Protein kinases associated with the yeast phosphoproteome

BACKGROUND: Protein phosphorylation is an extremely important mechanism of cellular regulation. A large-scale study of phosphoproteins in a whole-cell lysate of Saccharomyces cerevisiae has previously identified 383 phosphorylation sites in 216 peptide sequences. However, the protein kinases responsible for the phosphorylation of the identified proteins have not previously been assigned. RESULTS: We used Predikin in combination with other bioinformatic tools, to predict which of 116 unique protein kinases in yeast phosphorylates each experimentally determined site in the phosphoproteome. The prediction was based on the match between the phosphorylated 7-residue sequence and the predicted substrate specificity of each kinase, with the highest weight applied to the residues or positions that contribute most to the substrate specificity. We estimated the reliability of the predictions by performing a parallel prediction on phosphopeptides for which the kinase has been experimentally determined. CONCLUSION: The results reveal that the functions of the protein kinases and their predicted phosphoprotein substrates are often correlated, for example in endocytosis, cytokinesis, transcription, replication, carbohydrate metabolism and stress response. The predictions link phosphoproteins of unknown function with protein kinases with known functions and vice versa, suggesting functions for the uncharacterized proteins. The study indicates that the phosphoproteins and the associated protein kinases represented in our dataset have housekeeping cellular roles; certain kinases are not represented because they may only be activated during specific cellular responses. Our results demonstrate the utility of our previously reported protein kinase substrate prediction approach (Predikin) as a tool for establishing links between kinases and phosphoproteins that can subsequently be tested experimentally

Structural basis of nuclear import of flap endonuclease 1 (FEN1)

Flap endonuclease 1 (FEN1) is a member of the nuclease family and is structurally conserved from bacteriophages to humans. This protein is involved in multiple DNA-processing pathways, including Okazaki fragment maturation, stalled replication-fork rescue, telomere maintenance, long-patch base-excision repair and apoptotic DNA fragmentation. FEN1 has three functional motifs that are responsible for its nuclease, PCNA-interaction and nuclear localization activities, respectively. It has been shown that the C-terminal nuclear localization sequence (NLS) facilitates nuclear localization of the enzyme during the S phase of the cell cycle and in response to DNA damage. To determine the structural basis of the recognition of FEN1 by the nuclear import receptor importin alpha, the crystal structure of the complex of importin alpha with a peptide corresponding to the FEN1 NLS was solved. Structural studies confirmed the binding of the FEN1 NLS as a classical bipartite NLS; however, in contrast to the previously proposed (KRKX8KKK367)-K-354 sequence, it is the (354)KRX(10)KKAK(369) sequence that binds to importin alpha. This result explains the incomplete inhibition of localization that was observed on mutating residues (KKK367)-K-365. Acidic and polar residues in the X-10 linker region close to the basic clusters play an important role in binding to importin alpha. These results suggest that the basic residues in the N-terminal basic cluster of bipartite NLSs may play roles that are more critical than those of the many basic residues in the C-terminal basic cluster

Predicting Protein Kinase Specificity: Predikin Update and Performance in the DREAM4 Challenge

Predikin is a system for making predictions about protein kinase specificity. It was declared the “best performer” in the protein kinase section of the Peptide Recognition Domain specificity prediction category of the recent DREAM4 challenge (an independent test using unpublished data). In this article we discuss some recent improvements to the Predikin web server — including a more streamlined approach to substrate-to-kinase predictions and whole-proteome predictions — and give an analysis of Predikin's performance in the DREAM4 challenge. We also evaluate these improvements using a data set of yeast kinases that have been experimentally characterised, and we discuss the usefulness of Frobenius distance in assessing the predictive power of position weight matrices

PREDIVAC: CD4+T-cell epitope prediction for vaccine design that covers 95% of HLA class II DR protein diversity

Background: CD4+ T-cell epitopes play a crucial role in eliciting vigorous protective immune responses during peptide (epitope)-based vaccination. The prediction of these epitopes focuses on the peptide binding process by MHC class II proteins. The ability to account for MHC class II polymorphism is critical for epitope-based vaccine design tools, as different allelic variants can have different peptide repertoires. In addition, the specificity of CD4+ T-cells is often directed to a very limited set of immunodominant peptides in pathogen proteins. The ability to predict what epitopes are most likely to dominate an immune response remains a challenge

PACKAGING PROCESS RENOVATION IN THE PHARMACEUTICAL COMPANY

V diplomski nalogi obravnavamo optimizacijo pakiranja trdnih farmacevtskih oblik. Naloga se ukvarja predvsem s sistematskim spremljanjem razlogov za izgubo produktivnosti in pristopi k njihovemu razreševanju. Analiza procesa je pokazala, da trenutni zajem podatkov vedno ni omogočal določiti osnovni vzrokov, ki povzročajo izgubo produktivnosti. Podatki so se zaradi različnih razlogov neustrezno interpretirali, kar je povzročalo odmik od dejanskih vzrokov nastanka zastoja. Ugotovitve v nalogi pokažejo na velik pojav ponovljivosti vzrokov za zastoje. Le te je potrebno smiselno vsebinsko definirati, označiti in z ustrezno programsko opremo in spremljati njihovo odpravo. Na ta način zagotovimo trajno odpravljanje vzrokov za zastoje in preprečimo ponovljivost le teh. V reševanje so vključeni vsi neposredno vpleteni v proces pakiranja. Zaradi poglobljene definicije težav in ustrezne povratne informacije, ki jo omogoča novi sistem, se zaposlenim zvišuje nivo znanja in omogoča večjo samostojnost pri odpravi motenj. Vzporedno se nadgrajuje tudi dokumentacija za ustrezno ravnanje v primeru zastoja, ki služi kot pomoč ostalim ali v primeru ponovitve težave. Krepi se kultura razmišljanja v smeri reševanja problemov. Tak način dela vpliva na stalno izboljševanje pakirnega procesa. Novo oblikovani predlagani proces obravnavanja in odprave motenj, se lahko integrira na vse pakirne linije v podjetju in tako na dolgi rok doprinese izboljšanju učinkovitosti procesa pakiranja in s tem konkurenčni prednosti in pozitivnim poslovnim učinkom.The thesis paper discusses the optimization of packaging of solid pharmaceutical forms. The main focus of the thesis is placed on the systematic monitoring of the reasons for the loss of productivity and approaches for their solving. The analysis of the process has shown that the current data acquisition does not always enable us to determine the basic reasons that cause the loss of productivity. The data has been misinterpreted due to several factors, which resulted in the deviation from the actual reasons for the delay. The findings of the thesis point to a great reproducibility when it comes to causes for delays. The causes must be meaningfully defined, marked and monitored with a corresponding software while they are dispatched. All directly connected to the process of packaging are actively involved in it. Due to a systematic defining of the issues and adequate feedback, which are both enabled by the new system, employees are raising their level of knowledge and are also more independent when it comes to solving disturbances. Alongside to this also the documentation for proper engagement in the case of a standstill is updated. This documentation functions as an aid to other workers in the case of a relapse. Additionally, the problem-solving culture is enhanced, thus a continuous improvement of the packaging process is made possible. The newly-formed and suggested approach of treatment and elimination of interferences can be integrated to all packaging lines in a company and can contribute to a long-term competitiveness and positive business results

Using a BLOSUM cut-off value of 0 instead of 1 does not adversely effect Frobenius distance.

<p>The Frobenius distance is shown for 12 kinases using BLOSUM62 and a cut-off value of 1 (blue) and 0 (red). In each case it is apparent that switching from a cut-off value of 1 to 0 has little effect on the Frobenius distance.</p

Frobenius distances for Predikin position weight matrices built with the submitted and new method.

<p>The table shows Frobenius distances for position weight matrices built with the submitted and new method. In two of three cases there is a very significant improvement in p-value, while in the third case there is a very small increase in distance.</p

Number of position weight matrices built using each BLOSUM matrix.

<p>Each bar represents the number of kinases for which a position weight matrix could be built using each of 16 BLOSUM matrices. The blue bars show the number of position weight matrices built when using a cut-off value of 1, and the red bars show the number when using a cut-off value of 0. When considering just the number of position weight matrices, BLOSUM30 is clearly superior, and this is even more apparent when using a cut-off value of 0.</p

Predictive performance of old- and new-style position weight matrices.

<p>The predictive power, as assessed by the area under the ROC curve analysis, of the new-style matrices (black dashed) is virtually identical to that of the old-style (red solid). Demonstrating that Frobenius distance does not necessary provide an insight as to which weight matrix is the best for predictive purposes.</p

Comparison of old- and new-style position weight matrices.

<p>The blue circles show the Frobenius distance for yeast protein kinases achieved using the old style Predikin position weight matrices sorted into ascending order. The red squares show the corresponding distance using the new style position weight matrix. In all cases except one the new style position weight matrix produces a smaller distance than the old style as demonstrated by the green line being below the red.</p