Death-associated protein kinase (DAPk) and DAPk-related protein kinase (DRP)-1 proteins are Ca+2/calmodulin–regulated Ser/Thr death kinases whose precise roles in programmed cell death are still mostly unknown. In this study, we dissected the subcellular events in which these kinases are involved during cell death. Expression of each of these DAPk subfamily members in their activated forms triggered two major cytoplasmic events: membrane blebbing, characteristic of several types of cell death, and extensive autophagy, which is typical of autophagic (type II) programmed cell death. These two different cellular outcomes were totally independent of caspase activity. It was also found that dominant negative mutants of DAPk or DRP-1 reduced membrane blebbing during the p55/tumor necrosis factor receptor 1–induced type I apoptosis but did not prevent nuclear fragmentation. In addition, expression of the dominant negative mutant of DRP-1 or of DAPk antisense mRNA reduced autophagy induced by antiestrogens, amino acid starvation, or administration of interferon-γ. Thus, both endogenous DAPk and DRP-1 possess rate-limiting functions in these two distinct cytoplasmic events. Finally, immunogold staining showed that DRP-1 is localized inside the autophagic vesicles, suggesting a direct involvement of this kinase in the process of autophagy.
DAP kinase is a new type of calcium/calmodulin-dependent enzyme that phosphorylates serine/threonine residues on proteins. Its structure contains ankyrin repeats and the 'death' domain, and it is associated with the cell cytoskeleton. The gene encoding DAP kinase was initially isolated as a positive mediator of apoptosis induced by interferon-gamma, by using a strategy of functional cloning. We have now tested whether this gene has tumour-suppressive activity. We found that lung carcinoma clones, characterized by their highly aggressive metastatic behaviour and originating from two independent murine lung tumours, did not express DAP kinase, in contrast to their low-metastatic counterparts. Restoration of DAP kinase to physiological levels in high-metastatic Lewis carcinoma cells suppressed their ability to form lung metastases after intravenous injection into syngeneic mice, and delayed local tumour growth in a foreign 'microenvironment' Conversely, in vivo selection of rare lung lesions following injection into syngeneic mice of low-metastatic Lewis carcinoma cells or of DAP kinase transfectants, was associated with loss of DAP kinase expression. In situ TUNEL staining of tumour sections revealed that DAP kinase expression from the transgene raised the incidence of apoptosis in vivo. DAP-kinase transfectants also showed increased sensitivity in vitro to apoptotic stimuli, of the sort encountered by metastasizing cells at different stages of malignancy. We propose that loss of DAP kinase expression provides a unique mechanism that links suppression of apoptosis to metastasis.
In this study we describe the identification and structure-function analysis of a novel death-associated protein (DAP) kinase-related protein, DRP-1. DRP-1 is a 42-kDa Ca
The application of structure-based in silico methods to drug discovery is still considered a major challenge, especially when the x-ray structure of the target protein is unknown. Such is the case with human G protein-coupled receptors (GPCRs), one of the most important families of drug targets, where in the absence of x-ray structures, one has to rely on in silico 3D models. We report repeated success in using ab initio in silico GPCR models, generated by the PREDICT method, for blind in silico screening when applied to a set of five different GPCR drug targets. More than 100,000 compounds were typically screened in silico for each target, leading to a selection of <100 ''virtual hit'' compounds to be tested in the lab. In vitro binding assays of the selected compounds confirm high hit rates, of 12-21% (full dose-response curves, K i < 5 M). In most cases, the best hit was a novel compound (New Chemical Entity) in the 1-to 100-nM range, with very promising pharmacological properties, as measured by a variety of in vitro and in vivo assays. These assays validated the quality of the hits as lead compounds for drug discovery. The results demonstrate the usefulness and robustness of ab initio in silico 3D models and of in silico screening for GPCR drug discovery.modeling ͉ in silico screening ͉ structure-based G protein-coupled receptors (GPCRs) are membraneembedded proteins, responsible for communication between the cell and its environment (1). As a consequence, many major diseases, such as hypertension, cardiac dysfunction, depression, anxiety, obesity, inflammation, and pain, involve malfunction of these receptors (2), making them among the most important drug targets for pharmacological intervention (3-5). Thus, whereas GPCRs are only a small subset of the human genome, they are the targets for Ϸ50% of all recently launched drugs (6). As targets of paramount importance, it is expected that drug discovery for GPCRs would benefit from the introduction of computational methodologies (7), especially as these methods can be used in conjunction with such experimental methods as high-throughput screening (8, 9), NMR, and crystallography (10).Unfortunately, GPCRs, like other membrane-embedded proteins, have characteristics that make their 3D structure extremely difficult to determine experimentally. To date, the only GPCR for which a 3D structure was determined by x-ray crystallography is bovine rhodopsin (11), which is unique among GPCRs in that its ligand, retinal, is covalently bound and that it responds to light rather than to ligand binding. Hence, in the case of GPCRs, the limited availability of structural data has forced the computational design of ligands to heavily rely on ligand-based techniques. Indeed, for many GPCRs, the natural ligand can provide a good starting point, leading to useful pharmacophore models that can be used for identifying lead structures with novel scaffolds (6). These methods have been successfully applied for the discovery of peptide agonists to the somatostatin receptor (12) and for...
G-protein coupled receptors (GPCRs) are a major group of drug targets for which only one x-ray structure is known (the nondrugable rhodopsin), limiting the application of structure-based drug discovery to GPCRs. In this paper we present the details of PREDICT, a new algorithmic approach for modeling the 3D structure of GPCRs without relying on homology to rhodopsin. PREDICT, which focuses on the transmembrane domain of GPCRs, starts from the primary sequence of the receptor, simultaneously optimizing multiple 'decoy' conformations of the protein in order to find its most stable structure, culminating in a virtual receptor-ligand complex. In this paper we present a comprehensive analysis of three PREDICT models for the dopamine D2, neurokinin NK1, and neuropeptide Y Y1 receptors. A shorter discussion of the CCR3 receptor model is also included. All models were found to be in good agreement with a large body of experimental data. The quality of the PREDICT models, at least for drug discovery purposes, was evaluated by their successful utilization in in-silico screening. Virtual screening using all three PREDICT models yielded enrichment factors 9-fold to 44-fold better than random screening. Namely, the PREDICT models can be used to identify active small-molecule ligands embedded in large compound libraries with an efficiency comparable to that obtained using crystal structures for non-GPCR targets.
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