pkaPS: prediction of protein kinase A phosphorylation sites with the simplified kinase-substrate binding model

BACKGROUND: Protein kinase A (cAMP-dependent kinase, PKA) is a serine/threonine kinase, for which ca. 150 substrate proteins are known. Based on a refinement of the recognition motif using the available experimental data, we wished to apply the simplified substrate protein binding model for accurate prediction of PKA phosphorylation sites, an approach that was previously successful for the prediction of lipid posttranslational modifications and of the PTS1 peroxisomal translocation signal. RESULTS: Approximately 20 sequence positions flanking the phosphorylated residue on both sides have been found to be restricted in their sequence variability (region -18...+23 with the site at position 0). The conserved physical pattern can be rationalized in terms of a qualitative binding model with the catalytic cleft of the protein kinase A. Positions -6...+4 surrounding the phosphorylation site are influenced by direct interaction with the kinase in a varying degree. This sequence stretch is embedded in an intrinsically disordered region composed preferentially of hydrophilic residues with flexible backbone and small side chain. This knowledge has been incorporated into a simplified analytical model of productive binding of substrate proteins with PKA. CONCLUSION: The scoring function of the pkaPS predictor can confidently discriminate PKA phosphorylation sites from serines/threonines with non-permissive sequence environments (sensitivity of ~96% at a specificity of ~94%). The tool "pkaPS" has been applied on the whole human proteome. Among new predicted PKA targets, there are entirely uncharacterized protein groups as well as apparently well-known families such as those of the ribosomal proteins L21e, L22 and L6. AVAILABILITY: The supplementary data as well as the prediction tool as WWW server are available at . REVIEWERS: Erik van Nimwegen (Biozentrum, University of Basel, Switzerland), Sandor Pongor (International Centre for Genetic Engineering and Biotechnology, Trieste, Italy), Igor Zhulin (University of Tennessee, Oak Ridge National Laboratory, USA)

Application of a sensitive collection heuristic for very large protein families: Evolutionary relationship between adipose triglyceride lipase (ATGL) and classic mammalian lipases

BACKGROUND: Manually finding subtle yet statistically significant links to distantly related homologues becomes practically impossible for very populated protein families due to the sheer number of similarity searches to be invoked and analyzed. The unclear evolutionary relationship between classical mammalian lipases and the recently discovered human adipose triglyceride lipase (ATGL; a patatin family member) is an exemplary case for such a problem. RESULTS: We describe an unsupervised, sensitive sequence segment collection heuristic suitable for assembling very large protein families. It is based on fan-like expanding, iterative database searches. To prevent inclusion of unrelated hits, additional criteria are introduced: minimal alignment length and overlap with starting sequence segments, finding starting sequences in reciprocal searches, automated filtering for compositional bias and repetitive patterns. This heuristic was implemented as FAMILYSEARCHER in the ANNIE sequence analysis environment and applied to search for protein links between the classical lipase family and the patatin-like group. CONCLUSION: The FAMILYSEARCHER is an efficient tool for tracing distant evolutionary relationships involving large protein families. Although classical lipases and ATGL have no obvious sequence similarity and differ with regard to fold and catalytic mechanism, homology links detected with FAMILYSEARCHER show that they are evolutionarily related. The conserved sequence parts can be narrowed down to an ancestral core module consisting of three β-strands, one α-helix and a turn containing the typical nucleophilic serine. Moreover, this ancestral module also appears in numerous enzymes with various substrate specificities, but that critically rely on nucleophilic attack mechanisms

Hidden localization motifs: naturally occurring peroxisomal targeting signals in non-peroxisomal proteins

BACKGROUND: Can sequence segments coding for subcellular targeting or for posttranslational modifications occur in proteins that are not substrates in either of these processes? Although considerable effort has been invested in achieving low false-positive prediction rates, even accurate sequence-analysis tools for the recognition of these motifs generate a small but noticeable number of protein hits that lack the appropriate biological context but cannot be rationalized as false positives. RESULTS: We show that the carboxyl termini of a set of definitely non-peroxisomal proteins with predicted peroxisomal targeting signals interact with the peroxisomal matrix protein receptor peroxin 5 (PEX5) in a yeast two-hybrid test. Moreover, we show that examples of these proteins - chicken lysozyme, human tyrosinase and the yeast mitochondrial ribosomal protein L2 (encoded by MRP7) - are imported into peroxisomes in vivo if their original sorting signals are disguised. We also show that even prokaryotic proteins can contain peroxisomal targeting sequences. CONCLUSIONS: Thus, functional localization signals can evolve in unrelated protein sequences as a result of neutral mutations, and subcellular targeting is hierarchically organized, with signal accessibility playing a decisive role. The occurrence of silent functional motifs in unrelated proteins is important for the development of sequence-based function prediction tools and the interpretation of their results. Silent functional signals have the potential to acquire importance in future evolutionary scenarios and in pathological conditions

Electroweak Physics

We review the prospects for studies in electroweak physics at the LHC

Wiener klinische Wochenschrift / Commuter exposure to fine and ultrafine particulate matter in Vienna

Mass concentrations PM10, PM2.5, PM1, particle number concentrations of ultrafine particles and lung deposited surface area were measured during commutes with a subway, tram, bus, car and bicycle in Vienna for the first time. Obtained data were examined for significant differences in personal exposure when using various transport modalities along similar routes. Mean PM2.5 and PM1 mass concentrations were significantly higher in the subway when compared to buses. Mean PM10, PM2.5 and PM1 mass concentrations were significantly higher in the subway when compared to cars using low ventilation settings. Particle number concentrations of ultrafine particles were significantly higher in trams when compared to the subway and lung deposited surface area was significantly greater on bicycles when compared to the subway. After adjusting for different vehicle speeds, exposure to PM10, PM2.5 and PM1 along the same route length was significantly higher in the subway when compared to cars while exposure to ultrafine particles and partly also lung deposited surface area was significantly higher in bus, tram and on bicycle when compared to the subway. Car and bus passengers could be better isolated from ambient fine particulate matter than passengers in the subway, where a lot of ventilation occurs through open windows and larger doors. Tram passengers and cyclists might be exposed to increased amounts of ultrafine particles and larger lung deposited surface area due to a closer proximity to road traffic. Comparing cumulative exposure along the same route length leads to different results and favors faster traffic modes, such as the subway.(VLID)357362