV-2 protein domains were determined (KD ∼ 7-300 μM). Key specificity residues of the peptides were established for six of the interactions. Two of the peptides, binding Nsp9 and Nsp16, respectively, inhibited viral replication. Our findings demonstrate how high-throughput peptide binding screens simultaneously identify potential host-virus interactions and peptides with antiviral properties. Furthermore, the high number of low-affinity interactions suggest that overexpression of viral proteins during infection may perturb multiple cellular pathways.

Quantitative proteomics and phosphoproteomics of PP2A-PPP2R5D variants reveal deregulation of RPS6 phosphorylation via converging signaling cascades

Genetic germline variants of PPP2R5D (encoding: phosphoprotein phosphatase 2 regulatory protein 5D) result in PPP2R5D-related disorder (Jordan's Syndrome), which is characterized by intellectual disability, hypotonia, seizures, macrocephaly, autism spectrum disorder, and delayed motor skill development. The disorder originates from de novo single nucleotide mutations, generating missense variants that act in a dominant manner. Pathogenic mutations altering 13 different amino acids have been identified, with the E198K variant accounting for ∼40% of reported cases. However, the generation of a heterozygous E198K variant cell line to study the molecular effects of the pathogenic mutation has been challenging. Here, we use CRISPR-PRIME genomic editing to introduce a transition (c.592G>A) in a single PPP2R5D allele in HEK293 cells, generating E198K-heterozygous lines to complement existing E420K variant lines. We generate global protein and phosphorylation profiles of WT, E198K, and E420K cell lines and find unique and shared changes between variants and WT cells in kinase- and phosphatase-controlled signaling cascades. We observed ribosomal protein S6 (RPS6) hyperphosphorylation as a shared signaling alteration, indicative of increased ribosomal protein S6-kinase activity. Treatment with rapamycin or an RPS6-kinase inhibitor (LY2584702) suppressed RPS6 phosphorylation in both, suggesting upstream activation of mTORC1/p70S6K. Intriguingly, our data suggests ERK-dependent activation of mTORC1 in both E198K and E420K variant cells, with additional AKT-mediated mTORC1 activation in the E420K variant. Thus, although upstream activation of mTORC1 differs between PPP2R5D-related disorder genotypes, inhibition of mTORC1 or RPS6 kinases warrants further investigation as potential therapeutic strategies for patients.

Elucidation of Short Linear Motif-Based Interactions of the FERM Domains of Ezrin, Radixin, Moesin, and Merlin

The ERM (ezrin, radixin, and moesin) family of proteins and the related protein merlin participate in scaffolding and signaling events at the cell cortex. The proteins share an N-terminal FERM [band four-point-one (4.1) ERM] domain composed of three subdomains (F1, F2, and F3) with binding sites for short linear peptide motifs. By screening the FERM domains of the ERMs and merlin against a phage library that displays peptides representing the intrinsically disordered regions of the human proteome, we identified a large number of novel ligands. We determined the affinities for the ERM and merlin FERM domains interacting with 18 peptides and validated interactions with full-length proteins through pull-down experiments. The majority of the peptides contained an apparent Yx[FILV] motif; others show alternative motifs. We defined distinct binding sites for two types of similar but distinct binding motifs (YxV and FYDF) using a combination of Rosetta FlexPepDock computational peptide docking protocols and mutational analysis. We provide a detailed molecular understanding of how the two types of peptides with distinct motifs bind to different sites on the moesin FERM phosphotyrosine binding-like subdomain and uncover interdependencies between the different types of ligands. The study expands the motif-based interactomes of the ERMs and merlin and suggests that the FERM domain acts as a switchable interaction hub.

A novel binding site on the cryptic intervening domain is a motif-dependent regulator of O-GlcNAc transferase

The modification of intracellular proteins with O-linked β- N -acetylglucosamine (O-GlcNAc) moieties is a highly dynamic process that spatiotemporally regulates nearly every important cellular program. Despite its significance, little is known about the substrate recognition and regulation modes of O-GlcNAc transferase (OGT), the primary enzyme responsible for O-GlcNAc addition. In this study, we have identified the intervening domain (Int-D), a poorly understood protein fold found only in metazoan OGTs, as a specific regulator of OGT protein-protein interactions and substrate modification. Utilizing an innovative proteomic peptide phage display (ProP-PD) coupled with structural, biochemical, and cellular characterizations, we discovered a novel peptide motif, employed by the Int-D to facilitate specific O-GlcNAcylation. We further show that disruption of Int-D binding dysregulates important cellular programs including nutrient stress response and glucose metabolism. These findings illustrate a novel mode of OGT substrate recognition and offer the first insights into the biological roles of this unique domain.

Pr[m]: An Algorithm for Protein Motif Discovery

Motifs are the evolutionarily conserved patterns which are reported to serve the crucial structural and functional role. Identification of motif patterns in a set of protein sequences has been a prime concern for researchers in computational biology. The discovery of such a protein motif using existing algorithms is purely based on the parameters derived from sequence composition and length. However, the discovery of variable length motif remains a challenging task, as it is not possible to determine the length of a motif in advance. In current work, a k-mer based motif discovery approach called Pr[m], is proposed for the detection of the statistically significant un-gapped motif patterns, with or without wildcard characters. In order to analyze the performance of the proposed approach, a comparative study was performed with MEME and GLAM2, which are two widely used non-discriminative methods for motif discovery. A set of 7,500 test dataset were used to compare the performance of the proposed tool and the ones mentioned above. Pr[m] outperformed the existing methods in terms of predictive quality and performance. The proposed approach is hosted at https://bioserver.iiita.ac.in/Pr[m].

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.

Dynamic, but Not Necessarily Disordered, Human-Virus Interactions Mediated through SLiMs in Viral Proteins

Most viruses have small genomes that encode proteins needed to perform essential enzymatic functions. Across virus families, primary enzyme functions are under functional constraint; however, secondary functions mediated by exposed protein surfaces that promote interactions with the host proteins may be less constrained. Viruses often form transient interactions with host proteins through conformationally flexible interfaces. Exposed flexible amino acid residues are known to evolve rapidly suggesting that secondary functions may generate diverse interaction potentials between viruses within the same viral family. One mechanism of interaction is viral mimicry through short linear motifs (SLiMs) that act as functional signatures in host proteins. Viral SLiMs display specific patterns of adjacent amino acids that resemble their host SLiMs and may occur by chance numerous times in viral proteins due to mutational and selective processes. Through mimicry of SLiMs in the host cell proteome, viruses can interfere with the protein interaction network of the host and utilize the host-cell machinery to their benefit. The overlap between rapidly evolving protein regions and the location of functionally critical SLiMs suggest that these motifs and their functional potential may be rapidly rewired causing variation in pathogenicity, infectivity, and virulence of related viruses. The following review provides an overview of known viral SLiMs with select examples of their role in the life cycle of a virus, and a discussion of the structural properties of experimentally validated SLiMs highlighting that a large portion of known viral SLiMs are devoid of predicted intrinsic disorder based on the viral SLiMs from the ELM database.

Toll-like Receptor 5 Activation by the CagY Repeat Domains of Helicobacter pylori

Helicobacter pylori (Hp) is an important human pathogen associated with gastric inflammation and neoplasia. It is commonly believed that this bacterium avoids major immune recognition by Toll-like receptors (TLRs) because of low intrinsic activity of its flagellin and lipopolysaccharides (LPS). In particular, TLR5 specifically detects flagellins in various bacterial pathogens, while Hp evolved mutations in flagellin to evade detection through TLR5. Cancerogenic Hp strains encode a type IV secretion system (T4SS). The T4SS core component and pilus-associated protein CagY, a large VirB10 ortholog, drives effector molecule translocation. Here, we identify CagY as a flagellin-independent TLR5 agonist. We detect five TLR5 interaction sites, promoting binding of CagY-positive Hp to TLR5-expressing cells, TLR5 stimulation, and intracellular signal transduction. Consequently, CagY constitutes a remarkable VirB10 member detected by TLR5, driving crucial innate immune responses by this human pathogen.

Integrated analysis of Shank1 PDZ interactions with C-terminal and internal binding motifs

PDZ domains constitute a large family of modular domains that are well-known for binding C-terminal motifs of target proteins. Some of them also bind to internal PDZ binding motifs (PDZbms), but this aspect of the PDZ interactome is poorly studied. Here we explored internal PDZbm-mediated interactions using the PDZ domain of Shank1 as a model. We identified a series of human Shank1 ligands with C-terminal or internal PDZbms using proteomic peptide-phage display, and established that while the consensus sequence of C-terminal ligands is x-T-x-(L/F)-COOH, the consensus of internal PDZbm is exclusively x-T-x-F-x, where x is any amino acid. We found that the affinities of PDZbm interactions are in the low micromolar range. The crystal structure of the complex between Shank1 PDZ and an internal PDZbm revealed that the binding mode of internal PDZbms was similar to that of C-terminal ligands. Pull-down experiments confirmed that both C-terminal and internal PDZbm interactions can occur in the context of full-length proteins. Our study expands the interactome of Shank1 and hints at a largely unexplored interaction space of PDZ domains.

Piggybacking on Classical Import and Other Non-Classical Mechanisms of Nuclear Import Appear Highly Prevalent within the Human Proteome

One of the most conserved cellular pathways among eukaryotes is the extensively studied classical protein nuclear import pathway mediated by importin-α. Classical nuclear localization signals (cNLSs) are recognized by importin-α and are highly predictable due to their abundance of basic amino acids. However, various studies in model organisms have repeatedly demonstrated that only a fraction of nuclear proteins contain identifiable cNLSs, including those that directly interact with importin-α. Using data from the Human Protein Atlas and the Human Reference Interactome, and proteomic data from BioID/protein-proximity labeling studies using multiple human importin-α proteins, we determine that nearly 50% of the human nuclear proteome does not have a predictable cNLS. Surprisingly, between 25% and 50% of previously identified human importin-α cargoes do not have predictable cNLS. Analysis of importin-α cargo without a cNLS identified an alternative basic rich motif that does not resemble a cNLS. Furthermore, several previously suspected piggybacking proteins were identified, such as those belonging to the RNA polymerase II and transcription factor II D complexes. Additionally, many components of the mediator complex interact with at least one importin-α, yet do not have a predictable cNLS, suggesting that many of the subunits may enter the nucleus through an importin-α-dependent piggybacking mechanism.

Calcium ions modulate the structure of the intrinsically disordered Nucleobindin-2 protein

Nucleobindin-2 (Nucb2) is a widely expressed multi-domain protein. Nucb2 participates in many physiological processes, i.e. calcium level maintenance, feeding regulation in the hypothalamus, emotion and stress regulation, and many others. To date, this protein has not been structurally characterized. We describe the first comparative structural analysis of two homologs, a Gallus gallus and a Homo sapiens Nucb2. The in silico analysis suggested that apo-Nucb2s contain a mosaic-like structure, consisting of intertwined disordered and ordered regions. Surprisingly, the hydrogen-deuterium exchange mass spectrometry results revealed that Nucb2 is divided into two parts: an N-terminal half with a stable mosaic-like structure and a disordered C-terminal half. However, the presence of Ca²⁺ induces the formation of a mosaic-like structure in the C-terminal half of the Nucb2s. The Ca²⁺ also affects the tertiary and quaternary structure of Nucb2s. The presence of Ca²⁺ leads to an overall compaction of the Nucb2 molecule, resulting in structural change that is propagated along the molecule, which in turn affects the quaternary structure of the protein. Intrinsic disorder, and the mosaic-like Ca²⁺ dependent structure of Nucb2s, might be seen as the molecular factors responsible for their multifunctionality. Thus, Nucb2s might function as the versatile Ca²⁺ sensor involved in signal transduction.

Computational Prediction of Disordered Protein Motifs Using SLiMSuite

Short linear motifs (SLiMs) are important mediators of interactions between intrinsically disordered regions of proteins and their interaction partners. Here, we detail instructions for the computational prediction of SLiMs in disordered protein regions, using the main tools of the SLiMSuite package: (1) SLiMProb identifies and calculates enrichment of predefined motifs in a set of proteins; (2) SLiMFinder predicts SLiMs de novo in a set of proteins, accounting for evolutionary relationships; (3) QSLiMFinder increases SLiMFinder sensitivity by focusing SLiM prediction on a specific query protein/region; (4) CompariMotif compares predicted SLiMs to known SLiMs or other SLiM predictions to identify common patterns. For each tool, command-line and online server examples are provided. Detailed notes provide additional advice on different applications of SLiMSuite, including batch running of multiple datasets and conservation masking using alignments of predicted orthologues.

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.

Gain-of-Function Mutations: An Emerging Advantage for Cancer Biology

Advances in next-generation sequencing have identified thousands of genomic variants that perturb the normal functions of proteins, further contributing to diverse phenotypic consequences in cancer. Elucidating the functional pathways altered by loss-of-function (LOF) or gain-of-function (GOF) mutations will be crucial for prioritizing cancer-causing variants and their resultant therapeutic liabilities. In this review, we highlight the fundamental function of GOF mutations and discuss the potential mechanistic effects in the context of signaling networks. We also summarize advances in experimental and computational resources, which will dramatically help with studies on the functional and phenotypic consequences of mutations. Together, systematic investigations of the function of GOF mutations will provide an important missing piece for cancer biology and precision therapy.

The predictive performance of short-linear motif features in the prediction of calmodulin-binding proteins

Background

The prediction of calmodulin-binding (CaM-binding) proteins plays a very important role in the fields of biology and biochemistry, because the calmodulin protein binds and regulates a multitude of protein targets affecting different cellular processes. Computational methods that can accurately identify CaM-binding proteins and CaM-binding domains would accelerate research in calcium signaling and calmodulin function. Short-linear motifs (SLiMs), on the other hand, have been effectively used as features for analyzing protein-protein interactions, though their properties have not been utilized in the prediction of CaM-binding proteins.

Results

We propose a new method for the prediction of CaM-binding proteins based on both the total and average scores of known and new SLiMs in protein sequences using a new scoring method called sliding window scoring (SWS) as features for the prediction module. A dataset of 194 manually curated human CaM-binding proteins and 193 mitochondrial proteins have been obtained and used for testing the proposed model. The motif generation tool, Multiple EM for Motif Elucidation (MEME), has been used to obtain new motifs from each of the positive and negative datasets individually (the SM approach) and from the combined negative and positive datasets (the CM approach). Moreover, the wrapper criterion with random forest for feature selection (FS) has been applied followed by classification using different algorithms such as k-nearest neighbors (k-NN), support vector machines (SVM), naive Bayes (NB) and random forest (RF).

Conclusions

Our proposed method shows very good prediction results and demonstrates how information contained in SLiMs is highly relevant in predicting CaM-binding proteins. Further, three new CaM-binding motifs have been computationally selected and biologically validated in this study, and which can be used for predicting CaM-binding proteins.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2378-9) contains supplementary material, which is available to authorized users.

Exhaustive search of linear information encoding protein-peptide recognition

High-throughput in vitro methods have been extensively applied to identify linear information that encodes peptide recognition. However, these methods are limited in number of peptides, sequence variation, and length of peptides that can be explored, and often produce solutions that are not found in the cell. Despite the large number of methods developed to attempt addressing these issues, the exhaustive search of linear information encoding protein-peptide recognition has been so far physically unfeasible. Here, we describe a strategy, called DALEL, for the exhaustive search of linear sequence information encoded in proteins that bind to a common partner. We applied DALEL to explore binding specificity of SH3 domains in the budding yeast Saccharomyces cerevisiae. Using only the polypeptide sequences of SH3 domain binding proteins, we succeeded in identifying the majority of known SH3 binding sites previously discovered either in vitro or in vivo. Moreover, we discovered a number of sites with both non-canonical sequences and distinct properties that may serve ancillary roles in peptide recognition. We compared DALEL to a variety of state-of-the-art algorithms in the blind identification of known binding sites of the human Grb2 SH3 domain. We also benchmarked DALEL on curated biological motifs derived from the ELM database to evaluate the effect of increasing/decreasing the enrichment of the motifs. Our strategy can be applied in conjunction with experimental data of proteins interacting with a common partner to identify binding sites among them. Yet, our strategy can also be applied to any group of proteins of interest to identify enriched linear motifs or to exhaustively explore the space of linear information encoded in a polypeptide sequence. Finally, we have developed a webserver located at http://michnick.bcm.umontreal.ca/dalel, offering user-friendly interface and providing different scenarios utilizing DALEL.

Here we describe the first strategy for the exhaustive search of the linear information encoding protein-peptide recognition; an approach that has previously been physically unfeasible because the combinatorial space of polypeptide sequences is too vast. The search covers the entire space of sequences with no restriction on motif length or composition, and includes all possible combinations of amino acids at distinct positions of each sequence, as well as positions with correlated preferences for amino acids.

Evolutionary conservation of Ebola virus proteins predicts important functions at residue level

MOTIVATION

The recent outbreak of Ebola virus disease (EVD) resulted in a large number of human deaths. Due to this devastation, the Ebola virus has attracted renewed interest as model for virus evolution. Recent literature on Ebola virus (EBOV) has contributed substantially to our understanding of the underlying genetics and its scope with reference to the 2014 outbreak. But no study yet, has focused on the conservation patterns of EBOV proteins.

RESULTS

We analyzed the evolution of functional regions of EBOV and highlight the function of conserved residues in protein activities. We apply an array of computational tools to dissect the functions of EBOV proteins in detail: (i) protein sequence conservation, (ii) protein-protein interactome analysis, (iii) structural modeling and (iv) kinase prediction. Our results suggest the presence of novel post-translational modifications in EBOV proteins and their role in the modulation of protein functions and protein interactions. Moreover, on the basis of the presence of ATM recognition motifs in all EBOV proteins we postulate a role of DNA damage response pathways and ATM kinase in EVD. The ATM kinase is put forward, for further evaluation, as novel potential therapeutic target.

AVAILABILITY AND IMPLEMENTATION

http://www.biw.kuleuven.be/CSB/EBOV-PTMs CONTACT: vera.vannoort@biw.kuleuven.beSupplementary information: Supplementary data are available at Bioinformatics online.

Computational Framework for Prediction of Peptide Sequences That May Mediate Multiple Protein Interactions in Cancer-Associated Hub Proteins

A considerable proportion of protein-protein interactions (PPIs) in the cell are estimated to be mediated by very short peptide segments that approximately conform to specific sequence patterns known as linear motifs (LMs), often present in the disordered regions in the eukaryotic proteins. These peptides have been found to interact with low affinity and are able bind to multiple interactors, thus playing an important role in the PPI networks involving date hubs. In this work, PPI data and de novo motif identification based method (MEME) were used to identify such peptides in three cancer-associated hub proteins—MYC, APC and MDM2. The peptides corresponding to the significant LMs identified for each hub protein were aligned, the overlapping regions across these peptides being termed as overlapping linear peptides (OLPs). These OLPs were thus predicted to be responsible for multiple PPIs of the corresponding hub proteins and a scoring system was developed to rank them. We predicted six OLPs in MYC and five OLPs in MDM2 that scored higher than OLP predictions from randomly generated protein sets. Two OLP sequences from the C-terminal of MYC were predicted to bind with FBXW7, component of an E3 ubiquitin-protein ligase complex involved in proteasomal degradation of MYC. Similarly, we identified peptides in the C-terminal of MDM2 interacting with FKBP3, which has a specific role in auto-ubiquitinylation of MDM2. The peptide sequences predicted in MYC and MDM2 look promising for designing orthosteric inhibitors against possible disease-associated PPIs. Since these OLPs can interact with other proteins as well, these inhibitors should be specific to the targeted interactor to prevent undesired side-effects. This computational framework has been designed to predict and rank the peptide regions that may mediate multiple PPIs and can be applied to other disease-associated date hub proteins for prediction of novel therapeutic targets of small molecule PPI modulators.

Experimental detection of short regulatory motifs in eukaryotic proteins: tips for good practice as well as for bad

It has become clear in outline though not yet in detail how cellular regulatory and signalling systems are constructed. The essential machines are protein complexes that effect regulatory decisions by undergoing internal changes of state. Subcomponents of these cellular complexes are assembled into molecular switches. Many of these switches employ one or more short peptide motifs as toggles that can move between one or more sites within the switch system, the simplest being on-off switches. Paradoxically, these motif modules (termed short linear motifs or SLiMs) are both hugely abundant but difficult to research. So despite the many successes in identifying short regulatory protein motifs, it is thought that only the “tip of the iceberg” has been exposed. Experimental and bioinformatic motif discovery remain challenging and error prone. The advice presented in this article is aimed at helping researchers to uncover genuine protein motifs, whilst avoiding the pitfalls that lead to reports of false discovery.

Redefining the BH3 Death Domain as a 'Short Linear Motif'

B cell lymphoma-2 (BCL-2)-related proteins control programmed cell death through a complex network of protein–protein interactions mediated by BCL-2 homology 3 (BH3) domains. Given their roles as dynamic linchpins, the discovery of novel BH3-containing proteins has attracted considerable attention. However, without a clearly defined BH3 signature sequence the BCL-2 family has expanded to include a nebulous group of nonhomologous BH3-only proteins, now justified by an intriguing twist. We present evidence that BH3s from both ordered and disordered proteins represent a new class of short linear motifs (SLiMs) or molecular recognition features (MoRFs) and are diverse in their evolutionary histories. The implied corollaries are that BH3s have a broad phylogenetic distribution and could potentially bind to non-BCL-2-like structural domains with distinct functions.

BCL-2 family interactions are mediated by evolutionarily diverse BH3 motifs to regulate apoptosis. Given their key roles, BH3 mimetics are in clinical trials as cancer therapies.

The discovery of novel BH3-only proteins represents a major endeavor in the cell death field. As a result, BH3 motifs are reportedly present in a nebulous conglomerate of different proteins, both structured and intrinsically disordered.

There is no rigorous definition of a BH3 motif. Currently available BH3 signatures are diverse and elusive for predicting new functional BH3-containing proteins.

Redefining the BH3 motif as a new type of short linear motif (SLiM) or molecular recognition feature (MoRF) reconciles many puzzling features of this motif and opens up new avenues for research.

QSLiMFinder: improved short linear motif prediction using specific query protein data

Motivation: The sensitivity of de novo short linear motif (SLiM) prediction is limited by the number of patterns (the motif space) being assessed for enrichment. QSLiMFinder uses specific query protein information to restrict the motif space and thereby increase the sensitivity and specificity of predictions.

Results: QSLiMFinder was extensively benchmarked using known SLiM-containing proteins and simulated protein interaction datasets of real human proteins. Exploiting prior knowledge of a query protein likely to be involved in a SLiM-mediated interaction increased the proportion of true positives correctly returned and reduced the proportion of datasets returning a false positive prediction. The biggest improvement was seen if a short region of the query protein flanking the interaction site was known.

Availability and implementation: All the tools and data used in this study, including QSLiMFinder and the SLiMBench benchmarking software, are freely available under a GNU license as part of SLiMSuite, at: http://bioware.soton.ac.uk.

Contact:richard.edwards@unsw.edu.au

Supplementary information:Supplementary data are available at Bioinformatics online.

An Efficient Exact Algorithm for the Motif Stem Search Problem over Large Alphabets

In recent years, there has been an increasing interest in planted (l, d) motif search (PMS) with applications to discovering significant segments in biological sequences. However, there has been little discussion about PMS over large alphabets. This paper focuses on motif stem search (MSS), which is recently introduced to search motifs on large-alphabet inputs. A motif stem is an l-length string with some wildcards. The goal of the MSS problem is to find a set of stems that represents a superset of all (l , d) motifs present in the input sequences, and the superset is expected to be as small as possible. The three main contributions of this paper are as follows: (1) We build motif stem representation more precisely by using regular expressions. (2) We give a method for generating all possible motif stems without redundant wildcards. (3) We propose an efficient exact algorithm, called StemFinder, for solving the MSS problem. Compared with the previous MSS algorithms, StemFinder runs much faster and reports fewer stems which represent a smaller superset of all (l, d) motifs. StemFinder is freely available at http://sites.google.com/site/feqond/stemfinder.

Recombinant Intrinsically Disordered Proteins for NMR: Tips and Tricks

The growing recognition of the several roles that intrinsically disordered proteins play in biology places an increasing importance on protein sample availability to allow the characterization of their structural and dynamic properties. The sample preparation is therefore the limiting step to allow any biophysical method being able to characterize the properties of an intrinsically disordered protein and to clarify the links between these properties and the associated biological functions. An increasing array of tools has been recruited to help prepare and characterize the structural and dynamic properties of disordered proteins. This chapter describes their sample preparation, covering the most common drawbacks/barriers usually found working in the laboratory bench. We want this chapter to be the bedside book of any scientist interested in preparing intrinsically disordered protein samples for further biophysical analysis.

Bioinformatics Approaches for Predicting Disordered Protein Motifs

Short, linear motifs (SLiMs) in proteins are functional microdomains consisting of contiguous residue segments along the protein sequence, typically not more than 10 consecutive amino acids in length with less than 5 defined positions. Many positions are 'degenerate' thus offering flexibility in terms of the amino acid types allowed at those positions. Their short length and degenerate nature confers evolutionary plasticity meaning that SLiMs often evolve convergently. Further, SLiMs have a propensity to occur within intrinsically unstructured protein segments and this confers versatile functionality to unstructured regions of the proteome. SLiMs mediate multiple types of protein interactions based on domain-peptide recognition and guide functions including posttranslational modifications, subcellular localization of proteins, and ligand binding. SLiMs thus behave as modular interaction units that confer versatility to protein function and SLiM-mediated interactions are increasingly being recognized as therapeutic targets. In this chapter we start with a brief description about the properties of SLiMs and their interactions and then move on to discuss algorithms and tools including several web-based methods that enable the discovery of novel SLiMs (de novo motif discovery) as well as the prediction of novel occurrences of known SLiMs. Both individual amino acid sequences as well as sets of protein sequences can be scanned using these methods to obtain statistically overrepresented sequence patterns. Lists of putatively functional SLiMs are then assembled based on parameters such as evolutionary sequence conservation, disorder scores, structural data, gene ontology terms and other contextual information that helps to assess the functional credibility or significance of these motifs. These bioinformatics methods should certainly guide experiments aimed at motif discovery.

Cadherin juxtamembrane region derived peptides inhibit TGFβ1 induced gene expression

Bioactive peptides in the juxtamembrane regions of proteins are involved in many signaling events. The juxtamembrane regions of cadherins were examined for the identification of bioactive regions. Several peptides spanning the cytoplasmic juxtamembrane regions of E- and N-cadherin were synthesized and assessed for the ability to influence TGFβ responses in epithelial cells at the gene expression and protein levels. Peptides from regions closer to the membrane appeared more potent inhibitors of TGFβ signaling, blocking Smad3 phosphorylation. Thus inhibiting nuclear translocation of phosphorylated Smad complexes and subsequent transcriptional activation of TGFβ signal propagating genes. The peptides demonstrated a peptide-specific potential to inhibit other TGFβ superfamily members, such as BMP4.

DoReMi: context-based prioritization of linear motif matches

Many protein domains bind to short peptide sequences, called linear motifs. Data on their sequence specificities is sparse, which is why biologists usually resort to basic pattern searches to identify new putative binding sites for experimental follow-up. Most motifs have poor specificity and prioritization of the matches is thus crucial when scanning a full proteome with a pattern.

Here we present a generic method to prioritize motif occurrence predictions by using cellular contextual information. We take 2 parameters as input: the motif occurrences and one or more of the interacting domains. The potential hits are ranked based on how strongly the context network associates them with a protein containing one of the specified domains, which leads to an increased predictive performance. The method is available through a web interface at doremi.jensenlab.org, which allows for an easy application of the method. We show that this approach leads to improved predictions of binding partners for PDZ domains and the SUMO binding domain. This is consistent with the earlier observation that coupling sequence motifs with network information improves kinase-specific substrate predictions.

Potential of known and short prokaryotic protein motifs as a basis for novel peptide-based antibacterial therapeutics: a computational survey

Short linear motifs (SLiMs) are functional stretches of protein sequence that are of crucial importance for numerous biological processes by mediating protein-protein interactions. These motifs often comprise peptides of less than 10 amino acids that modulate protein-protein interactions. While well-characterized in eukaryotic intracellular signaling, their role in prokaryotic signaling is less well-understood. We surveyed the distribution of known motifs in prokaryotic extracellular and virulence proteins across a range of bacterial species and conducted searches for novel motifs in virulence proteins. Many known motifs in virulence effector proteins mimic eukaryotic motifs and enable the pathogen to control the intracellular processes of their hosts. Novel motifs were detected by finding those that had evolved independently in three or more unrelated virulence proteins. The search returned several significantly over-represented linear motifs of which some were known motifs and others are novel candidates with potential roles in bacterial pathogenesis. A putative C-terminal G[AG].$ motif found in type IV secretion system proteins was among the most significant detected. A KK$ motif that has been previously identified in a plasminogen-binding protein, was demonstrated to be enriched across a number of adhesion and lipoproteins. While there is some potential to develop peptide drugs against bacterial infection based on bacterial peptides that mimic host components, this could have unwanted effects on host signaling. Thus, novel SLiMs in virulence factors that do not mimic host components but are crucial for bacterial pathogenesis, such as the type IV secretion system, may be more useful to develop as leads for anti-microbial peptides or drugs.

Exploring Protein-Peptide Binding Specificity through Computational Peptide Screening

The binding of short disordered peptide stretches to globular protein domains is important for a wide range of cellular processes, including signal transduction, protein transport, and immune response. The often promiscuous nature of these interactions and the conformational flexibility of the peptide chain, sometimes even when bound, make the binding specificity of this type of protein interaction a challenge to understand. Here we develop and test a Monte Carlo-based procedure for calculating protein-peptide binding thermodynamics for many sequences in a single run. The method explores both peptide sequence and conformational space simultaneously by simulating a joint probability distribution which, in particular, makes searching through peptide sequence space computationally efficient. To test our method, we apply it to 3 different peptide-binding protein domains and test its ability to capture the experimentally determined specificity profiles. Insight into the molecular underpinnings of the observed specificities is obtained by analyzing the peptide conformational ensembles of a large number of binding-competent sequences. We also explore the possibility of using our method to discover new peptide-binding pockets on protein structures.

The interactions between proteins play a crucial role for almost every undertaking of a cell. Many of these interactions are mediated by the binding of relatively short unstructured polypeptide segments, or peptides, in one protein to well-folded domains in other proteins. Such protein-peptide interactions have some interesting and special properties, e.g., promiscuity, which means many different peptide sequences are able to bind the same protein domain. Peptides also often exhibit structural flexibility even after binding a protein. These special properties make it desirable, but also challenging, to simulate protein-peptide binding in atomistic detail for many different peptide sequences. To this end, we have developed a computational algorithm that simultaneously explores the structure of protein-peptide complexes and the amino acid sequences of the peptide. In particular, our algorithm allows binding-competent peptide sequences to be generated in direct relation to their binding strengths. We also explored the possibility of using our method to locate new peptide-binding pockets on protein structures. Computational algorithms such as the one developed here may pave the way to reveal the full complexity of protein-protein interaction networks used in cells.

Dual coordination of post translational modifications in human protein networks

Post-translational modifications (PTMs) regulate protein activity, stability and interaction profiles and are critical for cellular functioning. Further regulation is gained through PTM interplay whereby modifications modulate the occurrence of other PTMs or act in combination. Integration of global acetylation, ubiquitination and tyrosine or serine/threonine phosphorylation datasets with protein interaction data identified hundreds of protein complexes that selectively accumulate each PTM, indicating coordinated targeting of specific molecular functions. A second layer of PTM coordination exists in these complexes, mediated by PTM integration (PTMi) spots. PTMi spots represent very dense modification patterns in disordered protein regions and showed an equally high mutation rate as functional protein domains in cancer, inferring equivocal importance for cellular functioning. Systematic PTMi spot identification highlighted more than 300 candidate proteins for combinatorial PTM regulation. This study reveals two global PTM coordination mechanisms and emphasizes dataset integration as requisite in proteomic PTM studies to better predict modification impact on cellular signaling.

Normal cellular functioning is maintained by a vast array of macro-molecular machines that control both core and specialised molecular tasks. These machines are in large part multi-subunit protein complexes that undergo regulation at multiple levels, from expression of requisite components to a vast array of post translational modifications (PTMs). PTMs such as phosphorylation, ubiquitination and acetylation currently number up to more than 100,000 in the human proteome yet how, or if, they coordinate remains poorly understood. Here we show two mechanisms of systematic modification coordination that likely combine to provide finer control of protein complex function. Firstly, individual modifications selectively target protein complexes to execute specific molecular functions. Secondly, highly modified subunits of these complexes further accumulate multiple distinct modifications and contain regions of dense modification patterns, termed PTM integration (PTMi) spots. Through multiple PTM inputs, PTMi spots represent key regions for integrating multiple signals within these complexes, allowing finer regulation of protein function. Here we highlight the large extent of coordinated PTM regulation of protein complexes, and hence cellular function. Systematic dataset integration revealed biological insight into PTM mediated cellular regulatory mechanisms and further provides a resource for future hypothesis-driven studies.

Exon-phase symmetry and intrinsic structural disorder promote modular evolution in the human genome

A key signature of module exchange in the genome is phase symmetry of exons, suggestive of exon shuffling events that occurred without disrupting translation reading frame. At the protein level, intrinsic structural disorder may be another key element because disordered regions often serve as functional elements that can be effectively integrated into a protein structure. Therefore, we asked whether exon-phase symmetry in the human genome and structural disorder in the human proteome are connected, signalling such evolutionary mechanisms in the assembly of multi-exon genes. We found an elevated level of structural disorder of regions encoded by symmetric exons and a preferred symmetry of exons encoding for mostly disordered regions (>70% predicted disorder). Alternatively spliced symmetric exons tend to correspond to the most disordered regions. The genes of mostly disordered proteins (>70% predicted disorder) tend to be assembled from symmetric exons, which often arise by internal tandem duplications. Preponderance of certain types of short motifs (e.g. SH3-binding motif) and domains (e.g. high-mobility group domains) suggests that certain disordered modules have been particularly effective in exon-shuffling events. Our observations suggest that structural disorder has facilitated modular assembly of complex genes in evolution of the human genome.

Searching for protein signatures using a multilevel alphabet

Short motifs are known to play diverse roles in proteins, such as in mediating the interactions with other molecules, binding to membranes, or conducting a specific biological function. Standard approaches currently employed to detect short motifs in proteins search for enrichment of amino acid motifs considering mostly the sequence information. Here, we presented a new approach to search for common motifs (protein signatures) which share both physicochemical and structural properties, looking simultaneously at different features. Our method takes as an input an amino acid sequence and translates it to a new alphabet that reflects its intrinsic structural and chemical properties. Using the MEME search algorithm, we identified the proteins signatures within subsets of protein which encompass common sequence and structural information. We demonstrated that we can detect enriched structural motifs, such as the amphipathic helix, from large datasets of linear sequences, as well as predicting common structural properties (such as disorder, surface accessibility, or secondary structures) of known functional-motifs. Finally, we applied the method to the yeast protein interactome and identified novel putative interacting motifs. We propose that our approach can be applied for de novo protein function prediction given either sequence or structural information.

Analysis of Molecular Recognition Features (MoRFs) in membrane proteins

Molecular Recognition Features (MoRFs) are defined as short, intrinsically disordered regions in proteins that undergo disorder-to-order transition upon binding to their partners. As their name suggests, they are implicated in molecular recognition, which serves as the initial step for protein-protein interactions. Membrane proteins constitute approximately 30% of fully sequenced proteomes and are responsible for a wide variety of cellular functions. The aim of the current study was to identify and analyze MoRFs in membrane proteins. Two datasets of MoRFs, transmembrane and peripheral membrane protein MoRFs, were constructed from the Protein Data Bank, and sequence, structural and functional analysis was performed. Characterization of our datasets revealed their unique compositional biases and membrane protein MoRFs were categorized depending on their secondary structure after the interaction with their partners. Moreover, the position of transmembrane protein MoRFs in relation with the protein's topology was determined. Further studies were focused on functional analyses of MoRF-containing proteins and MoRFs' partners, associating them with protein binding, regulation and cell signaling, indicating half of them as putative hubs in protein-protein interaction networks. In conclusion, we provide insights into the disorder-based protein-protein interactions involving membrane proteins.

Multifarious roles of intrinsic disorder in proteins illustrate its broad impact on plant biology

Intrinsically disordered proteins (IDPs) are highly abundant in eukaryotic proteomes. Plant IDPs play critical roles in plant biology and often act as integrators of signals from multiple plant regulatory and environmental inputs. Binding promiscuity and plasticity allow IDPs to interact with multiple partners in protein interaction networks and provide important functional advantages in molecular recognition through transient protein-protein interactions. Short interaction-prone segments within IDPs, termed molecular recognition features, represent potential binding sites that can undergo disorder-to-order transition upon binding to their partners. In this review, we summarize the evidence for the importance of IDPs in plant biology and evaluate the functions associated with intrinsic disorder in five different types of plant protein families experimentally confirmed as IDPs. Functional studies of these proteins illustrate the broad impact of disorder on many areas of plant biology, including abiotic stress, transcriptional regulation, light perception, and development. Based on the roles of disorder in the protein-protein interactions, we propose various modes of action for plant IDPs that may provide insight for future experimental approaches aimed at understanding the molecular basis of protein function within important plant pathways.

Tissue-specific alternative splicing remodels protein-protein interaction networks

Alternative splicing plays a key role in the expansion of proteomic and regulatory complexity, yet the functions of the vast majority of differentially spliced exons are not known. In this study, we observe that brain and other tissue-regulated exons are significantly enriched in flexible regions of proteins that likely form conserved interaction surfaces. These proteins participate in significantly more interactions in protein-protein interaction (PPI) networks than other proteins. Using LUMIER, an automated PPI assay, we observe that approximately one-third of analyzed neural-regulated exons affect PPIs. Inclusion of these exons stimulated and repressed different partner interactions at comparable frequencies. This assay further revealed functions of individual exons, including a role for a neural-specific exon in promoting an interaction between Bridging Integrator 1 (Bin1)/Amphiphysin II and Dynamin 2 (Dnm2) that facilitates endocytosis. Collectively, our results provide evidence that regulated alternative exons frequently remodel interactions to establish tissue-dependent PPI networks.

Evaluating caveolin interactions: do proteins interact with the caveolin scaffolding domain through a widespread aromatic residue-rich motif?

Caveolins are coat proteins of caveolae, small flask-shaped pits of the plasma membranes of most cells. Aside from roles in caveolae formation, caveolins recruit, retain and regulate many caveolae-associated signalling molecules. Caveolin-protein interactions are commonly considered to occur between a ∼20 amino acid region within caveolin, the caveolin scaffolding domain (CSD), and an aromatic-rich caveolin binding motif (CBM) on the binding partner (фXфXXXXф, фXXXXфXXф or фXфXXXXфXXф, where ф is an aromatic and X an unspecified amino acid). The CBM resembles a typical linear motif - a short, simple sequence independently evolved many times in different proteins for a specific function. Here we exploit recent improvements in bioinformatics tools and in our understanding of linear motifs to critically examine the role of CBMs in caveolin interactions. We find that sequences conforming to the CBM occur in 30% of human proteins, but find no evidence for their statistical enrichment in the caveolin interactome. Furthermore, sequence- and structure-based considerations suggest that CBMs do not have characteristics commonly associated with true interaction motifs. Analysis of the relative solvent accessible area of putative CBMs shows that the majority of their aromatic residues are buried within the protein and are thus unlikely to interact directly with caveolin, but may instead be important for protein structural stability. Together, these findings suggest that the canonical CBM may not be a common characteristic of caveolin-target interactions and that interfaces between caveolin and targets may be more structurally diverse than presently appreciated.

SLiMPrints: conservation-based discovery of functional motif fingerprints in intrinsically disordered protein regions

Large portions of higher eukaryotic proteomes are intrinsically disordered, and abundant evidence suggests that these unstructured regions of proteins are rich in regulatory interaction interfaces. A major class of disordered interaction interfaces are the compact and degenerate modules known as short linear motifs (SLiMs). As a result of the difficulties associated with the experimental identification and validation of SLiMs, our understanding of these modules is limited, advocating the use of computational methods to focus experimental discovery. This article evaluates the use of evolutionary conservation as a discriminatory technique for motif discovery. A statistical framework is introduced to assess the significance of relatively conserved residues, quantifying the likelihood a residue will have a particular level of conservation given the conservation of the surrounding residues. The framework is expanded to assess the significance of groupings of conserved residues, a metric that forms the basis of SLiMPrints (short linear motif fingerprints), a de novo motif discovery tool. SLiMPrints identifies relatively overconstrained proximal groupings of residues within intrinsically disordered regions, indicative of putatively functional motifs. Finally, the human proteome is analysed to create a set of highly conserved putative motif instances, including a novel site on translation initiation factor eIF2A that may regulate translation through binding of eIF4E.

Deciphering a global network of functionally associated post-translational modifications

This study is the first large-scale comparative analysis of multiple types of post-translational modifications in different eukaryotic species. The resulting network of co-evolving and functionally associated modifications reveals the global landscape of post-translational regulation.

In all, 115 149 non-redundant post-translational modifications (PTMs) of 13 different types were collected from 8 eukaryotes.

Comparison of evolution speed reveals that carboxylation is the most conserved while SUMOylation is the fastest evolving PTM type.

Co-evolution of PTM pairs that co-occur within proteins reveals a vastly interconnected global network of functionally associated PTM types in eukaryotes.

Central to the network of functionally associated PTM types appear phosphorylation, acetylation, ubiquitination and O-linked glycosylation that control both temporal events and processes that govern protein localization.

Various post-translational modifications (PTMs) fine-tune the functions of almost all eukaryotic proteins, and co-regulation of different types of PTMs has been shown within and between a number of proteins. Aiming at a more global view of the interplay between PTM types, we collected modifications for 13 frequent PTM types in 8 eukaryotes, compared their speed of evolution and developed a method for measuring PTM co-evolution within proteins based on the co-occurrence of sites across eukaryotes. As many sites are still to be discovered, this is a considerable underestimate, yet, assuming that most co-evolving PTMs are functionally associated, we found that PTM types are vastly interconnected, forming a global network that comprise in human alone >50 000 residues in about 6000 proteins. We predict substantial PTM type interplay in secreted and membrane-associated proteins and in the context of particular protein domains and short-linear motifs. The global network of co-evolving PTM types implies a complex and intertwined post-translational regulation landscape that is likely to regulate multiple functional states of many if not all eukaryotic proteins.

Detecting remote sequence homology in disordered proteins: discovery of conserved motifs in the N-termini of Mononegavirales phosphoproteins

Paramyxovirinae are a large group of viruses that includes measles virus and parainfluenza viruses. The viral Phosphoprotein (P) plays a central role in viral replication. It is composed of a highly variable, disordered N-terminus and a conserved C-terminus. A second viral protein alternatively expressed, the V protein, also contains the N-terminus of P, fused to a zinc finger. We suspected that, despite their high variability, the N-termini of P/V might all be homologous; however, using standard approaches, we could previously identify sequence conservation only in some Paramyxovirinae. We now compared the N-termini using sensitive sequence similarity search programs, able to detect residual similarities unnoticeable by conventional approaches. We discovered that all Paramyxovirinae share a short sequence motif in their first 40 amino acids, which we called soyuz1. Despite its short length (11-16aa), several arguments allow us to conclude that soyuz1 probably evolved by homologous descent, unlike linear motifs. Conservation across such evolutionary distances suggests that soyuz1 plays a crucial role and experimental data suggest that it binds the viral nucleoprotein to prevent its illegitimate self-assembly. In some Paramyxovirinae, the N-terminus of P/V contains a second motif, soyuz2, which might play a role in blocking interferon signaling. Finally, we discovered that the P of related Mononegavirales contain similarly overlooked motifs in their N-termini, and that their C-termini share a previously unnoticed structural similarity suggesting a common origin. Our results suggest several testable hypotheses regarding the replication of Mononegavirales and suggest that disordered regions with little overall sequence similarity, common in viral and eukaryotic proteins, might contain currently overlooked motifs (intermediate in length between linear motifs and disordered domains) that could be detected simply by comparing orthologous proteins.

Minimotif Miner 3.0: database expansion and significantly improved reduction of false-positive predictions from consensus sequences

Minimotif Miner (MnM available at http://minimotifminer.org or http://mnm.engr.uconn.edu) is an online database for identifying new minimotifs in protein queries. Minimotifs are short contiguous peptide sequences that have a known function in at least one protein. Here we report the third release of the MnM database which has now grown 60-fold to approximately 300,000 minimotifs. Since short minimotifs are by their nature not very complex we also summarize a new set of false-positive filters and linear regression scoring that vastly enhance minimotif prediction accuracy on a test data set. This online database can be used to predict new functions in proteins and causes of disease.

Exploiting publicly available biological and biochemical information for the discovery of novel short linear motifs

The function of proteins is often mediated by short linear segments of their amino acid sequence, called Short Linear Motifs or SLiMs, the identification of which can provide important information about a protein function. However, the short length of the motifs and their variable degree of conservation makes their identification hard since it is difficult to correctly estimate the statistical significance of their occurrence. Consequently, only a small fraction of them have been discovered so far. We describe here an approach for the discovery of SLiMs based on their occurrence in evolutionarily unrelated proteins belonging to the same biological, signalling or metabolic pathway and give specific examples of its effectiveness in both rediscovering known motifs and in discovering novel ones. An automatic implementation of the procedure, available for download, allows significant motifs to be identified, automatically annotated with functional, evolutionary and structural information and organized in a database that can be inspected and queried. An instance of the database populated with pre-computed data on seven organisms is accessible through a publicly available server and we believe it constitutes by itself a useful resource for the life sciences (http://www.biocomputing.it/modipath).

SLiMSearch 2.0: biological context for short linear motifs in proteins

Short, linear motifs (SLiMs) play a critical role in many biological processes. The SLiMSearch 2.0 (Short, Linear Motif Search) web server allows researchers to identify occurrences of a user-defined SLiM in a proteome, using conservation and protein disorder context statistics to rank occurrences. User-friendly output and visualizations of motif context allow the user to quickly gain insight into the validity of a putatively functional motif occurrence. For each motif occurrence, overlapping UniProt features and annotated SLiMs are displayed. Visualization also includes annotated multiple sequence alignments surrounding each occurrence, showing conservation and protein disorder statistics in addition to known and predicted SLiMs, protein domains and known post-translational modifications. In addition, enrichment of Gene Ontology terms and protein interaction partners are provided as indicators of possible motif function. All web server results are available for download. Users can search motifs against the human proteome or a subset thereof defined by Uniprot accession numbers or GO term. The SLiMSearch server is available at: http://bioware.ucd.ie/slimsearch2.html.