Rune Linding

GlobPlot: exploring protein sequences for globularity and disorder

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. Non-globular 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.

Systematic discovery of in vivo phosphorylation networks

Protein kinases control cellular decision processes by phosphorylating specific substrates. Thousands of in vivo phosphorylation sites have been identified, mostly by proteome-wide mapping. However, systematically matching these sites to specific kinases is presently infeasible, due to limited specificity of consensus motifs, and the influence of contextual factors, such as protein scaffolds, localization, and expression, on cellular substrate specificity. We have developed an approach (NetworKIN) that augments motif-based predictions with the network context of kinases and phosphoproteins. The latter provides 60%-80% of the computational capability to assign in vivo substrate specificity. NetworKIN pinpoints kinases responsible for specific phosphorylations and yields a 2.5-fold improvement in the accuracy with which phosphorylation networks can be constructed. Applying this approach to DNA damage signaling, we show that 53BP1 and Rad50 are phosphorylated by CDK1 and ATM, respectively. We describe a scalable strategy to evaluate predictions, which suggests that BCLAF1 is a GSK-3 substrate.

Dynamic modularity in protein interaction networks predicts breast cancer outcome

Changes in the biochemical wiring of oncogenic cells drives phenotypic transformations that directly affect disease outcome. Here we examine the dynamic structure of the human protein interaction network (interactome) to determine whether changes in the organization of the interactome can be used to predict patient outcome. An analysis of hub proteins identified intermodular hub proteins that are co-expressed with their interacting partners in a tissue-restricted manner and intramodular hub proteins that are co-expressed with their interacting partners in all or most tissues. Substantial differences in biochemical structure were observed between the two types of hubs. Signaling domains were found more often in intermodular hub proteins, which were also more frequently associated with oncogenesis. Analysis of two breast cancer patient cohorts revealed that altered modularity of the human interactome may be useful as an indicator of breast cancer prognosis.

Linear Motif Atlas for Phosphorylation-Dependent Signaling

Created with both in vitro and in vivo data, NetPhorest is an atlas of consensus sequence motifs for 179 kinases and 104 phosphorylation-dependent binding domains and reveals new insight into phosphorylation-dependent signaling. An Atlas of Phosphorylation NetPhorest is a community resource that uses phylogenetic trees to organize data from both in vivo and in vitro experiments to derive sequence specificities for 179 kinases and 104 domains (SH2, PTB, BRCT, WW, and 14–3–3) that bind to phosphorylated sites. The resulting atlas of linear motifs revealed that oncogenic kinases tend to be less specific in the target sequences they phosphorylate than their non-oncogenic counterparts, that autophosphorylation sites tend to be more variable than other substrates of a given kinase, and that coupling interaction domains with kinase domains may allow phosphorylation site specificity to be low while still maintaining substrate specificity. Systematic and quantitative analysis of protein phosphorylation is revealing dynamic regulatory networks underlying cellular responses to environmental cues. However, matching these sites to the kinases that phosphorylate them and the phosphorylation-dependent binding domains that may subsequently bind to them remains a challenge. NetPhorest is an atlas of consensus sequence motifs that covers 179 kinases and 104 phosphorylation-dependent binding domains [Src homology 2 (SH2), phosphotyrosine binding (PTB), BRCA1 C-terminal (BRCT), WW, and 14–3–3]. The atlas reveals new aspects of signaling systems, including the observation that tyrosine kinases mutated in cancer have lower specificity than their non-oncogenic relatives. The resource is maintained by an automated pipeline, which uses phylogenetic trees to structure the currently available in vivo and in vitro data to derive probabilistic sequence models of linear motifs. The atlas is available as a community resource (http://netphorest.info).

Phosphorylation Dynamics during Early Differentiation of Human Embryonic Stem Cells

Pluripotent stem cells self-renew indefinitely and possess characteristic protein-protein networks that remodel during differentiation. How this occurs is poorly understood. Using quantitative mass spectrometry, we analyzed the (phospho)proteome of human embryonic stem cells (hESCs) during differentiation induced by bone morphogenetic protein (BMP) and removal of hESC growth factors. Of 5222 proteins identified, 1399 were phosphorylated on 3067 residues. Approximately 50% of these phosphosites were regulated within 1 hr of differentiation induction, revealing a complex interplay of phosphorylation networks spanning different signaling pathways and kinase activities. Among the phosphorylated proteins was the pluripotency-associated protein SOX2, which was SUMOylated as a result of phosphorylation. Using the data to predict kinase-substrate relationships, we reconstructed the hESC kinome; CDK1/2 emerged as central in controlling self-renewal and lineage specification. The findings provide new insights into how hESCs exit the pluripotent state and present the hESC (phospho)proteome resource as a complement to existing pluripotency network databases.

NetworKIN: a resource for exploring cellular phosphorylation networks

Protein kinases control cellular responses by phosphorylating specific substrates. Recent proteome-wide mapping of protein phosphorylation sites by mass spectrometry has discovered thousands of in vivo sites. Systematically assigning all 518 human kinases to all these sites is a challenging problem. The NetworKIN database (http://networkin.info) integrates consensus substrate motifs with context modelling for improved prediction of cellular kinase–substrate relations. Based on the latest human phosphoproteome from the Phospho.ELM and PhosphoSite databases, the resource offers insight into phosphorylation-modulated interaction networks. Here, we describe how NetworKIN can be used for both global and targeted molecular studies. Via the web interface users can query the database of precomputed kinase–substrate relations or obtain predictions on novel phosphoproteins. The database currently contains a predicted phosphorylation network with 20 224 site-specific interactions involving 3978 phosphoproteins and 73 human kinases from 20 families.

Comparative analysis reveals conserved protein phosphorylation networks implicated in multiple diseases.

Comparing the human phosphoproteome to that of flies, worms, and yeast reveals insight into evolution and disease. Phosphorylation Networks in Disease and Evolution Insights into the evolution of protein phosphorylation were revealed by combining the results from two computational analyses—a sequence-alignment approach and a kinase-substrate network alignment approach. The two approaches yielded different, but somewhat overlapping, sets of conserved phosphoproteins among humans and the model organisms. The first provided a set of genes encoding phosphoproteins that had positionally conserved phosphorylation sites, whereas the second included many functionally conserved phosphoproteins that lacked this positional conservation. Enrichment analysis of the genes identified through the kinase-substrate network approach suggested that genes encoding phosphorylated signaling hubs were enriched in disease-associated genes (defined by Online Mendelian Inheritance in Man), and both approaches showed that genes encoding conserved phosphoproteins were enriched in genes associated with cancer. The functional annotation of the two gene sets suggested that positional conservation is common in regions that are structurally constrained, such as those regulated by allosteric interactions, and that the kinase-substrate network method may aid in analyzing fast-evolving signaling processes, where functional conservation does not require positional conservation. The analysis also suggests that conserved regulatory networks may be involved in different diseases. Protein kinases enable cellular information processing. Although numerous human phosphorylation sites and their dynamics have been characterized, the evolutionary history and physiological importance of many signaling events remain unknown. Using target phosphoproteomes determined with a similar experimental and computational pipeline, we investigated the conservation of human phosphorylation events in distantly related model organisms (fly, worm, and yeast). With a sequence-alignment approach, we identified 479 phosphorylation events in 344 human proteins that appear to be positionally conserved over ~600 million years of evolution and hence are likely to be involved in fundamental cellular processes. This sequence-alignment analysis suggested that many phosphorylation sites evolve rapidly and therefore do not display strong evolutionary conservation in terms of sequence position in distantly related organisms. Thus, we devised a network-alignment approach to reconstruct conserved kinase-substrate networks, which identified 778 phosphorylation events in 698 human proteins. Both methods identified proteins tightly regulated by phosphorylation as well as signal integration hubs, and both types of phosphoproteins were enriched in proteins encoded by disease-associated genes. We analyzed the cellular functions and structural relationships for these conserved signaling events, noting the incomplete nature of current phosphoproteomes. Assessing phosphorylation conservation at both site and network levels proved useful for exploring both fast-evolving and ancient signaling events. We reveal that multiple complex diseases seem to converge within the conserved networks, suggesting that disease development might rely on common molecular networks.

A Mitotic Phosphorylation Feedback Network Connects Cdk1, Plk1, 53BP1, and Chk2 to Inactivate the G2/M DNA Damage Checkpoint

A combined computational and biochemical approach reveals how mitotic kinases allow cell division to proceed in the presence of DNA damage.

Normalization of nomenclature for peptide motifs as ligands of modular protein domains

We propose a normalization of symbols and terms used to describe, accurately and succinctly, the detailed interactions between amino acid residues of pairs of interacting proteins at protein:protein (or protein:peptide) interfaces. Our aim is to unify several diverse descriptions currently in use in order to facilitate communication in the rapidly progressing field of signaling by protein domains. In order for the nomenclature to be convenient and widely used, we also suggest a parallel set of symbols restricted to the ASCII format allowing accurate parsing of the nomenclature to a computer‐readable form. This proposal will be reviewed in the future and will therefore be open for the inclusion of new rules, modifications and changes.

Eukaryotic Protein Domains as Functional Units of Cellular Evolution

Clustering proteins into groups on the basis of their domain compositions provides insight into protein evolution. Domains for Change Protein domains endow proteins with specific activities and the ability to interact with specific partners. Most protein domains occur in many proteins and most proteins have multiple domains, but the combinations of domains are far fewer than would be predicted, suggesting that there is evolutionary pressure that preserves certain domain combinations. Jin et al. use a proteome-wide clustering method to identify eukaryotic protein domain combinations that correlate with evolutionary change. Their analysis suggests that reciprocal interactions between a protein and its microenvironment constrain the repertoire of domains that control specific cellular functions. They analyzed the proteins in seven eukaryotic species and organized the domains into 1245 “domain clubs,” with the majority of clubs containing proteins with multiple distinct domains and proteins with rich interrelationships among members of different clubs. They grouped proteins on the basis of their domain clubs into functional trees and were able to place domains of unknown function into functional groups, as well as make predictions about the role domain evolution contributes to the evolution of protein function within a molecular environment, as well as to the evolution of molecular environments. Modular protein domains are functional units that can be modified through the acquisition of new intrinsic activities or by the formation of novel domain combinations, thereby contributing to the evolution of proteins with new biological properties. Here, we assign proteins to groups with related domain compositions and functional properties, termed “domain clubs,” which we use to compare multiple eukaryotic proteomes. This analysis shows that different domain types can take distinct evolutionary trajectories, which correlate with the conservation, gain, expansion, or decay of particular biological processes. Evolutionary jumps are associated with a domain that coordinately acquires a new intrinsic function and enters new domain clubs, thereby providing the modified domain with access to a new cellular microenvironment. We also coordinately analyzed the covalent and noncovalent interactions of different domain types to assess the molecular compartment occupied by each domain. This reveals that specific subsets of domains demarcate particular cellular processes, such as growth factor signaling, chromatin remodeling, apoptotic and inflammatory responses, or vesicular trafficking. We suggest that domains, and the proteins in which they reside, are selected during evolution through reciprocal interactions with protein domains in their local microenvironment. Based on this scheme, we propose a mechanism by which Tudor domains may have evolved to support different modes of epigenetic regulation and suggest a role for the germline group of mammalian Tudor domains in Piwi-regulated RNA biology.