197 research outputs found

    The alpha-kinase family: an exceptional branch on the protein kinase tree

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    The alpha-kinase family represents a class of atypical protein kinases that display little sequence similarity to conventional protein kinases. Early studies on myosin heavy chain kinases in Dictyostelium discoideum revealed their unusual propensity to phosphorylate serine and threonine residues in the context of an alpha-helix. Although recent studies show that some members of this family can also phosphorylate residues in non-helical regions, the name alpha-kinase has remained. During evolution, the alpha-kinase domains combined with many different functional subdomains such as von Willebrand factor-like motifs (vWKa) and even cation channels (TRPM6 and TRPM7). As a result, these kinases are implicated in a large variety of cellular processes such as protein translation, Mg2+ homeostasis, intracellular transport, cell migration, adhesion, and proliferation. Here, we review the current state of knowledge on different members of this kinase family and discuss the potential use of alpha-kinases as drug targets in diseases such as cancer

    Construction and Analysis of an Integrated Regulatory Network Derived from High-Throughput Sequencing Data

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    We present a network framework for analyzing multi-level regulation in higher eukaryotes based on systematic integration of various high-throughput datasets. The network, namely the integrated regulatory network, consists of three major types of regulation: TF→gene, TF→miRNA and miRNA→gene. We identified the target genes and target miRNAs for a set of TFs based on the ChIP-Seq binding profiles, the predicted targets of miRNAs using annotated 3′UTR sequences and conservation information. Making use of the system-wide RNA-Seq profiles, we classified transcription factors into positive and negative regulators and assigned a sign for each regulatory interaction. Other types of edges such as protein-protein interactions and potential intra-regulations between miRNAs based on the embedding of miRNAs in their host genes were further incorporated. We examined the topological structures of the network, including its hierarchical organization and motif enrichment. We found that transcription factors downstream of the hierarchy distinguish themselves by expressing more uniformly at various tissues, have more interacting partners, and are more likely to be essential. We found an over-representation of notable network motifs, including a FFL in which a miRNA cost-effectively shuts down a transcription factor and its target. We used data of C. elegans from the modENCODE project as a primary model to illustrate our framework, but further verified the results using other two data sets. As more and more genome-wide ChIP-Seq and RNA-Seq data becomes available in the near future, our methods of data integration have various potential applications
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