Norman E. Davey

ELM—the database of eukaryotic linear motifs

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.

The eukaryotic linear motif resource ELM: 10 years and counting

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.

ELM: the status of the 2010 eukaryotic linear motif resource.

Linear motifs are short segments of multidomain proteins that provide regulatory functions independently of protein tertiary structure. Much of intracellular signalling passes through protein modifications at linear motifs. Many thousands of linear motif instances, most notably phosphorylation sites, have now been reported. Although clearly very abundant, linear motifs are difficult to predict de novo in protein sequences due to the difficulty of obtaining robust statistical assessments. The ELM resource at http://elm.eu.org/ provides an expanding knowledge base, currently covering 146 known motifs, with annotation that includes >1300 experimentally reported instances. ELM is also an exploratory tool for suggesting new candidates of known linear motifs in proteins of interest. Information about protein domains, protein structure and native disorder, cellular and taxonomic contexts is used to reduce or deprecate false positive matches. Results are graphically displayed in a ‘Bar Code’ format, which also displays known instances from homologous proteins through a novel ‘Instance Mapper’ protocol based on PHI-BLAST. ELM server output provides links to the ELM annotation as well as to a number of remote resources. Using the links, researchers can explore the motifs, proteins, complex structures and associated literature to evaluate whether candidate motifs might be worth experimental investigation.

How viruses hijack cell regulation.

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

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.

ELM 2016—data update and new functionality of the eukaryotic linear motif resource

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.

A Proteome-wide Screen for Mammalian SxIP Motif-Containing Microtubule Plus-End Tracking Proteins

Microtubule plus-end tracking proteins (+TIPs) are structurally and functionally diverse factors that accumulate at the growing microtubule plus-ends, connect them to various cellular structures, and control microtubule dynamics [1, 2]. EB1 and its homologs are +TIPs that can autonomously recognize growing microtubule ends and recruit to them a variety of other proteins. Numerous +TIPs bind to end binding (EB) proteins through natively unstructured basic and serine-rich polypeptide regions containing a core SxIP motif (serine-any amino acid-isoleucine-proline) [3]. The SxIP consensus sequence is short, and the surrounding sequences show high variability, raising the possibility that undiscovered SxIP containing +TIPs are encoded in mammalian genomes. Here, we performed a proteome-wide search for mammalian SxIP-containing +TIPs by combining biochemical and bioinformatics approaches. We have identified a set of previously uncharacterized EB partners that have the capacity to accumulate at the growing microtubule ends, including protein kinases, a small GTPase, centriole-, membrane-, and actin-associated proteins. We show that one of the newly identified +TIPs, CEP104, interacts with CP110 and CEP97 at the centriole and is required for ciliogenesis. Our study reveals the complexity of the mammalian +TIP interactome and provides a basis for investigating the molecular crosstalk between microtubule ends and other cellular structures.

SLiMFinder: A Probabilistic Method for Identifying Over-Represented, Convergently Evolved, Short Linear Motifs in Proteins

Background Short linear motifs (SLiMs) in proteins are functional microdomains of fundamental importance in many biological systems. SLiMs typically consist of a 3 to 10 amino acid stretch of the primary protein sequence, of which as few as two sites may be important for activity, making identification of novel SLiMs extremely difficult. In particular, it can be very difficult to distinguish a randomly recurring “motif” from a truly over-represented one. Incorporating ambiguous amino acid positions and/or variable-length wildcard spacers between defined residues further complicates the matter. Methodology/Principal Findings In this paper we present two algorithms. SLiMBuild identifies convergently evolved, short motifs in a dataset of proteins. Motifs are built by combining dimers into longer patterns, retaining only those motifs occurring in a sufficient number of unrelated proteins. Motifs with fixed amino acid positions are identified and then combined to incorporate amino acid ambiguity and variable-length wildcard spacers. The algorithm is computationally efficient compared to alternatives, particularly when datasets include homologous proteins, and provides great flexibility in the nature of motifs returned. The SLiMChance algorithm estimates the probability of returned motifs arising by chance, correcting for the size and composition of the dataset, and assigns a significance value to each motif. These algorithms are implemented in a software package, SLiMFinder. SLiMFinder default settings identify known SLiMs with 100% specificity, and have a low false discovery rate on random test data. Conclusions/Significance The efficiency of SLiMBuild and low false discovery rate of SLiMChance make SLiMFinder highly suited to high throughput motif discovery and individual high quality analyses alike. Examples of such analyses on real biological data, and how SLiMFinder results can help direct future discoveries, are provided. SLiMFinder is freely available for download under a GNU license from http://bioinformatics.ucd.ie/shields/software/slimfinder/.

Short Linear Motifs: Ubiquitous and Functionally Diverse Protein Interaction Modules Directing Cell Regulation

Interaction Modules Directing Cell Regulation Kim Van Roey,† Bora Uyar,† Robert J. Weatheritt,‡ Holger Dinkel,† Markus Seiler,† Aidan Budd,† Toby J. Gibson,† and Norman E. Davey*,†,§ †Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), Meyerhofstrasse 1, 69117 Heidelberg, Germany ‡MRC Laboratory of Molecular Biology (LMB), Francis Crick Avenue, Cambridge Biomedical Campus, Cambridge CB2 0QH, United Kingdom Department of Physiology, University of California, San Francisco, San Francisco, California 94143, United States

Motif switches: decision-making in cell regulation

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 proteins 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.