80 research outputs found

    Primary structures of blue-green algal proteins

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    A plant homologue to mammalian brain 14-3-3 protein and protein kinase C inhibitor

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    We have isolated cDNA clones of Spinacea oleracea L. and Oenothera hookeri of 930 and 1017 base pairs, respectively. The open reading frame deduced from the Oenothera sequence codes for a protein of a calculated molecular mass of 29 200. The primary amino acid sequence exhibits a very high degree (88%) of homology to the 14-3-3 protein from bovine brain, and protein kinase C inhibitor from sheep brain. Subsequently the plant protein was partially purified from leaf extract. The partially purified plant protein inhibited protein kinase C from sheep brain in a heterologous assay system. The active fraction consisted of 5–6 different polypeptides of similar molecular size. One of these proteins crossreacted with a peptide-specific antibody against protein kinase C inhibitor protein from sheep brain

    Amino acid sequence around the active serine in the acyl transferase domain of rabbit mammary fatty acid synthase

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    AbstractRabbit mammary fatty acid synthase was labelled in the acyl transferase domain(s) by the formation of the O-ester intermediates after incubation with [14C]acetyl- or malonyl-CoA. Elastase peptides containing the labelled acyl groups were isolated using high performance liquid chromatography and sequenced by fast atom bombardment mass spectrometry. An identical peptide (acyl-Serî—¸Leuî—¸Glyî—¸Gluî—¸Valî—¸Ala) was obtained after labelling with acetyl- or malonyl-CoA. This confirms the hypothesis that, unlike Escherichia coli or yeast, a single transferase catalyses the transfer of both acetyl- and malonyl-groups in the mammalian complex. The sequence at this site is compared with that around the active serine in other acyl transferases and hydrolases

    Amino acid sequence of β-galactoside-binding bovine heart lectin Member of a novel class of vertebrate proteins

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    AbstractA variety of animal tissues contain β-galactoside-binding lectins with molecular masses in the range 13–17 kDa. There is evidence that these lectins may constitute a new protein family although their function in vivo is not yet clear. In this work the major part of the amino acid sequence of the 13 kDa lectin from bovine heart muscle has been determined. Comparison of this sequence with the cDNA-deduced sequence published for the chick embryo skin lectin showed 58% homology. Comparison of the bovine lectin sequence with partial sequences from two cDNA clones from a human hepatoma library and partial amino acid sequences of human lung lectin showed 70, 40 and 85% homology, respectively. The sequences of these vertebrate lectins are thus clearly related, supporting earlier results of immunological cross-reactivity within this group of proteins. Computer searching of protein sequence databases did not detect significant homologies between the bovine lectin sequence and other known proteins

    Interaction of Akt-Phosphorylated Ataxin-1 with 14-3-3 Mediates Neurodegeneration in Spinocerebellar Ataxia Type 1

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    AbstractSpinocerebellar ataxia type 1 (SCA1) is one of several neurological disorders caused by a CAG repeat expansion. In SCA1, this expansion produces an abnormally long polyglutamine tract in the protein ataxin-1. Mutant polyglutamine proteins accumulate in neurons, inducing neurodegeneration, but the mechanism underlying this accumulation has been unclear. We have discovered that the 14-3-3 protein, a multifunctional regulatory molecule, mediates the neurotoxicity of ataxin-1 by binding to and stabilizing ataxin-1, thereby slowing its normal degradation. The association of ataxin-1 with 14-3-3 is regulated by Akt phosphorylation, and in a Drosophila model of SCA1, both 14-3-3 and Akt modulate neurodegeneration. Our finding that phosphatidylinositol 3-kinase/Akt signaling and 14-3-3 cooperate to modulate the neurotoxicity of ataxin-1 provides insight into SCA1 pathogenesis and identifies potential targets for therapeutic intervention

    Biopsy confirmation of metastatic sites in breast cancer patients:clinical impact and future perspectives

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    Determination of hormone receptor (estrogen receptor and progesterone receptor) and human epidermal growth factor receptor 2 status in the primary tumor is clinically relevant to define breast cancer subtypes, clinical outcome,and the choice of therapy. Retrospective and prospective studies suggest that there is substantial discordance in receptor status between primary and recurrent breast cancer. Despite this evidence and current recommendations,the acquisition of tissue from metastatic deposits is not routine practice. As a consequence, therapeutic decisions for treatment in the metastatic setting are based on the features of the primary tumor. Reasons for this attitude include the invasiveness of the procedure and the unreliable outcome of biopsy, in particular for biopsies of lesions at complex visceral sites. Improvements in interventional radiology techniques mean that most metastatic sites are now accessible by minimally invasive methods, including surgery. In our opinion, since biopsies are diagnostic and changes in biological features between the primary and secondary tumors can occur, the routine biopsy of metastatic disease needs to be performed. In this review, we discuss the rationale for biopsy of suspected breast cancer metastases, review issues and caveats surrounding discordance of biomarker status between primary and metastatic tumors, and provide insights for deciding when to perform biopsy of suspected metastases and which one (s) to biopsy. We also speculate on the future translational implications for biopsy of suspected metastatic lesions in the context of clinical trials and the establishment of bio-banks of biopsy material taken from metastatic sites. We believe that such bio-banks will be important for exploring mechanisms of metastasis. In the future,advances in targeted therapy will depend on the availability of metastatic tissue

    The Structural Basis for 14-3-3:Phosphopeptide Binding Specificity

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    AbstractThe 14-3-3 family of proteins mediates signal transduction by binding to phosphoserine-containing proteins. Using phosphoserine-oriented peptide libraries to probe all mammalian and yeast 14-3-3s, we identified two different binding motifs, RSXpSXP and RXY/FXpSXP, present in nearly all known 14-3-3 binding proteins. The crystal structure of 14-3-3ζ complexed with the phosphoserine motif in polyoma middle-T was determined to 2.6 Å resolution. The bound peptide is in an extended conformation, with a tight turn created by the pS +2 Pro in a cis conformation. Sites of peptide–protein interaction in the complex rationalize the peptide library results. Finally, we show that the 14-3-3 dimer binds tightly to single molecules containing tandem repeats of phosphoserine motifs, implicating bidentate association as a signaling mechanism with molecules such as Raf, BAD, and Cbl

    MCOIN: a novel heuristic for determining transcription factor binding site motif width

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    BACKGROUND: In transcription factor binding site discovery, the true width of the motif to be discovered is generally not known a priori. The ability to compute the most likely width of a motif is therefore a highly desirable property for motif discovery algorithms. However, this is a challenging computational problem as a result of changing model dimensionality at changing motif widths. The complexity of the problem is increased as the discovered model at the true motif width need not be the most statistically significant in a set of candidate motif models. Further, the core motif discovery algorithm used cannot guarantee to return the best possible result at each candidate width. RESULTS: We present MCOIN, a novel heuristic for automatically determining transcription factor binding site motif width, based on motif containment and information content. Using realistic synthetic data and previously characterised prokaryotic data, we show that MCOIN outperforms the current most popular method (E-value of the resulting multiple alignment) as a predictor of motif width, based on mean absolute error. MCOIN is also shown to choose models which better match known sites at higher levels of motif conservation, based on ROC analysis. CONCLUSIONS: We demonstrate the performance of MCOIN as part of a deterministic motif discovery algorithm and conclude that MCOIN outperforms current methods for determining motif width
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