TY - JOUR T1 - ELM-the Eukaryotic Linear Motif resource-2024 update. JF - Nucleic Acids Res Y1 - 2023 A1 - Manjeet Kumar A1 - Michael, Sushama A1 - Jesús Alvarado-Valverde A1 - Zeke, András A1 - Tamas Lazar A1 - Juliana Glavina A1 - Eszter Nagy-Kanta A1 - Juan Mac Donagh A1 - Zsofia E Kalman A1 - Stefano Pascarelli A1 - Nicolas Palopoli A1 - László Dobson A1 - Carmen Florencia Suarez A1 - Kim Van Roey A1 - Izabella Krystkowiak A1 - Juan Esteban Griffin A1 - Nagpal, Anurag A1 - Rajesh Bhardwaj A1 - Francesca Diella A1 - Mészáros, Bálint A1 - Kellie Dean A1 - Norman E Davey A1 - Rita Pancsa A1 - Lucia B Chemes A1 - Toby J Gibson AB -

Short Linear Motifs (SLiMs) are the smallest structural and functional components of modular eukaryotic proteins. They are also the most abundant, especially when considering post-translational modifications. As well as being found throughout the cell as part of regulatory processes, SLiMs are extensively mimicked by intracellular pathogens. At the heart of the Eukaryotic Linear Motif (ELM) Resource is a representative (not comprehensive) database. The ELM entries are created by a growing community of skilled annotators and provide an introduction to linear motif functionality for biomedical researchers. The 2024 ELM update includes 346 novel motif instances in areas ranging from innate immunity to both protein and RNA degradation systems. In total, 39 classes of newly annotated motifs have been added, and another 17 existing entries have been updated in the database. The 2024 ELM release now includes 356 motif classes incorporating 4283 individual motif instances manually curated from 4274 scientific publications and including >700 links to experimentally determined 3D structures. In a recent development, the InterPro protein module resource now also includes ELM data. ELM is available at: http://elm.eu.org.

M3 - 10.1093/nar/gkad1058 ER - TY - JOUR T1 - Minimum information guidelines for experiments structurally characterizing intrinsically disordered protein regions. JF - Nat Methods Y1 - 2023 A1 - Mészáros, Bálint A1 - András Hatos A1 - Nicolas Palopoli A1 - Federica Quaglia A1 - Edoardo Salladini A1 - Kim Van Roey A1 - Arthanari, Haribabu A1 - Zsuzsanna Dosztányi A1 - Isabella C Felli A1 - Patrick D Fischer A1 - Jeffrey C Hoch A1 - Cy M Jeffries A1 - Sonia Longhi A1 - Emiliano Maiani A1 - Sandra Orchard A1 - Rita Pancsa A1 - Elena Papaleo A1 - Roberta Pierattelli A1 - Damiano Piovesan A1 - Iva Pritisanac A1 - Luiggi Tenorio A1 - Thibault Viennet A1 - Peter Tompa A1 - Wim Vranken A1 - Silvio C E Tosatto A1 - Norman E Davey KW - Intrinsically Disordered Proteins KW - Protein Conformation AB -

An unambiguous description of an experiment, and the subsequent biological observation, is vital for accurate data interpretation. Minimum information guidelines define the fundamental complement of data that can support an unambiguous conclusion based on experimental observations. We present the Minimum Information About Disorder Experiments (MIADE) guidelines to define the parameters required for the wider scientific community to understand the findings of an experiment studying the structural properties of intrinsically disordered regions (IDRs). MIADE guidelines provide recommendations for data producers to describe the results of their experiments at source, for curators to annotate experimental data to community resources and for database developers maintaining community resources to disseminate the data. The MIADE guidelines will improve the interpretability of experimental results for data consumers, facilitate direct data submission, simplify data curation, improve data exchange among repositories and standardize the dissemination of the key metadata on an IDR experiment by IDR data sources.

VL - 20 CP - 9 M3 - 10.1038/s41592-023-01915-x ER - TY - RPRT T1 - Orphanet vertaling: activiteitenrapport (2022) Y1 - 2023 A1 - Kim Van Roey KW - Orphanet KW - Rare diseases PB - Sciensano CY - Brussels, Belgium ER - TY - RPRT T1 - Orphanet vertaling: activiteitenrapport (2021) Y1 - 2022 A1 - Kim Van Roey A1 - Elfriede Swinnen KW - Orphanet KW - Rare diseases PB - Sciensano CY - Brussels, Belgium ER - TY - RPRT T1 - Orphanet vertaling: activiteitenrapport (2020) Y1 - 2021 A1 - Kim Van Roey A1 - Elfriede Swinnen KW - Orphanet KW - Rare diseases PB - Sciensano CY - Brussels, Belgium ER - TY - JOUR T1 - How to Annotate and Submit a Short Linear Motif to the Eukaryotic Linear Motif Resource. JF - Methods Mol Biol Y1 - 2020 A1 - Marc Gouw A1 - Jesús Alvarado-Valverde A1 - Jelena Čalyševa A1 - Francesca Diella A1 - Manjeet Kumar A1 - Michael, Sushama A1 - Kim Van Roey A1 - Holger Dinkel A1 - Toby J Gibson AB -

Over the past few years, it has become apparent that approximately 35% of the human proteome consists of intrinsically disordered regions. Many of these disordered regions are rich in short linear motifs (SLiMs) which mediate protein-protein interactions. Although these motifs are short and often partially conserved, they are involved in many important aspects of protein function, including cleavage, targeting, degradation, docking, phosphorylation, and other posttranslational modifications. The Eukaryotic Linear Motif resource (ELM) was established over 15 years ago as a repository to store and catalogue the scientific discoveries of motifs. Each motif in the database is annotated and curated manually, based on the experimental evidence gathered from publications. The entries themselves are submitted to ELM by filling in two annotation templates designed for motif class and motif instance annotation. In this protocol, we describe the steps involved in annotating new motifs and how to submit them to ELM.

VL - 2141 M3 - 10.1007/978-1-0716-0524-0_4 ER - TY - JOUR T1 - Capturing variation impact on molecular interactions in the IMEx Consortium mutations data set. JF - Nat Commun Y1 - 2019 A1 - N Del-Toro A1 - M Duesbury A1 - M Koch A1 - L Perfetto A1 - A Shrivastava A1 - D Ochoa A1 - O Wagih A1 - J Piñero A1 - M Kotlyar A1 - C Pastrello A1 - P Beltrao A1 - L I Furlong A1 - I Jurisica A1 - H Hermjakob A1 - S Orchard A1 - P Porras KW - Amino Acid Substitution KW - Animals KW - disease KW - Genetic Variation KW - Humans KW - Molecular Sequence Annotation KW - Point Mutation KW - Protein Interaction Maps AB -

The current wealth of genomic variation data identified at nucleotide level presents the challenge of understanding by which mechanisms amino acid variation affects cellular processes. These effects may manifest as distinct phenotypic differences between individuals or result in the development of disease. Physical interactions between molecules are the linking steps underlying most, if not all, cellular processes. Understanding the effects that sequence variation has on a molecule's interactions is a key step towards connecting mechanistic characterization of nonsynonymous variation to phenotype. We present an open access resource created over 14 years by IMEx database curators, featuring 28,000 annotations describing the effect of small sequence changes on physical protein interactions. We describe how this resource was built, the formats in which the data is provided and offer a descriptive analysis of the data set. The data set is publicly available through the IntAct website and is enhanced with every monthly release.

VL - 10 CP - 1 M3 - 10.1038/s41467-018-07709-6 ER - TY - RPRT T1 - Orphanet vertaling: activiteitenrapport (2018-2019) Y1 - 2019 A1 - Kim Van Roey A1 - Elfriede Swinnen A1 - Kris Doggen KW - Orphanet KW - Rare diseases PB - Sciensano CY - Brussels, Belgium ER - TY - JOUR T1 - Encompassing new use cases - level 3.0 of the HUPO-PSI format for molecular interactions. JF - BMC Bioinformatics Y1 - 2018 A1 - Sivade M Dumousseau A1 - D Alonso-López A1 - M Ammari A1 - G Bradley A1 - N H Campbell A1 - A Ceol A1 - G Cesareni A1 - C Combe A1 - J De Las Rivas A1 - N Del-Toro A1 - J Heimbach A1 - H Hermjakob A1 - I Jurisica A1 - M Koch A1 - L Licata A1 - R C Lovering A1 - D J Lynn A1 - B H M Meldal A1 - G Micklem A1 - S Panni A1 - P Porras A1 - S Ricard-Blum A1 - B Roechert A1 - L Salwinski A1 - A Shrivastava A1 - J Sullivan A1 - N Thierry-Mieg A1 - Y Yehudi A1 - Kim Van Roey A1 - S Orchard KW - Databases, Protein KW - Humans KW - Mutation KW - Protein Interaction Maps KW - Proteome KW - Proteomics KW - Systems Biology AB -

BACKGROUND: Systems biologists study interaction data to understand the behaviour of whole cell systems, and their environment, at a molecular level. In order to effectively achieve this goal, it is critical that researchers have high quality interaction datasets available to them, in a standard data format, and also a suite of tools with which to analyse such data and form experimentally testable hypotheses from them. The PSI-MI XML standard interchange format was initially published in 2004, and expanded in 2007 to enable the download and interchange of molecular interaction data. PSI-XML2.5 was designed to describe experimental data and to date has fulfilled this basic requirement. However, new use cases have arisen that the format cannot properly accommodate. These include data abstracted from more than one publication such as allosteric/cooperative interactions and protein complexes, dynamic interactions and the need to link kinetic and affinity data to specific mutational changes.

RESULTS: The Molecular Interaction workgroup of the HUPO-PSI has extended the existing, well-used XML interchange format for molecular interaction data to meet new use cases and enable the capture of new data types, following extensive community consultation. PSI-MI XML3.0 expands the capabilities of the format beyond simple experimental data, with a concomitant update of the tool suite which serves this format. The format has been implemented by key data producers such as the International Molecular Exchange (IMEx) Consortium of protein interaction databases and the Complex Portal.

CONCLUSIONS: PSI-MI XML3.0 has been developed by the data producers, data users, tool developers and database providers who constitute the PSI-MI workgroup. This group now actively supports PSI-MI XML2.5 as the main interchange format for experimental data, PSI-MI XML3.0 which additionally handles more complex data types, and the simpler, tab-delimited MITAB2.5, 2.6 and 2.7 for rapid parsing and download.

VL - 19 CP - 1 M3 - 10.1186/s12859-018-2118-1 ER - TY - JOUR T1 - The eukaryotic linear motif resource - 2018 update. JF - Nucleic Acids Res Y1 - 2018 A1 - Marc Gouw A1 - Michael, Sushama A1 - Hugo Sámano-Sánchez A1 - Manjeet Kumar A1 - András Zeke A1 - Benjamin Lang A1 - Benoit Bely A1 - Lucia B Chemes A1 - Norman E Davey A1 - Deng, Ziqi A1 - Francesca Diella A1 - Clara-Marie Gürth A1 - Ann-Kathrin Huber A1 - Stefan Kleinsorg A1 - Lara S Schlegel A1 - Nicolás Palopoli A1 - Kim Van Roey A1 - Brigitte Altenberg A1 - Attila Reményi A1 - Holger Dinkel A1 - Toby J Gibson KW - Amino Acid Motifs KW - Animals KW - bacteria KW - Binding Sites KW - Cell Cycle KW - Databases, Protein KW - Eukaryotic Cells KW - Fungi KW - Host-Pathogen Interactions KW - Humans KW - Internet KW - Models, Molecular KW - Molecular Sequence Annotation KW - Plants KW - Protein Binding KW - Protein Conformation, alpha-Helical KW - Protein Conformation, beta-Strand KW - Protein Interaction Domains and Motifs KW - Proteins KW - SOFTWARE KW - Viruses AB -

Short linear motifs (SLiMs) are protein binding modules that play major roles in almost all cellular processes. SLiMs are short, often highly degenerate, difficult to characterize and hard to detect. The eukaryotic linear motif (ELM) resource (elm.eu.org) is dedicated to SLiMs, consisting of a manually curated database of over 275 motif classes and over 3000 motif instances, and a pipeline to discover candidate SLiMs in protein sequences. For 15 years, ELM has been one of the major resources for motif research. In this database update, we present the latest additions to the database including 32 new motif classes, and new features including Uniprot and Reactome integration. Finally, to help provide cellular context, we present some biological insights about SLiMs in the cell cycle, as targets for bacterial pathogenicity and their functionality in the human kinome.

VL - 46 CP - D1 M3 - 10.1093/nar/gkx1077 ER - TY - JOUR T1 - Exploring Short Linear Motifs Using the ELM Database and Tools. JF - Curr Protoc Bioinformatics Y1 - 2017 A1 - Marc Gouw A1 - Hugo Sámano-Sánchez A1 - Kim Van Roey A1 - Francesca Diella A1 - Toby J Gibson A1 - Holger Dinkel KW - Amino Acid Motifs KW - Computational Biology KW - Databases, Protein KW - Eukaryota KW - Protein Domains KW - Proteins AB -

The Eukaryotic Linear Motif (ELM) resource is dedicated to the characterization and prediction of short linear motifs (SLiMs). SLiMs are compact, degenerate peptide segments found in many proteins and essential to almost all cellular processes. However, despite their abundance, SLiMs remain largely uncharacterized. The ELM database is a collection of manually annotated SLiM instances curated from experimental literature. In this article we illustrate how to browse and search the database for curated SLiM data, and cover the different types of data integrated in the resource. We also cover how to use this resource in order to predict SLiMs in known as well as novel proteins, and how to interpret the results generated by the ELM prediction pipeline. The ELM database is a very rich resource, and in the following protocols we give helpful examples to demonstrate how this knowledge can be used to improve your own research. © 2017 by John Wiley & Sons, Inc.

VL - 58 M3 - 10.1002/cpbi.26 ER - TY - JOUR T1 - ELM 2016--data update and new functionality of the eukaryotic linear motif resource. JF - Nucleic Acids Res Y1 - 2016 A1 - Holger Dinkel A1 - Kim Van Roey A1 - Michael, Sushama A1 - Manjeet Kumar A1 - Bora Uyar A1 - Brigitte Altenberg A1 - Vladislava Milchevskaya A1 - Melanie Schneider A1 - Helen Kühn A1 - Annika Behrendt A1 - Sophie Luise Dahl A1 - Victoria Damerell A1 - Sandra Diebel A1 - Sara Kalman A1 - Steffen Klein A1 - Arne C Knudsen A1 - Christina Mäder A1 - Sabina Merrill A1 - Angelina Staudt A1 - Vera Thiel A1 - Lukas Welti A1 - Norman E Davey A1 - Francesca Diella A1 - Toby J Gibson KW - Amino Acid Motifs KW - Databases, Protein KW - Eukaryota KW - Internet KW - Signal Transduction KW - SOFTWARE AB -

The Eukaryotic Linear Motif (ELM) resource (http://elm.eu.org) is a manually curated database of short linear motifs (SLiMs). In this update, we present the latest additions to this resource, along with more improvements to the web interface. ELM 2016 contains more than 240 different motif classes with over 2700 experimentally validated instances, manually curated from more than 2400 scientific publications. In addition, more data have been made available as individually searchable pages and are downloadable in various formats.

VL - 44 CP - D1 M3 - 10.1093/nar/gkv1291 ER - TY - RPRT T1 - Etude de faisabilité : développement et implémentation d'un système de controle de qualité dans les 8 centres de génétique humaine et d'un registre de tests de génétique effectués dans ces centres Y1 - 2016 A1 - Fabienne Van Aelst A1 - Jean-Bernard Beaudry A1 - Kim Van Roey PB - WIV-ISP CY - Brussels, Belgium ER - TY - RPRT T1 - Haalbaarheidsstudie: ontwikkeling en implementatie van een kwaliteitscontrolesysteem in de 8 centra voor menselijke genetica en de creatie van een register van genetische testen die in deze centra worden uitgevoerd Y1 - 2016 A1 - Fabienne Van Aelst A1 - Jean-Bernard Beaudry A1 - Kim Van Roey PB - WIV-ISP CY - Brussels, Belgium ER - TY - JOUR T1 - Experimental detection of short regulatory motifs in eukaryotic proteins: tips for good practice as well as for bad. JF - Cell Commun Signal Y1 - 2015 A1 - Toby J Gibson A1 - Holger Dinkel A1 - Kim Van Roey A1 - Francesca Diella KW - Amino Acid Motifs KW - Animals KW - Computational Biology KW - Eukaryota KW - Genetic Testing KW - Humans KW - Proteins AB -

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.

VL - 13 M3 - 10.1186/s12964-015-0121-y ER - TY - JOUR T1 - Motif co-regulation and co-operativity are common mechanisms in transcriptional, post-transcriptional and post-translational regulation. JF - Cell Commun Signal Y1 - 2015 A1 - Kim Van Roey A1 - Norman E Davey KW - Amino Acid Motifs KW - Animals KW - Dna KW - Humans KW - Protein Processing, Post-Translational KW - Proteins KW - Rna KW - RNA Processing, Post-Transcriptional KW - Transcription, Genetic AB -

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

VL - 13 M3 - 10.1186/s12964-015-0123-9 ER - TY - JOUR T1 - The eukaryotic linear motif resource ELM: 10 years and counting. JF - Nucleic Acids Res Y1 - 2014 A1 - Holger Dinkel A1 - Kim Van Roey A1 - Michael, Sushama A1 - Norman E Davey A1 - Robert J Weatheritt A1 - Diana Born A1 - Tobias Speck A1 - Daniel Krüger A1 - Gleb Grebnev A1 - Marta Kuban A1 - Marta Strumillo A1 - Bora Uyar A1 - Aidan Budd A1 - Brigitte Altenberg A1 - Markus Seiler A1 - Lucia B Chemes A1 - Juliana Glavina A1 - Ignacio E Sánchez A1 - Francesca Diella A1 - Toby J Gibson KW - Amino Acid Motifs KW - Databases, Protein KW - Internet KW - Multiprotein Complexes KW - Protein Interaction Domains and Motifs AB -

The eukaryotic linear motif (ELM http://elm.eu.org) resource is a hub for collecting, classifying and curating information about short linear motifs (SLiMs). For >10 years, this resource has provided the scientific community with a freely accessible guide to the biology and function of linear motifs. The current version of ELM contains ∼200 different motif classes with over 2400 experimentally validated instances manually curated from >2000 scientific publications. Furthermore, detailed information about motif-mediated interactions has been annotated and made available in standard exchange formats. Where appropriate, links are provided to resources such as switches.elm.eu.org and KEGG pathways.

VL - 42 CP - Database issue M3 - 10.1093/nar/gkt1047 ER - TY - JOUR T1 - The MIntAct project--IntAct as a common curation platform for 11 molecular interaction databases. JF - Nucleic Acids Res Y1 - 2014 A1 - Sandra Orchard A1 - Mais Ammari A1 - Bruno Aranda A1 - Lionel Breuza A1 - Leonardo Briganti A1 - Fiona Broackes-Carter A1 - Nancy H Campbell A1 - Chavali, Gayatri A1 - Carol Chen A1 - Noemi del-Toro A1 - Margaret Duesbury A1 - Marine Dumousseau A1 - Eugenia Galeota A1 - Ursula Hinz A1 - Marta Iannuccelli A1 - Sruthi Jagannathan A1 - Rafael Jimenez A1 - Jyoti Khadake A1 - Astrid Lagreid A1 - Luana Licata A1 - Ruth C Lovering A1 - Birgit Meldal A1 - Anna N Melidoni A1 - Mila Milagros A1 - Daniele Peluso A1 - Livia Perfetto A1 - Pablo Porras A1 - Raghunath, Arathi A1 - Sylvie Ricard-Blum A1 - Bernd Roechert A1 - Andre Stutz A1 - Michael Tognolli A1 - Kim Van Roey A1 - Gianni Cesareni A1 - Hermjakob, Henning KW - Databases, Protein KW - Internet KW - Protein Interaction Mapping KW - SOFTWARE AB -

IntAct (freely available at http://www.ebi.ac.uk/intact) is an open-source, open data molecular interaction database populated by data either curated from the literature or from direct data depositions. IntAct has developed a sophisticated web-based curation tool, capable of supporting both IMEx- and MIMIx-level curation. This tool is now utilized by multiple additional curation teams, all of whom annotate data directly into the IntAct database. Members of the IntAct team supply appropriate levels of training, perform quality control on entries and take responsibility for long-term data maintenance. Recently, the MINT and IntAct databases decided to merge their separate efforts to make optimal use of limited developer resources and maximize the curation output. All data manually curated by the MINT curators have been moved into the IntAct database at EMBL-EBI and are merged with the existing IntAct dataset. Both IntAct and MINT are active contributors to the IMEx consortium (http://www.imexconsortium.org).

VL - 42 CP - Database issue M3 - 10.1093/nar/gkt1115 ER - TY - JOUR T1 - Short linear motifs: ubiquitous and functionally diverse protein interaction modules directing cell regulation. JF - Chem Rev Y1 - 2014 A1 - Kim Van Roey A1 - Bora Uyar A1 - Robert J Weatheritt A1 - Holger Dinkel A1 - Markus Seiler A1 - Aidan Budd A1 - Toby J Gibson A1 - Norman E Davey KW - Amino Acid Motifs KW - disease KW - Humans KW - Protein Processing, Post-Translational KW - Protein Structure, Tertiary VL - 114 CP - 13 M3 - 10.1021/cr400585q ER - TY - JOUR T1 - Capturing cooperative interactions with the PSI-MI format. JF - Database (Oxford) Y1 - 2013 A1 - Kim Van Roey A1 - Sandra Orchard A1 - Samuel Kerrien A1 - Marine Dumousseau A1 - Sylvie Ricard-Blum A1 - Hermjakob, Henning A1 - Toby J Gibson KW - Allosteric Regulation KW - Cell Cycle Proteins KW - Cyclin A KW - Cyclin-Dependent Kinase 2 KW - Databases, Protein KW - Humans KW - Models, Molecular KW - Molecular Sequence Annotation KW - Phosphorylation KW - Protein Binding KW - Protein Interaction Mapping KW - Proteomics AB -

The complex biological processes that control cellular function are mediated by intricate networks of molecular interactions. Accumulating evidence indicates that these interactions are often interdependent, thus acting cooperatively. Cooperative interactions are prevalent in and indispensible for reliable and robust control of cell regulation, as they underlie the conditional decision-making capability of large regulatory complexes. Despite an increased focus on experimental elucidation of the molecular details of cooperative binding events, as evidenced by their growing occurrence in literature, they are currently lacking from the main bioinformatics resources. One of the contributing factors to this deficiency is the lack of a computer-readable standard representation and exchange format for cooperative interaction data. To tackle this shortcoming, we added functionality to the widely used PSI-MI interchange format for molecular interaction data by defining new controlled vocabulary terms that allow annotation of different aspects of cooperativity without making structural changes to the underlying XML schema. As a result, we are able to capture cooperative interaction data in a structured format that is backward compatible with PSI-MI-based data and applications. This will facilitate the storage, exchange and analysis of cooperative interaction data, which in turn will advance experimental research on this fundamental principle in biology.

VL - 2013 M3 - 10.1093/database/bat066 ER - TY - JOUR T1 - The switches.ELM resource: a compendium of conditional regulatory interaction interfaces. JF - Sci Signal Y1 - 2013 A1 - Kim Van Roey A1 - Holger Dinkel A1 - Robert J Weatheritt A1 - Toby J Gibson A1 - Norman E Davey KW - Amino Acid Motifs KW - Amino Acid Sequence KW - Binding Sites KW - Databases, Protein KW - Molecular Sequence Data KW - Protein Binding KW - Protein Interaction Domains and Motifs KW - Protein Interaction Mapping KW - Protein Interaction Maps KW - Protein Processing, Post-Translational KW - Proteins KW - Sequence Homology, Amino Acid KW - Signal Transduction AB -

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.

VL - 6 CP - 269 M3 - 10.1126/scisignal.2003345 ER - TY - JOUR T1 - Attributes of short linear motifs. JF - Mol Biosyst Y1 - 2012 A1 - Norman E Davey A1 - Kim Van Roey A1 - Robert J Weatheritt A1 - Grischa Toedt A1 - Bora Uyar A1 - Brigitte Altenberg A1 - Aidan Budd A1 - Francesca Diella A1 - Holger Dinkel A1 - Toby J Gibson KW - Amino Acid Motifs KW - Amino acids KW - Animals KW - Conserved Sequence KW - Databases, Protein KW - Evolution, Molecular KW - Humans KW - Hydrophobic and Hydrophilic Interactions KW - Protein Folding KW - Protein Structure, Tertiary KW - Proteins KW - Repetitive Sequences, Amino Acid KW - Sequence Alignment AB -

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.

VL - 8 CP - 1 M3 - 10.1039/c1mb05231d ER - TY - JOUR T1 - ELM--the database of eukaryotic linear motifs. JF - Nucleic Acids Res Y1 - 2012 A1 - Holger Dinkel A1 - Michael, Sushama A1 - Robert J Weatheritt A1 - Norman E Davey A1 - Kim Van Roey A1 - Brigitte Altenberg A1 - Grischa Toedt A1 - Bora Uyar A1 - Markus Seiler A1 - Aidan Budd A1 - Lisa Jödicke A1 - Marcel A Dammert A1 - Christian Schroeter A1 - Maria Hammer A1 - Tobias Schmidt A1 - Peter Jehl A1 - Caroline McGuigan A1 - Magdalena Dymecka A1 - Claudia Chica A1 - Katja Luck A1 - Allegra Via A1 - Andrew Chatr-Aryamontri A1 - Niall Haslam A1 - Gleb Grebnev A1 - Richard J Edwards A1 - Michel O Steinmetz A1 - Heike Meiselbach A1 - Francesca Diella A1 - Toby J Gibson KW - Amino Acid Motifs KW - Computer Graphics KW - Databases, Protein KW - disease KW - Eukaryota KW - Sequence Analysis, Protein KW - User-Computer Interface KW - Viral Proteins AB -

Linear motifs are short, evolutionarily plastic components of regulatory proteins and provide low-affinity interaction interfaces. These compact modules play central roles in mediating every aspect of the regulatory functionality of the cell. They are particularly prominent in mediating cell signaling, controlling protein turnover and directing protein localization. Given their importance, our understanding of motifs is surprisingly limited, largely as a result of the difficulty of discovery, both experimentally and computationally. The Eukaryotic Linear Motif (ELM) resource at http://elm.eu.org provides the biological community with a comprehensive database of known experimentally validated motifs, and an exploratory tool to discover putative linear motifs in user-submitted protein sequences. The current update of the ELM database comprises 1800 annotated motif instances representing 170 distinct functional classes, including approximately 500 novel instances and 24 novel classes. Several older motif class entries have been also revisited, improving annotation and adding novel instances. Furthermore, addition of full-text search capabilities, an enhanced interface and simplified batch download has improved the overall accessibility of the ELM data. The motif discovery portion of the ELM resource has added conservation, and structural attributes have been incorporated to aid users to discriminate biologically relevant motifs from stochastically occurring non-functional instances.

VL - 40 CP - Database issue M3 - 10.1093/nar/gkr1064 ER - TY - JOUR T1 - Motif switches: decision-making in cell regulation. JF - Curr Opin Struct Biol Y1 - 2012 A1 - Kim Van Roey A1 - Toby J Gibson A1 - Norman E Davey KW - Amino Acid Motifs KW - Animals KW - Eukaryotic Cells KW - Humans KW - Models, Biological KW - Protein Binding KW - Protein Interaction Domains and Motifs KW - Proteins AB -

Tight regulation of gene products from transcription to protein degradation is required for reliable and robust control of eukaryotic cell physiology. Many of the mechanisms directing cell regulation rely on proteins detecting the state of the cell through context-dependent, tuneable interactions. These interactions underlie the ability of proteins to make decisions by combining regulatory information encoded in a protein's expression level, localisation and modification state. This raises the question, how do proteins integrate available information to correctly make decisions? Over the past decade pioneering work on the nature and function of intrinsically disordered protein regions has revealed many elegant switching mechanisms that underlie cell signalling and regulation, prompting a reevaluation of their role in cooperative decision-making.

VL - 22 CP - 3 M3 - 10.1016/j.sbi.2012.03.004 ER - TY - THES T1 - MTAC, a pancreatic islet-specific HMG-box protein isolated as a suppressor of a glucose-sensing deficient yeast mutant Y1 - 2009 A1 - Kim Van Roey ER - TY - JOUR T1 - Nutrient sensing systems for rapid activation of the protein kinase A pathway in yeast. JF - Biochem Soc Trans Y1 - 2005 A1 - J M Thevelein A1 - R Geladé A1 - I Holsbeeks A1 - O Lagatie A1 - Y Popova A1 - F Rolland A1 - F Stolz A1 - van de Velde, S A1 - P Van Dijck A1 - P Vandormael A1 - A Van Nuland A1 - Kim Van Roey A1 - G Van Zeebroeck A1 - B Yan KW - Cyclic AMP-Dependent Protein Kinases KW - Enzyme Activation KW - Glucose KW - Membrane Transport Proteins KW - Phosphates KW - Phosphorylation KW - Saccharomyces cerevisiae KW - Sucrose AB -

The cAMP-protein kinase A (PKA) pathway in the yeast Saccharomyces cerevisiae controls a variety of properties that depend on the nutrient composition of the medium. High activity of the pathway occurs in the presence of rapidly fermented sugars like glucose or sucrose, but only as long as growth is maintained. Growth arrest of fermenting cells or growth on a respiratory carbon source, like glycerol or ethanol, is associated with low activity of the PKA pathway. We have studied how different nutrients trigger rapid activation of the pathway. Glucose and sucrose activate cAMP synthesis through a G-protein-coupled receptor system, consisting of the GPCR Gpr1, the Galpha protein Gpa2 and its RGS protein Rgs2. Glucose is also sensed intracellularly through its phosphorylation. Specific mutations in Gpr1 abolish glucose but not sucrose signalling. Activation of the PKA pathway by addition of a nitrogen source or phosphate to nitrogen- or phosphate-starved cells, respectively, is not mediated by an increase in cAMP. Activation by amino acids is triggered by the general amino acid permease Gap1, which functions as a transporter/receptor. Short truncation of the C-terminus results in constitutively activating alleles. Activation by ammonium uses the ammonium permeases Mep1 and Mep2 as receptor. Specific point mutations in Mep2 uncouple signalling from transport. Activation by phosphate is triggered a.o. by the Pho84 phosphate permease. Several mutations in Pho84 separating transport and signalling or triggering constitutive activation have been obtained.

VL - 33 CP - Pt 1 M3 - 10.1042/BST0330253 ER - TY - BOOK T1 - Genomics and evolution of Metazoan Ga proteins Y1 - 2003 A1 - Kim Van Roey A1 - M Derks A1 - J Poels A1 - J Vanden Broeck SN - 1-59033-960-6 ER -