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The movement protein (MP) of parietaria mottle virus (PMoV) is required for virus cell-to-cell movement. Bioinformatics analysis identified two hydrophilic non-contiguous regions (R1 and R2) rich in the basic amino acids lysine and arginine and with the predicted secondary structure of an α-helix. Different approaches were used to determine the implication of the R1 and R2 regions in RNA binding, plasmodesmata (PD) targeting and cell-to-cell movement. EMSA (Electrophoretic Mobility Shift Assay) showed that both regions have RNA-binding activity whereas that mutational analysis reported that either deletion of any of these regions, or loss of the basic amino acids, interfered with the viral intercellular movement. Subcellular localization studies showed that PMoV MP locates at PD. Mutants designed to impeded cell-to-cell movement failed to accumulate at PD indicating that basic residues in both R1 and R2 are critical for binding the MP at PD.
Pubmed ID: 24583367 RIS Download
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Group headed by Professor David Jones, and was originally founded as the Joint Research Council funded Bioinformatics Unit within the Department of Computer Science at University College London. Supports the following tools: Protein Structure Prediction Threading (THREADER) Ab initio folding simulations Secondary structure prediction (PSIPRED) Protein disorder prediction (DISOPRED) Protein domain prediction (DomPred) Database of protein disorder (DisoDB) Protein Sequence Analysis Protein function prediction (ffpred) Metsite: Metal binding residue prediction HSPred : Protein-protein interaction characterisation Amino acid substitution matrices Hidden Markov Models (collaboration with N. Goldman, Cambridge, & J. Thorne, NCSU) Genome Analysis Genomic fold recognition (GenTHREADER) Genome annotation using software agents Protein Structure Classification CATH (collaboration with J. Thornton & C. Orengo, UCL Biochemistry) Transmembrane Protein Modelling MEMSAT & MEMSATSVM Folding In Lipid Membranes (FILM) MEMPACK Biological Applications of Data-mining and Machine Learning Techniques Information extraction for biological research (BioRat) Microarray Analysis Data integration for microarray analysis Data visualization Systems Biology Systems biology applied to stem cells Legacy Services (to be retired shortly) Comparison of structure classifications (CATH/SCOP/FSSP) Genomic Threading Database (GTD)
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