DILIMOT: discovery of linear motifs in proteins

Discovery of protein functional motifs is critical in modern biology. Small segments of 3–10 residues play critical roles in protein interactions, post-translational modifications and trafficking. DILIMOT (DIscovery of LInear MOTifs) is a server for the prediction of these short linear motifs within a set of proteins. Given a set of sequences sharing a common functional feature (e.g. interaction partner or localization) the method finds statistically over-represented motifs likely to be responsible for it. The input sequences are first passed through a set of filters to remove regions unlikely to contain instances of linear motifs. Motifs are then found in the remaining sequence and ranked according to a statistic that measure over-representation and conservation across homologues in related species. The results are displayed via a visual interface for easy perusal. The server is available a

Systematic Discovery of New Recognition Peptides Mediating Protein Interaction Networks

Many aspects of cell signalling, trafficking, and targeting are governed by interactions between globular protein domains and short peptide segments. These domains often bind multiple peptides that share a common sequence pattern, or “linear motif” (e.g., SH3 binding to PxxP). Many domains are known, though comparatively few linear motifs have been discovered. Their short length (three to eight residues), and the fact that they often reside in disordered regions in proteins makes them difficult to detect through sequence comparison or experiment. Nevertheless, each new motif provides critical molecular details of how interaction networks are constructed, and can explain how one protein is able to bind to very different partners. Here we show that binding motifs can be detected using data from genome-scale interaction studies, and thus avoid the normally slow discovery process. Our approach based on motif over-representation in non-homologous sequences, rediscovers known motifs and predicts dozens of others. Direct binding experiments reveal that two predicted motifs are indeed protein-binding modules: a DxxDxxxD protein phosphatase 1 binding motif with a K (D) of 22 μM and a VxxxRxYS motif that binds Translin with a K (D) of 43 μM. We estimate that there are dozens or even hundreds of linear motifs yet to be discovered that will give molecular insight into protein networks and greatly illuminate cellular processes

Lentiviral Hematopoietic Stem Cell Gene Therapy Benefits Metachromatic Leukodystrophy

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GlobPlot: exploring protein sequences for globularity and disorder. Nucl Acids Res

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

Overview of Motifs Found in the Fly

<p>Significant predictions from the yeast two-hybrid set for the fly. Blue dots in the center of each cluster represent proteins with four or more interaction partners (red and white dots) containing at least one confidently predicted motif (<i>p-</i>value < 0.001; <i>S_cons</i> ≤ 8 × 10⁻¹⁵). Partner proteins containing the motif are represented by red dots, whereas proteins lacking the motif are indicated by white dots. Clusters are labelled as gene name→detected motif. Yellow circles enclose known motifs: SH3→PxxP [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0030405#pbio-0030405-b38" target="_blank">38</a>], PP1→RVxF [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0030405#pbio-0030405-b22" target="_blank">22</a>], C-terminal binding protein (CtBP)→PxDLS [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0030405#pbio-0030405-b52" target="_blank">52</a>], SR splicing factors RS-rich segments [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0030405#pbio-0030405-b53" target="_blank">53</a>], and CG6843→SxKSKxxK, a likely nuclear localization signal. The Translin→VxxxRxYS motif was experimentally tested (<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0030405#pbio-0030405-g003" target="_blank">Figure 3</a>). The grey circles enclose clusters with low-complexity patterns. Two additional known motifs were also found in the fly using more relaxed criteria than those used for the other motifs in the figure: Groucho→WRPW [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0030405#pbio-0030405-b07" target="_blank">7</a>] and Dynein light chain→TQT [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0030405#pbio-0030405-b26" target="_blank">26</a>] as the variant A(TI)QT(DE). The latter was also identified as significant in the domain sets. Proteins are denoted either by their FlyBase accession codes or protein names when available.</p

A Lit-1 MAP Kinase SxPxxxS Motif

<p>The MAP kinase lit-1 surrounded by its interaction partners containing the SxPxxxS motif. Details are as for <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0030405#pbio-0030405-g003" target="_blank">Figure 3</a>. Yellow boxes show the location of deletion mutants known to affect the interaction. Cbr, <i>C. briggsae;</i> Cel, <i>C. elegans</i>.</p

In Vivo Tracking of Human Hematopoiesis Reveals Patterns of Clonal Dynamics during Early and Steady-State Reconstitution Phases

Hematopoietic stem/progenitor cells (HSPCs) are capable of supporting the lifelong production of blood cells exerting a wide spectrum of functions. Lentiviral vector HSPC gene therapy generates a human hematopoietic system stably marked at the clonal level by vector integration sites (ISs). Using IS analysis, we longitudinally tracked >89,000 clones from 15 distinct bone marrow and peripheral blood lineages purified up to 4 years after transplant in four Wiskott-Aldrich syndrome patients treated with HSPC gene therapy. We measured at the clonal level repopulating waves, populations’ sizes and dynamics, activity of distinct HSPC subtypes, contribution of various progenitor classes during the early and late post-transplant phases, and hierarchical relationships among lineages. We discovered that in-vitro-manipulated HSPCs retain the ability to return to latency after transplant and can be physiologically reactivated, sustaining a stable hematopoietic output. This study constitutes in vivo comprehensive tracking in humans of hematopoietic clonal dynamics during the early and late post-transplant phases