Linear motifs: lost in (pre)translation

Leveraging machine learning models for peptide-protein interaction prediction

Peptides play a pivotal role in a wide range of biological activities through participating in up to 40% protein-protein interactions in cellular processes. They also demonstrate remarkable specificity and efficacy, making them promising candidates for drug development. However, predicting peptide-protein complexes by traditional computational approaches, such as docking and molecular dynamics simulations, still remains a challenge due to high computational cost, flexible nature of peptides, and limited structural information of peptide-protein complexes. In recent years, the surge of available biological data has given rise to the development of an increasing number of machine learning models for predicting peptide-protein interactions. These models offer efficient solutions to address the challenges associated with traditional computational approaches. Furthermore, they offer enhanced accuracy, robustness, and interpretability in their predictive outcomes. This review presents a comprehensive overview of machine learning and deep learning models that have emerged in recent years for the prediction of peptide-protein interactions.

Protein structure-function continuum model: Emerging nexuses between specificity, evolution, and structure

The rationale for replacing the old binary of structure-function with the trinity of structure, disorder, and function has gained considerable ground in recent years. A continuum model based on the expanded form of the existing paradigm can now subsume importance of both conformational flexibility and intrinsic disorder in protein function. The disorder is actually critical for understanding the protein-protein interactions in many regulatory processes, formation of membrane-less organelles, and our revised notions of specificity as amply illustrated by moonlighting proteins. While its importance in formation of amyloids and function of prions is often discussed, the roles of intrinsic disorder in infectious diseases and protein function under extreme conditions are also becoming clear. This review is an attempt to discuss how our current understanding of protein function, specificity, and evolution fit better with the continuum model. This integration of structure and disorder under a single model may bring greater clarity in our continuing quest for understanding proteins and molecular mechanisms of their functionality.

The function of alternative splicing in the proteome: rewiring protein interactomes to put old functions into new contexts

Alternative splicing affects more than 95% of multi-exon genes in the human genome. These changes affect the proteome in a myriad of ways. Here, we review our understanding of the breadth of these changes from their effect on protein structure to their influence on interactions. These changes encompass effects on nucleic acid binding in the nucleus to protein-carbohydrate interactions in the extracellular milieu, altering interactions involving all major classes of biological molecules. Protein isoforms have profound influences on cellular and tissue physiology, for example, by shaping neuronal connections, enhancing insulin secretion by pancreatic beta cells and allowing for alternative viral defense strategies in stem cells. More broadly, alternative splicing enables repurposing proteins from one context to another and thereby contributes to both the evolution of new traits as well as the creation of disease-specific interactomes that drive pathological phenotypes. In this Review, we highlight this universal character of alternative splicing as a central regulator of protein function with implications for almost every biological process.

PepCNN deep learning tool for predicting peptide binding residues in proteins using sequence, structural, and language model features

Protein-peptide interactions play a crucial role in various cellular processes and are implicated in abnormal cellular behaviors leading to diseases such as cancer. Therefore, understanding these interactions is vital for both functional genomics and drug discovery efforts. Despite a significant increase in the availability of protein-peptide complexes, experimental methods for studying these interactions remain laborious, time-consuming, and expensive. Computational methods offer a complementary approach but often fall short in terms of prediction accuracy. To address these challenges, we introduce PepCNN, a deep learning-based prediction model that incorporates structural and sequence-based information from primary protein sequences. By utilizing a combination of half-sphere exposure, position specific scoring matrices from multiple-sequence alignment tool, and embedding from a pre-trained protein language model, PepCNN outperforms state-of-the-art methods in terms of specificity, precision, and AUC. The PepCNN software and datasets are publicly available at https://github.com/abelavit/PepCNN.git .

Computational Prediction of Protein Intrinsically Disordered Region Related Interactions and Functions

Intrinsically Disordered Proteins (IDPs) and Regions (IDRs) exist widely. Although without well-defined structures, they participate in many important biological processes. In addition, they are also widely related to human diseases and have become potential targets in drug discovery. However, there is a big gap between the experimental annotations related to IDPs/IDRs and their actual number. In recent decades, the computational methods related to IDPs/IDRs have been developed vigorously, including predicting IDPs/IDRs, the binding modes of IDPs/IDRs, the binding sites of IDPs/IDRs, and the molecular functions of IDPs/IDRs according to different tasks. In view of the correlation between these predictors, we have reviewed these prediction methods uniformly for the first time, summarized their computational methods and predictive performance, and discussed some problems and perspectives.

Prediction of protein-protein interaction sites in intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) participate in many biological processes by interacting with other proteins, including the regulation of transcription, translation, and the cell cycle. With the increasing amount of disorder sequence data available, it is thus crucial to identify the IDP binding sites for functional annotation of these proteins. Over the decades, many computational approaches have been developed to predict protein-protein binding sites of IDP (IDP-PPIS) based on protein sequence information. Moreover, there are new IDP-PPIS predictors developed every year with the rapid development of artificial intelligence. It is thus necessary to provide an up-to-date overview of these methods in this field. In this paper, we collected 30 representative predictors published recently and summarized the databases, features and algorithms. We described the procedure how the features were generated based on public data and used for the prediction of IDP-PPIS, along with the methods to generate the feature representations. All the predictors were divided into three categories: scoring functions, machine learning-based prediction, and consensus approaches. For each category, we described the details of algorithms and their performances. Hopefully, our manuscript will not only provide a full picture of the status quo of IDP binding prediction, but also a guide for selecting different methods. More importantly, it will shed light on the inspirations for future development trends and principles.

Correlating multi-functional role of cold shock domain proteins with intrinsically disordered regions

Cold shock proteins (CSPs) are an ancient and conserved family of proteins. They are renowned for their role in response to low-temperature stress in bacteria and nucleic acid binding activities. In prokaryotes, cold and non-cold inducible CSPs are involved in various cellular and metabolic processes such as growth and development, osmotic oxidation, starvation, stress tolerance, and host cell invasion. In prokaryotes, cold shock condition reduces cell transcription and translation efficiency. Eukaryotic cold shock domain (CSD) proteins are evolved form of prokaryotic CSPs where CSD is flanked by N- and C-terminal domains. Eukaryotic CSPs are multi-functional proteins. CSPs also act as nucleic acid chaperons by preventing the formation of secondary structures in mRNA at low temperatures. In human, CSD proteins play a crucial role in the progression of breast cancer, colon cancer, lung cancer, and Alzheimer's disease. A well-defined three-dimensional structure of intrinsically disordered regions of CSPs family members is still undetermined. In this article, intrinsic disorder regions of CSPs have been explored systematically to understand the pleiotropic role of the cold shock family of proteins.

Predicting protein-peptide binding residues via interpretable deep learning

 

Identifying the protein-peptide binding residues is fundamentally important to understand the mechanisms of protein functions and explore drug discovery. Although several computational methods have been developed, they highly rely on third-party tools or information for feature design, easily resulting in low computational efficacy and suffering from low predictive performance. To address the limitations, we propose PepBCL, a novel BERT (Bidirectional Encoder Representation from Transformers)-based Contrastive Learning framework to predict the protein-Peptide binding residues based on protein sequences only. PepBCL is an end-to-end predictive model that is independent of designed features. Specifically, we introduce a well pre-trained protein language model that can automatically extract and learn high-latent representations of protein sequences relevant for protein structure and functions. Further, we design a novel contrastive learning module to optimize the feature representations of binding residues underlying the imbalanced dataset. We demonstrate that our proposed method significantly outperforms the state-of-the-art methods under benchmarking comparison, and achieves more robust performance. Moreover, we found that we further improve the performance via the integration of traditional features and our learnt features. Our results highlight the flexibility and adaptability of deep learning-based protein language model to capture both conserved and non-conserved sequential characteristics of peptide-binding residues. Interestingly, we demonstrate that peptide-binding residues in local sequential regions have more specific sequential patterns as compared with other protein-ligand binding residues, which potentially provides functional difference. Finally, to facilitate the use of our method, we establish an online predictive platform as the implementation of the proposed PepBCL, which is now available at http://server.wei-group.net/PepBCL/.

AVAILABILITY

https://github.com/Ruheng-W/PepBCL.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Databases for intrinsically disordered proteins

Intrinsically disordered regions (IDRs) lacking a fixed three-dimensional protein structure are widespread and play a central role in cell regulation. Only a small fraction of IDRs have been functionally characterized, with heterogeneous experimental evidence that is largely buried in the literature. Predictions of IDRs are still difficult to estimate and are poorly characterized. Here, an overview of the publicly available knowledge about IDRs is reported, including manually curated resources, deposition databases and prediction repositories. The types, scopes and availability of the various resources are analyzed, and their complementarity and overlap are highlighted. The volume of information included and the relevance to the field of structural biology are compared.

Identification of a Putative DNA-Binding Protein in Arabidopsis That Acts as a Susceptibility Hub and Interacts With Multiple Pseudomonas syringae Effectors

Phytopathogens use secreted effector proteins to suppress host immunity and promote pathogen virulence, and there is increasing evidence that the host-pathogen interactome comprises a complex network. To identify novel interactors of the Pseudomonas syringae effector HopZ1a, we performed a yeast two-hybrid screen that identified a previously uncharacterized Arabidopsis protein that we designate HopZ1a interactor 1 (ZIN1). Additional analyses in yeast and in planta revealed that ZIN1 also interacts with several other P. syringae effectors. We show that an Arabidopsis loss-of-function zin1 mutant is less susceptible to infection by certain strains of P. syringae, while overexpression of ZIN1 results in enhanced susceptibility. Functionally, ZIN1 exhibits topoisomerase-like activity in vitro. Transcriptional profiling of wild-type and zin1 Arabidopsis plants inoculated with P. syringae indicated that while ZIN1 regulates a wide range of pathogen-responsive biological processes, the list of genes more highly expressed in zin1 versus wild-type plants is particularly enriched for ribosomal protein genes. Altogether, these data illuminate ZIN1 as a potential susceptibility hub that interacts with multiple effectors to influence the outcome of plant-microbe interactions.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Arabidopsis Abscisic Acid Repressor 1 is a susceptibility hub that interacts with multiple Pseudomonas syringae effectors

Pathogens secrete effector proteins into host cells to suppress host immunity and promote pathogen virulence, although many features at the molecular interface of host-pathogen interactions remain to be characterized. In a yeast two-hybrid assay, we found that the Pseudomonas syringae effector HopZ1a interacts with the Arabidopsis transcriptional regulator Abscisic Acid Repressor 1 (ABR1). Further analysis revealed that ABR1 interacts with multiple P. syringae effectors, suggesting that it may be targeted as a susceptibility hub. Indeed, loss-of-function abr1 mutants exhibit reduced susceptibility to a number of P. syringae strains. The ABR1 protein comprises a conserved APETALA2 (AP2) domain flanked by long regions of predicted structural disorder. We verified the DNA-binding activity of the AP2 domain and demonstrated that the disordered domains act redundantly to enhance DNA binding and to facilitate transcriptional activation by ABR1. Finally, we compared gene expression profiles from wild-type and abr1 plants following inoculation with P. syringae, which suggested that the reduced susceptibility of abr1 mutants is due to the loss of a virulence target rather than an enhanced immune response. These data highlight ABR1 as a functionally important component at the host-pathogen interface.

MobiDB: intrinsically disordered proteins in 2021

The MobiDB database (URL: https://mobidb.org/) provides predictions and annotations for intrinsically disordered proteins. Here, we report recent developments implemented in MobiDB version 4, regarding the database format, with novel types of annotations and an improved update process. The new website includes a re-designed user interface, a more effective search engine and advanced API for programmatic access. The new database schema gives more flexibility for the users, as well as simplifying the maintenance and updates. In addition, the new entry page provides more visualisation tools including customizable feature viewer and graphs of the residue contact maps. MobiDB v4 annotates the binding modes of disordered proteins, whether they undergo disorder-to-order transitions or remain disordered in the bound state. In addition, disordered regions undergoing liquid-liquid phase separation or post-translational modifications are defined. The integrated information is presented in a simplified interface, which enables faster searches and allows large customized datasets to be downloaded in TSV, Fasta or JSON formats. An alternative advanced interface allows users to drill deeper into features of interest. A new statistics page provides information at database and proteome levels. The new MobiDB version presents state-of-the-art knowledge on disordered proteins and improves data accessibility for both computational and experimental users.

Functions of short lifetime biological structures at large: the case of intrinsically disordered proteins

Although for more than a century a protein function was intimately associated with the presence of unique structure in a protein molecule, recent years witnessed a skyrocket rise of the appreciation of protein intrinsic disorder concept that emphasizes the importance of the biologically active proteins without ordered structures. In different proteins, the depth and breadth of disorder penetrance are different, generating an amusing spatiotemporal heterogeneity of intrinsically disordered proteins (IDPs) and intrinsically disordered protein region regions (IDPRs), which are typically described as highly dynamic ensembles of rapidly interconverting conformations (or a multitude of short lifetime structures). IDPs/IDPRs constitute a substantial part of protein kingdom and have unique functions complementary to functional repertoires of ordered proteins. They are recognized as interaction specialists and global controllers that play crucial roles in regulation of functions of their binding partners and in controlling large biological networks. IDPs/IDPRs are characterized by immense binding promiscuity and are able to use a broad spectrum of binding modes, often resulting in the formation of short lifetime complexes. In their turn, functions of IDPs and IDPRs are controlled by various means, such as numerous posttranslational modifications and alternative splicing. Some of the functions of IDPs/IDPRs are briefly considered in this review to shed some light on the biological roles of short-lived structures at large.

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.

Alternative Splicing of Disabled-1 Controls Multipolar-to-Bipolar Transition of Migrating Neurons in the Neocortex

Multipolar-to-bipolar transition (MBT) is crucial for the neuronal migration and positioning in the neocortex. Reelin-Disabled-1 (Dab1) signaling plays a pivotal role in neuronal migration, yet how Dab1 coordinatively regulates downstream molecules to affect MBT remains unclear. We have previously found that alternative splicing produces multiple Dab1 isoforms with different tyrosine motifs and differential ability to recruit downstream effectors. Here, we report that splicing of Dab1 exons 7 and 8 and 9bc dynamically regulates the inclusion and activities of Dab1 tyrosine motifs in the neocortex. By in utero electroporation, we show that expression of Dab1 isoforms missing exons 7 and 8 or retaining exons 9bc in WT neurons resulted in neuronal migration defects with attenuated Dab1 tyrosine phosphorylation, disrupted leading process extension, and disorientated multipolar neurons in the multipolar accumulation zone. Introducing the canonical Dab1 form, but not those missing exons 7 and 8 or retaining exons 9bc, into Dab1-deficient neurons promoted MBT and rescued neuronal migration defects, suggesting that alternative splicing of Dab1 modulates the tyrosine motif switch and mediates MBT of cortical neurons. Our study reveals a critical mechanism by which Dab1 alternative splicing coordinately controls MBT and neuronal migration in a spatiotemporal manner.

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.

Co-Evolution of Intrinsically Disordered Proteins with Folded Partners Witnessed by Evolutionary Couplings

Although improved strategies for the detection and analysis of evolutionary couplings (ECs) between protein residues already enable the prediction of protein structures and interactions, they are mostly restricted to conserved and well-folded proteins. Whereas intrinsically disordered proteins (IDPs) are central to cellular interaction networks, due to the lack of strict structural constraints, they undergo faster evolutionary changes than folded domains. This makes the reliable identification and alignment of IDP homologs difficult, which led to IDPs being omitted in most large-scale residue co-variation analyses. By preforming a dedicated analysis of phylogenetically widespread bacterial IDP–partner interactions, here we demonstrate that partner binding imposes constraints on IDP sequences that manifest in detectable interprotein ECs. These ECs were not detected for interactions mediated by short motifs, rather for those with larger IDP–partner interfaces. Most identified coupled residue pairs reside close (<10 Å) to each other on the interface, with a third of them forming multiple direct atomic contacts. EC-carrying interfaces of IDPs are enriched in negatively charged residues, and the EC residues of both IDPs and partners preferentially reside in helices. Our analysis brings hope that IDP–partner interactions difficult to study could soon be successfully dissected through residue co-variation analysis.

Intrinsically disordered N-terminal domain of the Helicoverpa armigera Ultraspiracle stabilizes the dimeric form via a scorpion-like structure

Nuclear receptors (NRs) are a family of ligand-dependent transcription factors activated by lipophilic compounds. NRs share a common structure comprising three domains: a variable N-terminal domain (NTD), a highly conserved globular DNA-binding domain and a ligand-binding domain. There are numerous papers describing the molecular details of the latter two globular domains. However, very little is known about the structure-function relationship of the NTD, especially as an intrinsically disordered fragment of NRs that may influence the molecular properties and, in turn, the function of globular domains. Here, we investigated whether and how an intrinsically disordered NTD consisting of 58 amino acid residues affects the functions of the globular domains of the Ultraspiracle protein from Helicoverpa armigera (HaUsp). The role of the NTD was examined for two well-known and easily testable NR functions, i.e., interactions with specific DNA sequences and dimerization. Electrophoretic mobility shift assays showed that the intrinsically disordered NTD influences the interaction of HaUsp with specific DNA sequences, apparently by destabilization of HaUsp-DNA complexes. On the other hand, multi-angle light scattering and sedimentation velocity analytical ultracentrifugation revealed that the NTD acts as a structural element that stabilizes HaUsp homodimers. Molecular models based on small-angle X-ray scattering indicate that the intrinsically disordered NTD may exert its effects on the tested HaUsp functions by forming an unexpected scorpion-like structure, in which the NTD bends towards the ligand-binding domain in each subunit of the HaUsp homodimer. This structure may be crucial for specific NTD-dependent regulation of the functions of globular domains in NRs.

How alternative splicing affects membrane-trafficking dynamics

The cell biology field has outstanding working knowledge of the fundamentals of membrane-trafficking pathways, which are of critical importance in health and disease. Current challenges include understanding how trafficking pathways are fine-tuned for specialized tissue functions in vivo and during development. In parallel, the ENCODE project and numerous genetic studies have revealed that alternative splicing regulates gene expression in tissues and throughout development at a post-transcriptional level. This Review summarizes recent discoveries demonstrating that alternative splicing affects tissue specialization and membrane-trafficking proteins during development, and examines how this regulation is altered in human disease. We first discuss how alternative splicing of clathrin, SNAREs and BAR-domain proteins influences endocytosis, secretion and membrane dynamics, respectively. We then focus on the role of RNA-binding proteins in the regulation of splicing of membrane-trafficking proteins in health and disease. Overall, our aim is to comprehensively summarize how trafficking is molecularly influenced by alternative splicing and identify future directions centered on its physiological relevance.

Relating protein functional diversity to cell type number identifies genes that determine dynamic aspects of chromatin organisation as potential contributors to organismal complexity

Organismal complexity broadly relates to the number of different cell types within an organism and generally increases across a phylogeny. Whilst gene expression will underpin organismal complexity, it has long been clear that a simple count of gene number is not a sufficient explanation. In this paper, we use open-access information from the Ensembl databases to quantify the functional diversity of human genes that are broadly involved in transcription. Functional diversity is described in terms of the numbers of paralogues, protein isoforms and structural domains for each gene. The change in functional diversity is then calculated for up to nine orthologues from the nematode worm to human and correlated to the change in cell-type number. Those with the highest correlation are subject to gene ontology term enrichment and interaction analyses. We found that a range of genes that encode proteins associated with dynamic changes to chromatin are good candidates to contribute to organismal complexity.

The contribution of intrinsically disordered regions to protein function, cellular complexity, and human disease

In the 1960s, Christian Anfinsen postulated that the unique three-dimensional structure of a protein is determined by its amino acid sequence. This work laid the foundation for the sequence–structure–function paradigm, which states that the sequence of a protein determines its structure, and structure determines function. However, a class of polypeptide segments called intrinsically disordered regions does not conform to this postulate. In this review, I will first describe established and emerging ideas about how disordered regions contribute to protein function. I will then discuss molecular principles by which regulatory mechanisms, such as alternative splicing and asymmetric localization of transcripts that encode disordered regions, can increase the functional versatility of proteins. Finally, I will discuss how disordered regions contribute to human disease and the emergence of cellular complexity during organismal evolution.

The ribosome-engaged landscape of alternative splicing

High-throughput RNA sequencing (RNA-seq) has revealed an enormous complexity of alternative splicing (AS) across diverse cell and tissue types. However, it is currently unknown to what extent repertoires of splice-variant transcripts are translated into protein products. Here, we surveyed AS events engaged by the ribosome. Notably, at least 75% of human exon-skipping events detected in transcripts with medium-to-high abundance in RNA-seq data were also detected in ribosome profiling data. Furthermore, relatively small subsets of functionally related splice variants are engaged by ribosomes at levels that do not reflect their absolute abundance, thus indicating a role for AS in modulating translational output. This mode of regulation is associated with control of the mammalian cell cycle. Our results thus suggest that a major fraction of splice variants is translated and that specific cellular functions including cell-cycle control are subject to AS-dependent modulation of translation output.

Extent of pre-translational regulation for the control of nucleocytoplasmic protein localization

Background

Appropriate protein subcellular localization is essential for proper cellular function. Central to the regulation of protein localization are protein targeting motifs, stretches of amino acids serving as guides for protein entry in a specific cellular compartment. While the use of protein targeting motifs is modulated in a post-translational manner, mainly by protein conformational changes and post-translational modifications, the presence of these motifs in proteins can also be regulated in a pre-translational manner. Here, we investigate the extent of pre-translational regulation of the main signals controlling nucleo-cytoplasmic traffic: the nuclear localization signal (NLS) and the nuclear export signal (NES).

Results

Motif databases and manual curation of the literature allowed the identification of 175 experimentally validated NLSs and 120 experimentally validated NESs in human. Following mapping onto annotated transcripts, these motifs were found to be modular, most (73 % for NLS and 88 % for NES) being encoded entirely in only one exon. The presence of a majority of these motifs is regulated in an alternative manner at the transcript level (61 % for NLS and 72 % for NES) while the remaining motifs are present in all coding isoforms of their encoding gene. NLSs and NESs are pre-translationally regulated using four main mechanisms: alternative transcription/translation initiation, alternative translation termination, alternative splicing of the exon encoding the motif and frameshift, the first two being by far the most prevalent mechanisms. Quantitative analysis of the presence of these motifs using RNA-seq data indicates that inclusion of these motifs can be regulated in a tissue-specific and a combinatorial manner, can be altered in disease states in a directed way and that alternative inclusion of these motifs is often used by proteins with diverse interactors and roles in diverse pathways, such as kinases.

Conclusions

The pre-translational regulation of the inclusion of protein targeting motifs is a prominent and tightly-regulated mechanism that adds another layer in the control of protein subcellular localization.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2854-4) contains supplementary material, which is available to authorized users.

MoRFchibi SYSTEM: software tools for the identification of MoRFs in protein sequences

Molecular recognition features, MoRFs, are short segments within longer disordered protein regions that bind to globular protein domains in a process known as disorder-to-order transition. MoRFs have been found to play a significant role in signaling and regulatory processes in cells. High-confidence computational identification of MoRFs remains an important challenge. In this work, we introduce MoRFchibi SYSTEM that contains three MoRF predictors: MoRFCHiBi, a basic predictor best suited as a component in other applications, MoRFCHiBi_ Light, ideal for high-throughput predictions and MoRFCHiBi_ Web, slower than the other two but best for high accuracy predictions. Results show that MoRFchibi SYSTEM provides more than double the precision of other predictors. MoRFchibi SYSTEM is available in three different forms: as HTML web server, RESTful web server and downloadable software at: http://www.chibi.ubc.ca/faculty/joerg-gsponer/gsponer-lab/software/morf_chibi/.

Short linear motif acquisition, exon formation and alternative splicing determine a pathway to diversity for NCoR-family co-repressors

Vertebrate NCoR-family co-repressors play central roles in the timing of embryo and stem cell differentiation by repressing the activity of a range of transcription factors. They interact with nuclear receptors using short linear motifs (SLiMs) termed co-repressor for nuclear receptor (CoRNR) boxes. Here, we identify the pathway leading to increasing co-repressor diversity across the deuterostomes. The final complement of CoRNR boxes arose in an ancestral cephalochordate, and was encoded in one large exon; the urochordates and vertebrates then split this region between 10 and 12 exons. In Xenopus, alternative splicing is prevalent in NCoR2, but absent in NCoR1. We show for one NCoR1 exon that alternative splicing can be recovered by a single point mutation, suggesting NCoR1 lost the capacity for alternative splicing. Analyses in Xenopus and zebrafish identify that cellular context, rather than gene sequence, predominantly determines species differences in alternative splicing. We identify a pathway to diversity for the NCoR family beginning with the addition of a SLiM, followed by gene duplication, the generation of alternatively spliced isoforms and their differential deployment.

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.

Computational Identification of MoRFs in Protein Sequences Using Hierarchical Application of Bayes Rule

Motivation

Intrinsically disordered regions of proteins play an essential role in the regulation of various biological processes. Key to their regulatory function is often the binding to globular protein domains via sequence elements known as molecular recognition features (MoRFs). Development of computational tools for the identification of candidate MoRF locations in amino acid sequences is an important task and an area of growing interest. Given the relative sparseness of MoRFs in protein sequences, the accuracy of the available MoRF predictors is often inadequate for practical usage, which leaves a significant need and room for improvement. In this work, we introduce MoRF_{CHiBi_Web}, which predicts MoRF locations in protein sequences with higher accuracy compared to current MoRF predictors.

Methods

Three distinct and largely independent property scores are computed with component predictors and then combined to generate the final MoRF propensity scores. The first score reflects the likelihood of sequence windows to harbour MoRFs and is based on amino acid composition and sequence similarity information. It is generated by MoRF_CHiBi using small windows of up to 40 residues in size. The second score identifies long stretches of protein disorder and is generated by ESpritz with the DisProt option. Lastly, the third score reflects residue conservation and is assembled from PSSM files generated by PSI-BLAST. These propensity scores are processed and then hierarchically combined using Bayes rule to generate the final MoRF_{CHiBi_Web} predictions.

Results

MoRF_{CHiBi_Web} was tested on three datasets. Results show that MoRF_{CHiBi_Web} outperforms previously developed predictors by generating less than half the false positive rate for the same true positive rate at practical threshold values. This level of accuracy paired with its relatively high processing speed makes MoRF_{CHiBi_Web} a practical tool for MoRF prediction.

Availability

http://morf.chibi.ubc.ca:8080/morf/.

The Bcl-2 family: structures, interactions and targets for drug discovery

Two phylogenetically and structurally distinct groups of proteins regulate stress induced intrinsic apoptosis, the programmed disassembly of cells. Together they form the B cell lymphoma-2 (Bcl-2) family. Bcl-2 proteins appeared early in metazoan evolution and are identified by the presence of up to four short conserved sequence blocks known as Bcl-2 homology (BH) motifs, or domains. The simple BH3-only proteins bear only a BH3-motif and are intrinsically disordered proteins and antagonize or activate the other group, the multi-motif Bcl-2 proteins that have up to four BH motifs, BH1-BH4. Multi-motif Bcl-2 proteins are either pro-survival or pro-apoptotic in action and have remarkably similar α-helical bundle structures that provide a binding groove formed from the BH1, BH2, and BH3-motifs for their BH3-bearing antagonists. In mammals a network of interactions between Bcl-2 members regulates mitochondrial outer membrane permeability (MOMP) and efflux of cytochrome c and other death inducing factors from mitochondria to initiate the apoptotic caspase cascade, but the molecular events leading to MOMP are uncertain. Dysregulation of the Bcl-2 family occurs in many diseases and pathogenic viruses have assimilated pro-survival Bcl-2 proteins to evade immune responses. Their role in disease has made the Bcl-2 family the focus of drug design attempts and clinical trials are showing promise for 'BH3-mimics', drugs that mimic the ability of BH3-only proteins to neutralize selected pro-survival proteins to induce cell death in tumor cells. This review focuses on the structural biology of Bcl-2 family proteins, their interactions and attempts to harness them as targets for drug design.

Systematic transcriptome analysis reveals tumor-specific isoforms for ovarian cancer diagnosis and therapy

Tumor-specific molecules are needed across diverse areas of oncology for use in early detection, diagnosis, prognosis and therapy. Large and growing public databases of transcriptome sequencing data (RNA-seq) derived from tumors and normal tissues hold the potential of yielding tumor-specific molecules, but because the data are new they have not been fully explored for this purpose. We have developed custom bioinformatic algorithms and used them with 296 high-grade serous ovarian (HGS-OvCa) tumor and 1,839 normal RNA-seq datasets to identify mRNA isoforms with tumor-specific expression. We rank prioritized isoforms by likelihood of being expressed in HGS-OvCa tumors and not in normal tissues and analyzed 671 top-ranked isoforms by high-throughput RT-qPCR. Six of these isoforms were expressed in a majority of the 12 tumors examined but not in 18 normal tissues. An additional 11 were expressed in most tumors and only one normal tissue, which in most cases was fallopian or colon. Of the 671 isoforms, the topmost 5% (n = 33) ranked based on having tumor-specific or highly restricted normal tissue expression by RT-qPCR analysis are enriched for oncogenic, stem cell/cancer stem cell, and early development loci--including ETV4, FOXM1, LSR, CD9, RAB11FIP4, and FGFRL1. Many of the 33 isoforms are predicted to encode proteins with unique amino acid sequences, which would allow them to be specifically targeted for one or more therapeutic strategies--including monoclonal antibodies and T-cell-based vaccines. The systematic process described herein is readily and rapidly applicable to the more than 30 additional tumor types for which sufficient amounts of RNA-seq already exist.

Computational identification of MoRFs in protein sequences

MOTIVATION

Intrinsically disordered regions of proteins play an essential role in the regulation of various biological processes. Key to their regulatory function is the binding of molecular recognition features (MoRFs) to globular protein domains in a process known as a disorder-to-order transition. Predicting the location of MoRFs in protein sequences with high accuracy remains an important computational challenge.

METHOD

In this study, we introduce MoRFCHiBi, a new computational approach for fast and accurate prediction of MoRFs in protein sequences. MoRFCHiBi combines the outcomes of two support vector machine (SVM) models that take advantage of two different kernels with high noise tolerance. The first, SVMS, is designed to extract maximal information from the general contrast in amino acid compositions between MoRFs, their surrounding regions (Flanks), and the remainders of the sequences. The second, SVMT, is used to identify similarities between regions in a query sequence and MoRFs of the training set.

RESULTS

We evaluated the performance of our predictor by comparing its results with those of two currently available MoRF predictors, MoRFpred and ANCHOR. Using three test sets that have previously been collected and used to evaluate MoRFpred and ANCHOR, we demonstrate that MoRFCHiBi outperforms the other predictors with respect to different evaluation metrics. In addition, MoRFCHiBi is downloadable and fast, which makes it useful as a component in other computational prediction tools.

AVAILABILITY AND IMPLEMENTATION

http://www.chibi.ubc.ca/morf/.

Structural basis of protein-protein interactions

Regulated interactions between proteins govern signaling pathways within and between cells. Structural studies on protein complexes formed reversibly and/or transiently illustrate the remarkable diversity of interactions, both in terms of interfacial size and nature. In recent years, "domain-peptide" interactions have gained much greater recognition and may be viewed as both pre-translational and posttranslational-dependent functional switches. Our understanding of the multistep regulation of auto-inhibited multidomain proteins has also grown. Their activity may be understood as the "combinatorial" output of multiple input signals, including phosphorylation, location, and mechanical force. The prospects for bridging the gap between the new "systems biology" data and the traditional "reductionist" data are also discussed.

Protein moonlighting: a new factor in biology and medicine

The phenomenon of protein moonlighting was discovered in the 1980s and 1990s, and the current definition of what constitutes a moonlighting protein was provided at the end of the 1990s. Since this time, several hundred moonlighting proteins have been identified in all three domains of life, and the rate of discovery is accelerating as the importance of protein moonlighting in biology and medicine becomes apparent. The recent re-evaluation of the number of protein-coding genes in the human genome (approximately 19000) is one reason for believing that protein moonlighting may be a more general phenomenon than the current number of moonlighting proteins would suggest, and preliminary studies of the proportion of proteins that moonlight would concur with this hypothesis. Protein moonlighting could be one way of explaining the seemingly small number of proteins that are encoded in the human genome. It is emerging that moonlighting proteins can exhibit novel biological functions, thus extending the range of the human functional proteome. The several hundred moonlighting proteins so far discovered play important roles in many aspects of biology. For example, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), heat-shock protein 60 (Hsp60) and tRNA synthetases play a wide range of biological roles in eukaryotic cells, and a growing number of eukaryotic moonlighting proteins are recognized to play important roles in physiological processes such as sperm capacitation, implantation, immune regulation in pregnancy, blood coagulation, vascular regeneration and control of inflammation. The dark side of protein moonlighting finds a range of moonlighting proteins playing roles in various human diseases including cancer, cardiovascular disease, HIV and cystic fibrosis. However, some moonlighting proteins are being tested for their therapeutic potential, including immunoglobulin heavy-chain-binding protein (BiP), for rheumatoid arthritis, and Hsp90 for wound healing. In addition, it has emerged over the last 20 years that a large number of bacterial moonlighting proteins play important roles in bacteria–host interactions as virulence factors and are therefore potential therapeutic targets in bacterial infections. So as we progress in the 21st Century, it is likely that moonlighting proteins will be seen to play an increasingly important role in biology and medicine. It is hoped that some of the major unanswered questions, such as the mechanism of evolution of protein moonlighting, the structural biology of moonlighting proteins and their role in the systems biology of cellular systems can be addressed during this period.

A million peptide motifs for the molecular biologist

A molecular description of functional modules in the cell is the focus of many high-throughput studies in the postgenomic era. A large portion of biomolecular interactions in virtually all cellular processes is mediated by compact interaction modules, referred to as peptide motifs. Such motifs are typically less than ten residues in length, occur within intrinsically disordered regions, and are recognized and/or posttranslationally modified by structured domains of the interacting partner. In this review, we suggest that there might be over a million instances of peptide motifs in the human proteome. While this staggering number suggests that peptide motifs are numerous and the most understudied functional module in the cell, it also holds great opportunities for new discoveries.

Wrecked regulation of intrinsically disordered proteins in diseases: pathogenicity of deregulated regulators

Biologically active proteins without stable tertiary structure are common in all known proteomes. Functions of these intrinsically disordered proteins (IDPs) are typically related to regulation, signaling, and control. Cellular levels of these important regulators are tightly regulated by a variety mechanisms ranging from firmly controlled expression to precisely targeted degradation. Functions of IDPs are controlled by binding to specific partners, alternative splicing, and posttranslational modifications among other means. In the norm, right amounts of precisely activated IDPs have to be present in right time at right places. Wrecked regulation brings havoc to the ordered world of disordered proteins, leading to protein misfolding, misidentification, and missignaling that give rise to numerous human diseases, such as cancer, cardiovascular disease, neurodegenerative diseases, and diabetes. Among factors inducing pathogenic transformations of IDPs are various cellular mechanisms, such as chromosomal translocations, damaged splicing, altered expression, frustrated posttranslational modifications, aberrant proteolytic degradation, and defective trafficking. This review presents some of the aspects of deregulated regulation of IDPs leading to human diseases.

Comprehensive repertoire of foldable regions within whole genomes

In order to get a comprehensive repertoire of foldable domains within whole proteomes, including orphan domains, we developed a novel procedure, called SEG-HCA. From only the information of a single amino acid sequence, SEG-HCA automatically delineates segments possessing high densities in hydrophobic clusters, as defined by Hydrophobic Cluster Analysis (HCA). These hydrophobic clusters mainly correspond to regular secondary structures, which together form structured or foldable regions. Genome-wide analyses revealed that SEG-HCA is opposite of disorder predictors, both addressing distinct structural states. Interestingly, there is however an overlap between the two predictions, including small segments of disordered sequences, which undergo coupled folding and binding. SEG-HCA thus gives access to these specific domains, which are generally poorly represented in domain databases. Comparison of the whole set of SEG-HCA predictions with the Conserved Domain Database (CDD) also highlighted a wide proportion of predicted large (length >50 amino acids) segments, which are CDD orphan. These orphan sequences may either correspond to highly divergent members of already known families or belong to new families of domains. Their comprehensive description thus opens new avenues to investigate new functional and/or structural features, which remained so far uncovered. Altogether, the data described here provide new insights into the protein architecture and organization throughout the three kingdoms of life.

Spontaneous or induced folding into a specific 3D structure is a key property of proteins to perform their biological functions. Folded 3D structures of proteins perform specific functions, including interactions with other proteins. Intrinsically disordered regions also mediate interaction, gaining structure only when bound to a target protein. In both cases, hydrophobicity generally plays a major role in the protein segment “foldability”. Here, we developed an original procedure to identify foldable segments from only the information of a single amino acid sequence and to explore protein structures at a proteomic scale. Our approach goes beyond the simple consideration of mean hydrophobicity, by including the secondary structure information through the use of a two-dimensional transposition of the sequence. The developed procedure, combined with disorder predictors, may facilitate the specific identification of small segments that undergo coupled folding and binding. Combined with the analysis of specific domain databases, it also highlights orphan foldable segments, which remain yet uncharacterized.

Complexity of the alternative splicing landscape in plants

Alternative splicing (AS) of precursor mRNAs (pre-mRNAs) from multiexon genes allows organisms to increase their coding potential and regulate gene expression through multiple mechanisms. Recent transcriptome-wide analysis of AS using RNA sequencing has revealed that AS is highly pervasive in plants. Pre-mRNAs from over 60% of intron-containing genes undergo AS to produce a vast repertoire of mRNA isoforms. The functions of most splice variants are unknown. However, emerging evidence indicates that splice variants increase the functional diversity of proteins. Furthermore, AS is coupled to transcript stability and translation through nonsense-mediated decay and microRNA-mediated gene regulation. Widespread changes in AS in response to developmental cues and stresses suggest a role for regulated splicing in plant development and stress responses. Here, we review recent progress in uncovering the extent and complexity of the AS landscape in plants, its regulation, and the roles of AS in gene regulation. The prevalence of AS in plants has raised many new questions that require additional studies. New tools based on recent technological advances are allowing genome-wide analysis of RNA elements in transcripts and of chromatin modifications that regulate AS. Application of these tools in plants will provide significant new insights into AS regulation and crosstalk between AS and other layers of gene regulation.

Drift and conservation of differential exon usage across tissues in primate species

Alternative usage of exons provides genomes with plasticity to produce different transcripts from the same gene, modulating the function, localization, and life cycle of gene products. It affects most human genes. For a limited number of cases, alternative functions and tissue-specific roles are known. However, recent high-throughput sequencing studies have suggested that much alternative isoform usage across tissues is nonconserved, raising the question of the extent of its functional importance. We address this question in a genome-wide manner by analyzing the transcriptomes of five tissues for six primate species, focusing on exons that are 1:1 orthologous in all six species. Our results support a model in which differential usage of exons has two major modes: First, most of the exons show only weak differences, which are dominated by interspecies variability and may reflect neutral drift and noisy splicing. These cases dominate the genome-wide view and explain why conservation appears to be so limited. Second, however, a sizeable minority of exons show strong differences between tissues, which are mostly conserved. We identified a core set of 3,800 exons from 1,643 genes that show conservation of strongly tissue-dependent usage patterns from human at least to macaque. This set is enriched for exons encoding protein-disordered regions and untranslated regions. Our findings support the theory that isoform regulation is an important target of evolution in primates, and our method provides a powerful tool for discovering potentially functional tissue-dependent isoforms.

Structural disorder provides increased adaptability for vesicle trafficking pathways

Vesicle trafficking systems play essential roles in the communication between the organelles of eukaryotic cells and also between cells and their environment. Endocytosis and the late secretory route are mediated by clathrin-coated vesicles, while the COat Protein I and II (COPI and COPII) routes stand for the bidirectional traffic between the ER and the Golgi apparatus. Despite similar fundamental organizations, the molecular machinery, functions, and evolutionary characteristics of the three systems are very different. In this work, we compiled the basic functional protein groups of the three main routes for human and yeast and analyzed them from the structural disorder perspective. We found similar overall disorder content in yeast and human proteins, confirming the well-conserved nature of these systems. Most functional groups contain highly disordered proteins, supporting the general importance of structural disorder in these routes, although some of them seem to heavily rely on disorder, while others do not. Interestingly, the clathrin system is significantly more disordered (∼23%) than the other two, COPI (∼9%) and COPII (∼8%). We show that this structural phenomenon enhances the inherent plasticity and increased evolutionary adaptability of the clathrin system, which distinguishes it from the other two routes. Since multi-functionality (moonlighting) is indicative of both plasticity and adaptability, we studied its prevalence in vesicle trafficking proteins and correlated it with structural disorder. Clathrin adaptors have the highest capability for moonlighting while also comprising the most highly disordered members. The ability to acquire tissue specific functions was also used to approach adaptability: clathrin route genes have the most tissue specific exons encoding for protein segments enriched in structural disorder and interaction sites. Overall, our results confirm the general importance of structural disorder in vesicle trafficking and suggest major roles for this structural property in shaping the differences of evolutionary adaptability in the three routes.

Vesicle trafficking systems are fundamental among cellular transport mechanisms; various cargo molecules are transported via different coated vesicles to their specific destinations in every eukaryotic cell. Clathrin-coated vesicles mediate endocytosis and the late secretory route, while the COat Protein I and II (COPI and COPII) vesicle trafficking routes are responsible for the bidirectional traffic between the ER and the Golgi apparatus. Despite similar basic principles, regulatory mechanisms and structural features of the three systems, their molecular machinery, functions, and evolutionary characteristics vastly differ. We investigated and compared these three routes and their basic functional protein groups from the structural disorder point of view, since disordered protein regions could provide a broad variety of functional and evolutionary advantages for them. We found that structurally disordered protein segments are most abundant in the clathrin system, which might explain the observed inherent plasticity, increased adaptability and exceptional robustness of this route. We support our hypothesis by two analyses on protein multi-functionality and tissue specificity, both being indicative of evolutionary adaptability. Clathrin pathway proteins stand out in both measures, with their disordered regions being largely responsible for their outstanding capabilities.

Co-evolution of sphingomyelin and the ceramide transport protein CERT

Life creates many varieties of lipids. The choline-containing sphingophospholipid sphingomyelin (SM) exists ubiquitously or widely in vertebrates and lower animals, but is absent or rare in bacteria, fungi, protists, and plants. In the biosynthesis of SM, ceramide, which is synthesized in the endoplasmic reticulum, is transported to the Golgi region by the ceramide transport protein CERT, probably in a non-vesicular manner, and is then converted to SM by SM synthase, which catalyzes the reaction of phosphocholine transfer from phosphatidylcholine (PtdCho) to ceramide. Recent advances in genomics and lipidomics indicate that the phylogenetic occurrence of CERT and its orthologs is nearly parallel to that of SM. Based on the chemistry of lipids together with evolutionary aspects of SM and CERT, several concepts are here proposed. SM may serve as a chemically inert and robust, but non-covalently interactive lipid class at the outer leaflet of the plasma membrane. The functional domains and peptidic motifs of CERT are separated by exon units, suggesting an exon-shuffling mechanism for the generation of an ancestral CERT gene. CERT may have co-evolved with SM to bypass a competing metabolic reaction at the bifurcated point in the anabolism of ceramide. Human CERT is identical to the splicing variant of human Goodpasture antigen-binding protein (GPBP) annotated as an extracellular non-canonical serine/threonine protein kinase. The relationship between CERT and GPBP has also been discussed from an evolutionary aspect. Moreover, using an analogy of "compatible (or osmoprotective) solutes" that can accumulate to very high concentrations in the cytosol without denaturing proteins, choline phospholipids such as PtdCho and SM may act as compatible phospholipids in biomembranes. This article is part of a Special Issue entitled New Frontiers in Sphingolipid Biology.

Dynamic integration of splicing within gene regulatory pathways

Precursor mRNA splicing is one of the most highly regulated processes in metazoan species. In addition to generating vast repertoires of RNAs and proteins, splicing has a profound impact on other gene regulatory layers, including mRNA transcription, turnover, transport, and translation. Conversely, factors regulating chromatin and transcription complexes impact the splicing process. This extensive crosstalk between gene regulatory layers takes advantage of dynamic spatial, physical, and temporal organizational properties of the cell nucleus, and further emphasizes the importance of developing a multidimensional understanding of splicing control.

The switches.ELM resource: a compendium of conditional regulatory interaction interfaces

Short linear motifs (SLiMs) are protein interaction sites that play an important role in cell regulation by controlling protein activity, localization, and local abundance. The functionality of a SLiM can be modulated in a context-dependent manner to induce a gain, loss, or exchange of binding partners, which will affect the function of the SLiM-containing protein. As such, these conditional interactions underlie molecular decision-making in cell signaling. We identified multiple types of pre- and posttranslational switch mechanisms that can regulate the function of a SLiM and thereby control its interactions. The collected examples of experimentally characterized SLiM-based switch mechanisms were curated in the freely accessible switches.ELM resource (http://switches.elm.eu.org). On the basis of these examples, we defined and integrated rules to analyze SLiMs for putative regulatory switch mechanisms. We applied these rules to known validated SLiMs, providing evidence that more than half of these are likely to be pre- or posttranslationally regulated. In addition, we showed that posttranslationally modified sites are enriched around SLiMs, which enables cooperative and integrative regulation of protein interaction interfaces. We foresee switches.ELM complementing available resources to extend our knowledge of the molecular mechanisms underlying cell signaling.

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.