线性短模体：介导蛋白质相互作用的新模块

线性短模体是天然无序蛋白实现生物学功能的重要组件.线性短模体具有柔性结构和短小的序列,可以介导瞬时、可逆的蛋白质相互作用,并在发生相互作用时表现出杂泛性.随着实验技术的更新和预测手段的发展,越来越多的线性短模体被发现和重新定义,例如BH3线性短模体.本文重点总结了线性短模体在结构、生物学功能以及进化等方面的特点.对线性短模体功能的研究将为解析细胞信号转导网络、疾病靶标确认、新药发现等领域带来新的思路.     

SLiMDisc: short, linear motif discovery, correcting for common evolutionary descent

Many important interactions of proteins are facilitated by short, linear motifs (SLiMs) within a protein's primary sequence. Our aim was to establish robust methods for discovering putative functional motifs. The strongest evidence for such motifs is obtained when the same motifs occur in unrelated proteins, evolving by convergence. In practise, searches for such motifs are often swamped by motifs shared in related proteins that are identical by descent. Prediction of motifs among sets of biologically related proteins, including those both with and without detectable similarity, were made using the TEIRESIAS algorithm. The number of motif occurrences arising through common evolutionary descent were normalized based on treatment of BLAST local alignments. Motifs were ranked according to a score derived from the product of the normalized number of occurrences and the information content. The method was shown to significantly outperform methods that do not discount evolutionary relatedness, when applied to known SLiMs from a subset of the eukaryotic linear motif (ELM) database. An implementation of Multiple Spanning Tree weighting outperformed two other weighting schemes, in a variety of settings.     

Attributes of short linear motifs

Traditionally, protein-protein interactions were thought to be mediated by large, structured domains. However, it has become clear that the interactome comprises a wide range of binding interfaces with varying degrees of flexibility, ranging from rigid globular domains to disordered regions that natively lack structure. Enrichment for disorder in highly connected hub proteins and its correlation with organism complexity hint at the functional importance of disordered regions. Nevertheless, they have not yet been extensively characterised. Shifting the attention from globular domains to disordered regions of the proteome might bring us closer to elucidating the dense and complex connectivity of the interactome. An important class of disordered interfaces are the compact mono-partite, short linear motifs (SLiMs, or eukaryotic linear motifs (ELMs)). They are evolutionarily plastic and interact with relatively low affinity due to the limited number of residues that make direct contact with the binding partner. These features confer to SLiMs the ability to evolve convergently and mediate transient interactions, which is imperative to network evolution and to maintain robust cell signalling, respectively. The ability to discriminate biologically relevant SLiMs by means of different attributes will improve our understanding of the complexity of the interactome and aid development of bioinformatics tools for motif discovery. In this paper, the curated instances currently available in the Eukaryotic Linear Motif (ELM) database are analysed to provide a clear overview of the defining attributes of SLiMs. These analyses suggest that functional SLiMs have higher levels of conservation than their surrounding residues, frequently evolve convergently, preferentially occur in disordered regions and often form a secondary structure when bound to their interaction partner. These results advocate searching for small groupings of residues in disordered regions with higher relative conservation and a propensity to form the secondary structure. Finally, the most interesting conclusions are examined in regard to their functional consequences.     

A comparative study of short linear motif compositions of the influenza A virus ribonucleoproteins

Protein-protein interactions through short linear motifs (SLiMs) are an emerging concept that is different from interactions between globular domains. The SLiMs encode a functional interaction interface in a short (three to ten residues) poorly conserved sequence. This characteristic makes them much more likely to arise/disappear spontaneously via mutations, and they may be more evolutionarily labile than globular domains. The diversity of SLiM composition may provide functional diversity for a viral protein from different viral strains. This study is designed to determine the different SLiM compositions of ribonucleoproteins (RNPs) from influenza A viruses (IAVs) from different hosts and with different levels of virulence. The 96 consensus sequences (regular expressions) of SLiMs from the ELM server were used to conduct a comprehensive analysis of the 52,513 IAV RNP sequences. The SLiM compositions of RNPs from IAVs from different hosts and with different levels of virulence were compared. The SLiM compositions of 845 RNPs from highly virulent/pandemic IAVs were also analyzed. In total, 292 highly conserved SLiMs were found in RNPs regardless of the IAV host range. These SLiMs may be basic motifs that are essential for the normal functions of RNPs. Moreover, several SLiMs that are rare in seasonal IAV RNPs but are present in RNPs from highly virulent/pandemic IAVs were identified.The SLiMs identified in this study provide a useful resource for experimental virologists to study the interactions between IAV RNPs and host intracellular proteins. Moreover, the SLiM compositions of IAV RNPs also provide insights into signal transduction pathways and protein interaction networks with which IAV RNPs might be involved. Information about SLiMs might be useful for the development of anti-IAV drugs.     

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.

     

D-SLIMMER: domain-SLiM interaction motifs miner for sequence based protein-protein interaction data

Many biologically important protein-protein interactions (PPIs) have been found to be mediated by short linear motifs (SLiMs). These interactions are mediated by the binding of a protein domain, often with a nonlinear interaction interface, to a SLiM. We propose a method called D-SLIMMER to mine for SLiMs in PPI data on the basis of the interaction density between a nonlinear motif (i.e., a protein domain) in one protein and a SLiM in the other protein. Our results on a benchmark of 113 experimentally verified reference SLiMs showed that D-SLIMMER outperformed existing methods notably for discovering domain-SLiMs interaction motifs. To illustrate the significance of the SLiMs detected, we highlighted two SLiMs discovered from the PPI data by D-SLIMMER that are variants of the known ELM SLiM, as well as a literature-backed SLiM that is yet to be listed in the reference databases. We also presented a novel SLiM predicted by D-SLIMMER that was strongly supported by existing biological literatures. These examples showed that D-SLIMMER is able to find SLiMs that are biologically relevant.     

Interactome-wide prediction of short, disordered protein interaction motifs in humans

Many of the specific functions of intrinsically disordered protein segments are mediated by Short Linear Motifs (SLiMs) interacting with other proteins. Well known examples include SLiMs that interact with 14-3-3, PDZ, SH2, SH3, and WW domains but the true extent and diversity of SLiM-mediated interactions is largely unknown. Here, we attempt to expand our knowledge of human SLiMs by applying in silico SLiM prediction to the human interactome. Combining data from seven different interaction databases, we analysed approximately 6000 protein-centred and 1600 domain-centred human interaction datasets of 3+ unrelated proteins that interact with a common partner. Results were placed in context through comparison to randomised datasets of similar size and composition. The search returned thousands of evolutionarily conserved, intrinsically disordered occurrences of hundreds of significantly enriched recurring motifs, including many that have never been previously identified (). In addition to True Positive results for at least 25 different known SLiMs, a striking number of "off-target" proteins/domains also returned significantly enriched known motifs. Often, this was due to the non-independence of the datasets, with many proteins sharing interaction partners or contributing interactions to multiple domain datasets. The majority of these motif classes, however, were also found to be significantly enriched in one or more randomised datasets. This highlights the need for care when interpreting motif predictions of this nature but also raises the possibility that SLiM occurrences may be successfully identified independently of interaction data. Although not as compositionally biased as previous studies, patterns matching known SLiMs tended to cluster into a few large groups of similar sequence, while novel predictions tended to be more distinctive and less abundant. Whether this is due to ascertainment bias or a true functional composition bias of SLiMs is not clear and warrants further investigation.     

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.     

Yeast two-hybrid junk sequences contain selected linear motifs

Yeast two-hybrid (Y2H) screenings result in identification of many out-of-frame (OOF) clones that code for short (2-100 amino acids) peptides with no sequence homology to known proteins. We hypothesize that these peptides can reveal common short linear motifs (SLiMs) responsible for their selection. We present a new protocol to address this issue, using an existing SLIM detector (TEIRESIAS) as a base method, and applying filters derived from a mathematical model of SLiM selection in OOF clones. The model allows for initial analysis of likely presence of SLiM(s) in a collection of OOF sequences, assisting investigators with the decision of whether to invest resources in further analysis. If SLiM presence is detected, it estimates the length and number of amino acid residues involved in binding specificity and the amount of noise in the Y2H screen. We demonstrate that our model can double the prediction sensitivity of TEIRESIAS and improve its specificity from 0 to 1.0 on simulated data and apply the model to seven sets of experimentally derived OOF clones. Finally, we experimentally validate one SLiM found by our method, demonstrating its utility.     

A correlated motif approach for finding short linear motifs from protein interaction networks

Background  

An important class of interaction switches for biological circuits and disease pathways are short binding motifs. However, the biological experiments to find these binding motifs are often laborious and expensive. With the availability of protein interaction data, novel binding motifs can be discovered computationally: by applying standard motif extracting algorithms on protein sequence sets each interacting with either a common protein or a protein group with similar properties. The underlying assumption is that proteins with common interacting partners will share some common binding motifs. Although novel binding motifs have been discovered with such approach, it is not applicable if a protein interacts with very few other proteins or when prior knowledge of protein group is not available or erroneous. Experimental noise in input interaction data can further deteriorate the dismal performance of such approaches.     

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.     

Linear motifs: lost in (pre)translation

Pretranslational modification by alternative splicing, alternative promoter usage and RNA editing enables the production of multiple protein isoforms from a single gene. A large quantity of data now supports the notion that short linear motifs (SLiMs), which are protein interaction modules enriched within intrinsically disordered regions, are key for the functional diversification of these isoforms. The inclusion or removal of these SLiMs can switch the subcellular localisation of an isoform, promote cooperative associations, refine the affinity of an interaction, coordinate phase transitions within the cell, and even create isoforms of opposing function. This article discusses the novel functionality enabled by the addition or removal of SLiM-containing exons by pretranslational modifications, such as alternative splicing and alternative promoter usage, and how these alterations enable the creation and modulation of complex regulatory and signalling pathways.     

How viruses hijack cell regulation

Viruses, as obligate intracellular parasites, are the pathogens that have the most intimate relationship with their host, and as such, their genomes have been shaped directly by interactions with the host proteome. Every step of the viral life cycle, from entry to budding, is orchestrated through interactions with cellular proteins. Accordingly, viruses will hijack and manipulate these proteins utilising any achievable mechanism. Yet, the extensive interactions of viral proteomes has yielded a conundrum: how do viruses commandeer so many diverse pathways and processes, given the obvious spatial constraints imposed by their compact genomes? One important approach is slowly being revealed, the extensive mimicry of host protein short linear motifs (SLiMs).     

The MDMX Acidic Domain Uses Allovalency to Bind Both p53 and MDMX

Autoinhibition of p53 binding to MDMX requires two short-linear motifs (SLiMs) containing adjacent tryptophan (WW) and tryptophan-phenylalanine (WF) residues. NMR spectroscopy was used to show the WW and WF motifs directly compete for the p53 binding site on MDMX and circular dichroism spectroscopy was used to show the WW motif becomes helical when it is bound to the p53 binding domain (p53BD) of MDMX. Binding studies using isothermal titration calorimetry showed the WW motif is a stronger inhibitor of p53 binding than the WF motif when they are both tethered to p53BD by the natural disordered linker. We also investigated how the WW and WF motifs interact with the DNA binding domain (DBD) of p53. Both motifs bind independently to similar sites on DBD that overlap the DNA binding site. Taken together our work defines a model for complex formation between MDMX and p53 where a pair of disordered SLiMs bind overlapping sites on both proteins.     

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. Proteins 2013; © 2012 Wiley Periodicals, Inc.     

Design and Evaluation of Antimalarial Peptides Derived from Prediction of Short Linear Motifs in Proteins Related to Erythrocyte Invasion

The purpose of this study was to investigate the blood stage of the malaria causing parasite, Plasmodium falciparum, to predict potential protein interactions between the parasite merozoite and the host erythrocyte and design peptides that could interrupt these predicted interactions. We screened the P. falciparum and human proteomes for computationally predicted short linear motifs (SLiMs) in cytoplasmic portions of transmembrane proteins that could play roles in the invasion of the erythrocyte by the merozoite, an essential step in malarial pathogenesis. We tested thirteen peptides predicted to contain SLiMs, twelve of them palmitoylated to enhance membrane targeting, and found three that blocked parasite growth in culture by inhibiting the initiation of new infections in erythrocytes. Scrambled peptides for two of the most promising peptides suggested that their activity may be reflective of amino acid properties, in particular, positive charge. However, one peptide showed effects which were stronger than those of scrambled peptides. This was derived from human red blood cell glycophorin-B. We concluded that proteome-wide computational screening of the intracellular regions of both host and pathogen adhesion proteins provides potential lead peptides for the development of anti-malarial compounds.     

GlobPlot: Exploring protein sequences for globularity and disorder

A major challenge in the proteomics and structural genomics era is to predict protein structure and function, including identification of those proteins that are partially or wholly unstructured. Non-globular sequence segments often contain short linear peptide motifs (e.g. SH3-binding sites) which are important for protein function. We present here a new tool for discovery of such unstructured, or disordered regions within proteins. GlobPlot (http://globplot.embl.de) is a web service that allows the user to plot the tendency within the query protein for order/globularity and disorder. We show examples with known proteins where it successfully identifies inter-domain segments containing linear motifs, and also apparently ordered regions that do not contain any recognised domain. GlobPlot may be useful in domain hunting efforts. The plots indicate that instances of known domains may often contain additional N- or C-terminal segments that appear ordered. Thus GlobPlot may be of use in the design of constructs corresponding to globular proteins, as needed for many biochemical studies, particularly structural biology. GlobPlot has a pipeline interface--GlobPipe--for the advanced user to do whole proteome analysis. GlobPlot can also be used as a generic infrastructure package for graphical displaying of any possible propensity.