@misc{DurekSchudomaWeckwerthetal.2009,
  author    = {Durek, Pawel and Schudoma, Christian and Weckwerth, Wolfram and Selbig, Joachim and Walther, Dirk},
  title     = {Detection and characterization of 3D-signature phosphorylation site motifs and their contribution towards improved phosphorylation site prediction in proteins},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-45129},
  year      = {2009},
  abstract  = {Background: Phosphorylation of proteins plays a crucial role in the regulation and activation of metabolic and signaling pathways and constitutes an important target for pharmaceutical intervention. Central to the phosphorylation process is the recognition of specific target sites by protein kinases followed by the covalent attachment of phosphate groups to the amino acids serine, threonine, or tyrosine. The experimental identification as well as computational prediction of phosphorylation sites (P-sites) has proved to be a challenging problem. Computational methods have focused primarily on extracting predictive features from the local, one-dimensional sequence information surrounding phosphorylation sites. Results: We characterized the spatial context of phosphorylation sites and assessed its usability for improved phosphorylation site predictions. We identified 750 non-redundant, experimentally verified sites with three-dimensional (3D) structural information available in the protein data bank (PDB) and grouped them according to their respective kinase family. We studied the spatial distribution of amino acids around phosphorserines, phosphothreonines, and phosphotyrosines to extract signature 3D-profiles. Characteristic spatial distributions of amino acid residue types around phosphorylation sites were indeed discernable, especially when kinase-family-specific target sites were analyzed. To test the added value of using spatial information for the computational prediction of phosphorylation sites, Support Vector Machines were applied using both sequence as well as structural information. When compared to sequence-only based prediction methods, a small but consistent performance improvement was obtained when the prediction was informed by 3D-context information. Conclusion: While local one-dimensional amino acid sequence information was observed to harbor most of the discriminatory power, spatial context information was identified as relevant for the recognition of kinases and their cognate target sites and can be used for an improved prediction of phosphorylation sites. A web-based service (Phos3D) implementing the developed structurebased P-site prediction method has been made available at http://phos3d.mpimp-golm.mpg.de.},
  language  = {en}
}
@article{BaesslerWeissWienkoopetal.2009,
  author    = {Baessler, Olivia Y. and Weiss, Julia and Wienkoop, Stefanie and Lehmann, Karola and Scheler, Christian and Doelle, Sabine and Schwarz, Dietmar and Franken, Philipp and George, Eckhard and Worm, Margitta and Weckwerth, Wolfram},
  title     = {Evidence for novel tomato seed allergens : IgE-reactive legumin and vicilin proteins identified by multidimensional protein fractionation-mass spectrometry and in silico epitope modeling},
  issn      = {1535-3893},
  doi       = {10.1021/Pr800186d},
  year      = {2009},
  abstract  = {Tomato fruit and seed allergens were detected by IgE-immunoblotting using sera from 18 adult tomato-sensitized patients selected based on a positive history skin prick test (SPT) and specific Immunglobulin (Ig) E-levels. Isolated tomato seed total protein showed high SPT activity comparable or even higher than tomato fruit protein. For the molecular characterization of tomato seed allergens, a multidimensional protein fractionation strategy and LC-MS/MS was used. Two legumin- and vicilin-proteins were purified and showed strong IgE-reactivity in immunoblots. Individual patient sera exhibited varying IgE-sensitivity against the purified proteins. In silico structural modeling indicates high homology between epitopes of known walnut allergens and the detected IgE-crossreactive tomato proteins.},
  language  = {en}
}
@article{KempaHummelSchwemmeretal.2009,
  author    = {Kempa, Stefan and Hummel, Jan and Schwemmer, Thorsten and Pietzke, Matthias and Strehmel, Nadine and Wienkoop, Stefanie and Kopka, Joachim and Weckwerth, Wolfram},
  title     = {An automated GCxGC-TOF-MS protocol for batch-wise extraction and alignment of mass isotopomer matrixes from differential C-13-labelling experiments : a case study for photoautotrophic-mixotrophic grown Chlamydomonas reinhardtii cells},
  issn      = {0233-111X},
  doi       = {10.1002/jobm.200800337},
  year      = {2009},
  abstract  = {Two dimensional gas chromatography coupled to time-of-flight mass spectrometry (GCxGC-TOF-MS) is a promising technique to overcome limits of complex metabolome analysis using one dimensional GC-TOF-MS. Especially at the stage of data export and data mining, however, convenient procedures to cope with the complexity of GCxGC-TOF-MS data are still in development. Here, we present a high sample throughput protocol exploiting first and second retention index for spectral library search and subsequent construction of a high dimensional data matrix useful for statistical analysis. The method was applied to the analysis of 13 C-labelling experiments in the unicellular green alga Chlamydomonas reinhardtii. We developed a rapid sampling and extraction procedure for Chlamydomonas reinhardtii laboratory strain (CC503), a cell wall deficient mutant. By testing all published quenching protocols we observed dramatic metabolite leakage rates for certain metabolites. To circumvent metabolite leakage, samples were directly quenched and analyzed without separation of the medium. The growth medium was adapted to this rapid sampling protocol to avoid interference with GCxGC-TOF-MS analysis. To analyse batches of samples a new software tool, MetMax, was implemented which extracts the isotopomer matrix from stable isotope labelling experiments together with the first and second retention index (RI1 and RI2). To exploit RI1 and RI2 for metabolite identification we used the Golm metabolome database (GMD [1] with RI1/ RI2-reference spectra and new search algorithms. Using those techniques we analysed the dynamics of (CO2)-C-13 and C-13- acetate uptake in Chlamydomonas reinhardtii cells in two different steady states namely photoautotrophic and mixotrophic growth conditions.},
  language  = {en}
}