Structural basis and prediction of substrate specificity in protein serine/threonine kinases

The large number of protein kinases makes it impractical to determine their specificities and substrates experimentally. Using the available crystal structures, molecular modeling, and sequence analyses of kinases and substrates, we developed a set of rules governing the binding of a heptapeptide substrate motif (surrounding the phosphorylation site) to the kinase and implemented these rules in a web-interfaced program for automated prediction of optimal substrate peptides, taking only the amino acid sequence of a protein kinase as input. We show the utility of the method by analyzing yeast cell cycle control and DNA damage checkpoint pathways. Our method is the only available predictive method generally applicable for identifying possible substrate proteins for protein serine/threonine kinases and helps in silico construction of signaling pathways. The accuracy of prediction is comparable to the accuracy of data from systematic large-scale experimental approaches.

Extinction times for a birth-death process with two phases

Many populations have a negative impact on their habitat or upon other species in the environment if their numbers become too large. For this reason they are often subjected to some form of control. One common control regime is the reduction regime: when the population reaches a certain threshold it is controlled (for example culled) until it falls below a lower predefined level. The natural model for such a controlled population is a birth-death process with two phases, the phase determining which of two distinct sets of birth and death rates governs the process. We present formulae for the probability of extinction and the expected time to extinction, and discuss several applications. (c) 2006 Elsevier Inc. All rights reserved.

Neural progenitor number is regulated by nuclear factor-kappa B p65 and p50 subunit-dependent proliferation rather than cell survival

The number of cells generated by a proliferating stem or precursor cell can be influenced both by proliferation and by the degree of cell death/survival of the progeny generated. In this study, the extent to which cell survival controls progenitor number was examined by comparing the growth characteristics of neurosphere cultures derived from mice lacking genes for the death inducing Bcl-2 homologue Hara Kiri (Hrk), apoptosis-associated protein 1 (Apaf1), or the prosurvival nuclear factor-kappa B (NF kappa B) subunits p65, p50, or c-rel. We found no evidence that Hrk or Apaf1, and by inference the mitochondrial cell death pathway, are involved in regulating the number of neurosphere-derived progeny. However, we identified the p65p50 NF kappa B dimer as being required for the normal growth and expansion of neurosphere cultures. Genetic loss of both p65 and p50 NF kappa B subunits resulted in a reduced number of progeny but an increased proportion of neurons. No effect on cell survival was observed. This suggests that the number and fate of neural progenitor cells are more strongly regulated by cell cycle control than survival. (c) 2005 Wiley-Liss, Inc.

The complexity of p53 stabilization and activation

A number of proteins are activated by stress stimuli but none so spectacularly or with the degree of complexity as the tumour suppressor p53 (human p53 gene or protein). Once stabilized, p53 is responsible for the transcriptional activation of a series of proteins involved in cell cycle control, apoptosis and senescence. This protein is present at low levels in resting cells but after exposure to DNA-damaging agents and other stress stimuli it is stabilized and activated by a series of post-translational modifications that free it from MDM2 (mouse double minute 2 but used interchangeably to denote human also), a ubiquination ligase that ubiquitinates it prior to proteasome degradation. The stability of p53 is also influenced by a series of other interacting proteins. In this review, we discuss the post-translational modifications to p53 in response to different stresses and the consequences of these changes.

Further evidence of linkage at 7p22 with familial hyperaldosteronism type II and exclusion of genetic defects in the RBAK coding regions

Once thought rare, primary aldosteronism (PAL) is now reported to be responsible for 5–10% of hypertension. Unlike familial hyperaldosteronism type I (FH-I), FH-II is not glucocorticoidremediable and not associated with the hybrid CYP11B1/CYP11B2 gene mutation. At least five times more common than FH-I, FH-II is clinically indistinguishable from apparently sporadic PAL, suggesting an even higher incidence. Studies performed in collaboration with C Stratakis (NIH, Bethesda) on our largest Australian family (eight affected members) demonstrated linkage at chromosome 7p22. Linkage at this region was also found in a South American family (DNA provided by MI New, Mount Sinai School of Medicine, New York) and in a second Australian family. The combined multipoint LOD score for these 3 families is 4.61 (q = 0) with markers D7S462 and D7S517, providing strong support for this locus harbouring mutations responsible for FH-II. A newly identified recombination event in our largest Australian family has narrowed the region of linkage by 1.8 Mb, permitting exclusion of approximately half the genes residing in the originally reported 5 Mb linked locus. Candidate genes that are involved in cell cycle control are of interest as adrenal hyperplasia and adrenal adenomas are common in FH-II patients. A novel candidate gene in this linked region produces the retinoblastoma-associated Kruppel-associated box protein (RBaK) which interacts with the retinoblastoma gene product to repress the expression of genes activated by members of the E2F family of transcription factors.

Exploration of the cell-cycle genes found within the RIKEN FANTOM2 data set

The cell cycle is one of the most fundamental processes within a cell. Phase-dependent expression and cell-cycle checkpoints require a high level of control. A large number of genes with varying functions and modes of action are responsible for this biology. In a targeted exploration of the FANTOM2-Variable Protein Set, a number of mouse homologs to known cell-cycle regulators as well as novel members of cell-cycle families were identified. Focusing on two prototype cell-cycle families, the cyclins and the NIMA-related kinases (NEKs), we believe we have identified all of the mouse members of these families, 24 cyclins and 10 NEKs, and mapped them to ENSEMBL transcripts. To attempt to globally identify all potential cell cycle-related genes within mouse, the MGI (Mouse Genome Database) assignments for the RIKEN Representative Set (RPS) and the results from two homology-based queries were merged. We identified 1415 genes with possible cell-cycle roles, and 1758 potential paralogs. We comment on the genes identified in this screen and evaluate the merits of each approach.