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

Edwards, Richard J.; Davey, Norman E.; Shields, Denis C.

doi:10.1371/journal.pone.0000967

Cited by 146 publications

(195 citation statements)

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“…With regard to IDP regions involved in binding, various descriptors have been used, such as eukaryotic linear motif (ELMs), 34,35 linear motifs (LMs), 36 short linear motif (SLiMs), 37,38 regions of increased structural propensity (RISPs), 39 and molecular recognition features (MoRFs). 40 All of these describe similar phenomena, despite differing approaches used by the various researchers for identification of binding segments.…”

Section: Introductionmentioning

confidence: 99%

“…41,42 Predicting binding sites by sequence matches to the motifs of ELMs, 34,35 LMs, 36 SLiMs, 37,38 or other collections of sequence patterns [43][44][45] provides one strategy for identifying potential binding sites located within IDPs or IDP regions. Using sequence characteristics that indicate short binding regions within longer regions of disorder offers a second strategy that does not depend on specific motifs, and several predictors have been developed that use this second strategy.…”

Section: Introductionmentioning

confidence: 99%

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Exploring the binding diversity of intrinsically disordered proteins involved in one‐to‐many binding

et al. 2013

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Molecular recognition features (MoRFs) are intrinsically disordered protein regions that bind to partners via disorder-to-order transitions. In one-to-many binding, a single MoRF binds to two or more different partners individually. MoRF-based one-to-many protein-protein interaction (PPI) examples were collected from the Protein Data Bank, yielding 23 MoRFs bound to 2-9 partners, with all pairs of same-MoRF partners having less than 25% sequence identity. Of these, 8 MoRFs were bound to 2-9 partners having completely different folds, whereas 15 MoRFs were bound to 2-5 partners having the same folds but with low sequence identities. For both types of partner variation, backbone and side chain torsion angle rotations were used to bring about the conformational changes needed to enable close fits between a single MoRF and distinct partners. Alternative splicing events (ASEs) and posttranslational modifications (PTMs) were also found to contribute to distinct partner binding. Because ASEs and PTMs both commonly occur in disordered regions, and because both ASEs and PTMs are often tissue-specific, these data suggest that MoRFs, ASEs, and PTMs may collaborate to alter PPI networks in different cell types. These data enlarge the set of carefully studied MoRFs that use inherent flexibility and that also use ASE-based and/or PTM-based surface modifications to enable the same disordered segment to selectively associate with two or more partners. The small number of residues involved in MoRFs and in their modifications by ASEs or PTMs may simplify the evolvability of signaling network diversity.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Exploring the binding diversity of intrinsically disordered proteins involved in one‐to‐many binding

et al. 2013

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“…Whereas other methods for finding motifs are designed to search for known motifs (e.g., Eukaryotic Linear Motif database) (29)(30)(31)(32), or motifs with properties previously observed in linear binding sites (e.g., 3D structures, intrinsic disorder, sequence conservation, and solvent accessibility) (33)(34)(35)(36)(37)(38), or motifs that are over-represented according to a statistical model (e.g., hidden Markov model, Gibbs sampling, and Nested sampling) (39)(40)(41)(42), our method exhaustively enumerates all possible motifs, covering the entire space of peptide variations. Here, we determine the specificity of all of the enumerated motifs for a target peptidebinding domain.…”

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confidence: 99%

Evolution of domain–peptide interactions to coadapt specificity and affinity to functional diversity

Kelil

Levy

Michnick

2016

Proc. Natl. Acad. Sci. U.S.A.

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Evolution of complexity in eukaryotic proteomes has arisen, in part, through emergence of modular independently folded domains mediating protein interactions via binding to short linear peptides in proteins. Over 30 years, structural properties and sequence preferences of these peptides have been extensively characterized. Less successful, however, were efforts to establish relationships between physicochemical properties and functions of domainpeptide interactions. To our knowledge, we have devised the first strategy to exhaustively explore the binding specificity of protein domain-peptide interactions. We applied the strategy to SH3 domains to determine the properties of their binding peptides starting from various experimental data. The strategy identified the majority (∼70%) of experimentally determined SH3 binding sites. We discovered mutual relationships among binding specificity, binding affinity, and structural properties and evolution of linear peptides. Remarkably, we found that these properties are also related to functional diversity, defined by depth of proteins within hierarchies of gene ontologies. Our results revealed that linear peptides evolved to coadapt specificity and affinity to functional diversity of domain-peptide interactions. Thus, domain-peptide interactions follow human-constructed gene ontologies, which suggest that our understanding of biological process hierarchies reflect the way chemical and thermodynamic properties of linear peptides and their interaction networks, in general, have evolved.linear peptides | domain-peptide interactions | binding specificity | binding affinity | functional specificity M any proteins, particularly in eukaryotes, are composed of modular protein architectures consisting of multiple independently folding domains (1). Specific domains such as SH3 and PDZ domains were repeatedly used throughout evolution in increasingly complex organisms to mediate protein-protein interactions involved in signal transduction and protein targeting (2-5). These domains are associated with a number of human diseases and are targets of virus and other pathogen virulence proteins (6). Functions of these domains include binding to sequence-specific peptides both among themselves and on other proteins. Such interactions can create enormous plasticity in complex signaling and regulatory networks on immediate to evolutionary timescales (7), and are often used for regulating the activities of proteins and the spatiotemporal organization of protein interaction networks (8,9). However, at the cellular level, we still do not grasp why certain peptides in proteins bind to distinct domains with high specificity whereas others highly cross-react with a number of members of a family of domains, and also what is the relationship between specificity of binding and specificity of functions of domain-peptide interactions. Two extreme examples are peptides of the MAPKK protein Pbs2 (residues 92-106) (10) and the actin assembly protein Las17 (residues 306-336) (11), which both interact with ...

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“…SLiMFinder [13] identifies novel short linear motifs (SLiMs) in a set of sequences. SLiMs are microdomains that have important functions in many diverse biological pathways.…”

Section: Tools For Motif Discoverymentioning

confidence: 99%

“…Some tools, such as Teiresias [11], or the MEME suite [12], can discover motifs in both DNA and protein sequences. Other work has been dedicated to the discovery of specific types of protein motifs, such as patterns containing large irregular gaps with "eukaryotic linear motifs" with SLiMFinder [13] or phosphorylation sites [14]. Many studies have been conducted to compare these specific motif discovery tools, such as [15].…”

Section: Introductionmentioning

confidence: 99%

Motif Discovery in Protein Sequences

Mohamed¹,

Elloumi²,

Thompson³

2016

Pattern Recognition - Analysis and Applications

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Biology has become a data-intensive research field. Coping with the flood of data from the new genome sequencing technologies is a major area of research. The exponential increase in the size of the datasets produced by "next-generation sequencing" (NGS) poses unique computational challenges. In this context, motif discovery tools are widely used to identify important patterns in the sequences produced. Biological sequence motifs are defined as short, usually fixed length, sequence patterns that may represent important structural or functional features in nucleic acid and protein sequences such as transcription binding sites, splice junctions, active sites, or interaction interfaces. They can occur in an exact or approximate form within a family or a subfamily of sequences. Motif discovery is therefore an important field in bioinformatics, and numerous methods have been developed for the identification of motifs shared by a set of functionally related sequences. This chapter will review the existing motif discovery methods for protein sequences and their ability to discover biologically important features as well as their limitations for the discovery of new motifs. Finally, we will propose new horizons for motif discovery in order to address the short comings of the existent methods.

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

Cited by 146 publications

References 18 publications

Exploring the binding diversity of intrinsically disordered proteins involved in one‐to‐many binding

Exploring the binding diversity of intrinsically disordered proteins involved in one‐to‐many binding

Evolution of domain–peptide interactions to coadapt specificity and affinity to functional diversity

Motif Discovery in Protein Sequences

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