Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: EC:2.7.11.22 (cdc2)
 8,319 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

To date, several classes of enzymes have been shown to affect transcription by catalyzing the modifications of nucleosomes via methylation. Employing our global proteomic screen, GPS, we have determined that the loss of Bur2, a component of the Bur1/Bur2 cyclin-dependent protein kinase, results in a decrease in histone H3(K4) methylation catalyzed by COMPASS. Furthermore, Bur1/Bur2 is required for histone H2B monoubiquitination by Rad6/Bre1. The effect on histone monoubiquitination and methylation is the result of defective Bur1/Bur2-mediated phosphorylation of Rad6 on its serine residue 120 and proper recruitment of the Paf1 complex to chromatin. We have also demonstrated that serine 120 of Rad6 is required for histone H2B monoubiquitination and the regulation of gene expression in vivo. Our results identify in vivo substrates for Bur1/Bur2, thus linking its role to transcriptional elongation and demonstrating a potential activation mechanism for histone H2B monoubiquitination by the Rad6/Bre1 complex.
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PMID:The Bur1/Bur2 complex is required for histone H2B monoubiquitination by Rad6/Bre1 and histone methylation by COMPASS. 1630 22

Meta-predictors make predictions by organizing and processing the predictions produced by several other predictors in a defined problem domain. A proficient meta-predictor not only offers better predicting performance than the individual predictors from which it is constructed, but it also relieves experimentally researchers from making difficult judgments when faced with conflicting results made by multiple prediction programs. As increasing numbers of predicting programs are being developed in a large number of fields of life sciences, there is an urgent need for effective meta-prediction strategies to be investigated. We compiled four unbiased phosphorylation site datasets, each for one of the four major serine/threonine (S/T) protein kinase families-CDK, CK2, PKA and PKC. Using these datasets, we examined several meta-predicting strategies with 15 phosphorylation site predictors from six predicting programs: GPS, KinasePhos, NetPhosK, PPSP, PredPhospho and Scansite. Meta-predictors constructed with a generalized weighted voting meta-predicting strategy with parameters determined by restricted grid search possess the best performance, exceeding that of all individual predictors in predicting phosphorylation sites of all four kinase families. Our results demonstrate a useful decision-making tool for analysing the predictions of the various S/T phosphorylation site predictors. An implementation of these meta-predictors is available on the web at: http://MetaPred.umn.edu/MetaPredPS/.
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PMID:Meta-prediction of phosphorylation sites with weighted voting and restricted grid search parameter selection. 1823 18